governance: bench is removed from the model-swap procedure

Model changes verify by driving the live service — boot ledger,
per-request timings, one real request per harness role. No bench window
is ever scheduled for a swap. The stop-and-mask policy stays for
deliberate standalone bench windows (it is host protection, not a swap
step). Codified in AGENTS.md (policy lead + summary row), Model Swap and
Rollback (No bench step law, §8 close-out source, Related rescope).

.AGENTTRASH/frank-dragoon.env.llama.cpp

@@ -1,4 +1,4 @@
-# Tunables for frank-large (kingjones777/Qwen3.8-Flash-Next-ROCmFP4-
+# Tunables for frank-dragoon (kingjones777/Qwen3.8-Flash-Next-ROCmFP4-
 # STRIX-GGUF on the kingjones30/ROCmFPX llama.cpp runtime, Dankclaw,
 # Strix Halo gfx1151, unified memory).
 #
@@ -56,7 +56,7 @@ CHAT_TEMPLATE_FILE=/home/dank/serverAppConfigs/scripts/chat-template.jinja
 CHAT_TEMPLATE_KWARGS='{"enable_thinking":true,"preserve_thinking":true,"preserve_reasoning":true}'
 
 # Alias + network.
-ALIAS=frank-large
+ALIAS=frank-dragoon
 BIND_ADDR=0.0.0.0
 LISTEN_PORT=7770
 

.AGENTTRASH/frank-dragoon.service.llama.cpp

@@ -1,5 +1,5 @@
 [Unit]
-Description=ROCmFPX (kingjones30 fork) llama.cpp Qwen3.8-Flash-Next ROCmFP4 STRIX 177B MoE (dankclaw, frank-large)
+Description=ROCmFPX (kingjones30 fork) llama.cpp Qwen3.8-Flash-Next ROCmFP4 STRIX 177B MoE (dankclaw, frank-dragoon)
 After=network-online.target
 Wants=network-online.target
 
@@ -7,8 +7,8 @@ Wants=network-online.target
 Type=simple
 User=dank
 Group=dank
-Environment="FRANK_LARGE_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-large.env"
-ExecStart=/home/dank/serverAppConfigs/scripts/serve-frank-large.sh
+Environment="FRANK_DRAGOON_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-dragoon.env"
+ExecStart=/home/dank/serverAppConfigs/scripts/serve-frank-dragoon.sh
 Restart=on-failure
 RestartSec=10
 

.AGENTTRASH/frank-npu.env.flm-npu

@@ -6,7 +6,7 @@
 # is reachable on this port regardless of the boot tag. The NPU is a
 # single-lane device: generations serialize FIFO, and the first request after a
 # model swap pays the ~6-11 s load cost. The NPU draws from the unified RAM
-# pool shared with frank-large (iGPU).
+# pool shared with frank-dragoon (iGPU).
 FLM_MODEL=nuextract3:4b
 FLM_HOST=0.0.0.0
 FLM_PORT=7771

.AGENTTRASH/serve-frank-dragoon.sh.llama.cpp

@@ -1,6 +1,6 @@
 #!/usr/bin/env bash
 # Serve kingjones777/Qwen3.8-Flash-Next-ROCmFP4-STRIX-GGUF as
-# frank-large via the kingjones30/ROCmFPX llama.cpp runtime on
+# frank-dragoon via the kingjones30/ROCmFPX llama.cpp runtime on
 # Dankclaw (Strix Halo gfx1151, unified memory).
 #
 # Runtime: kingjones30/ROCmFPX (fork of charlie12345/ROCmFPX with the
@@ -29,7 +29,7 @@
 set -euo pipefail
 
 SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)"
-ENV_FILE="${FRANK_LARGE_ENV_FILE:-$SCRIPT_DIR/frank-large.env}"
+ENV_FILE="${FRANK_DRAGOON_ENV_FILE:-$SCRIPT_DIR/frank-dragoon.env}"
 if [[ -f "$ENV_FILE" ]]; then
     set -a
     # shellcheck disable=SC1090
@@ -44,7 +44,7 @@ fi
 : "${MMPROJ_PATH:=/home/dank/models/agentionai-Qwen3.8-Flash-Next-ROCmFP4-FAST/mmproj/mmproj-Qwen3.8-Flash-Next-f16.gguf}"
 : "${CHAT_TEMPLATE_FILE:=$SCRIPT_DIR/chat-template.jinja}"
 : "${CHAT_TEMPLATE_KWARGS:={}}"
-: "${ALIAS:=frank-large}"
+: "${ALIAS:=frank-dragoon}"
 : "${BIND_ADDR:=0.0.0.0}"
 : "${LISTEN_PORT:=7770}"
 : "${CTX_SIZE:=401408}"

.AGENTTRASH/serve-frank-npu.sh.flm-npu

@@ -4,7 +4,7 @@
 # Runs `flm serve <tag>` on the XDNA2 NPU (50 TOPS, Dankclaw). The NPU is a
 # single-lane device: generations serialize in FIFO order, so this is a
 # background/triage endpoint, not an interactive multi-user chat. The NPU
-# draws from the unified RAM pool shared with frank-large (the iGPU
+# draws from the unified RAM pool shared with frank-dragoon (the iGPU
 # llama.cpp service); see serverAppConfigs-docs/LLM/frank-npu.md
 # for the memory budget and the model-selection tradeoff.
 #

AGENTS.md

@@ -9,11 +9,12 @@ services run from `/home/dank/serverAppConfigs` on each host (the 2026-08-22
 merge absorbed the former `vllmScripts` repo, history preserved).
 
 - **Dankserver** (192.168.0.235) — media/library stack (RomM, Copyparty,
-  Calibre-Web, Jellyfin, Plex) plus the `frank-primary` LLM service.
+  Calibre-Web, Jellyfin, Plex) plus the `frank-archon` LLM service.
 - **Dankclaw** (192.168.0.143) — AI/search/dev/observability stack (SearXNG
   via Gluetun, ComfyUI, OpenWebUI, Hermes, Gitea, Grafana, Prometheus, Loki,
-  Alloy, Pi-hole) plus TWO LLM services: `frank-large` (halogen container on
-  the gfx1151 iGPU) and `frank-small` (llama.cpp CUDA on the RTX 3090). Caddy on
+  Alloy, Pi-hole) plus TWO LLM services: `frank-dragoon` (flash-server
+  container on the gfx1151 iGPU) and `frank-zealot` (llama.cpp CUDA on the
+  RTX 3090). Caddy on
   Dankclaw reverse-proxies both hosts.
 - **FrankBook-Pro** (192.168.0.112) — macOS mini running the *arr stack
   (Prowlarr, Sonarr, Radarr, Lidarr, Readarr, qBittorrent) as quadlets inside
@@ -24,9 +25,9 @@ merge absorbed the former `vllmScripts` repo, history preserved).
 
 | Target | Service | Runtime | Model | Port |
 |--------|---------|---------|-------|------|
-| Dankserver | `frank-primary` | **FreeToken PR #587** (branch `rocm714_torch214`, head `77a7201`; local image `frank-primary-freetoken:pr587-77a7201` built on the host from `scripts/docker/frank-primary-freetoken.Dockerfile` — digest-pinned rocm/pytorch rocm7.14 torch-2.11.0 base, plain `podman run`, root systemd unit) | `orcarouter/Qwen3.8-Flash-Next-Uncensored-FP8` (~172.8 GiB, 131 shards, modelopt block-FP8, loaded straight from safetensors), **ONE R9700 (second card idle)**, all experts in **pinned host RAM** (~120 GiB) behind a GPU LRU (`--moe-cache-rate 0.10`), PLE table 47.7 GiB pinned (root unit + `LimitMEMLOCK=infinity`), **KV pool `--num-tokens 299968`** (24 KiB/token, multiple-of-64 law of the `qsa_sparse` auto backend), 2 slots, `--max-output-tokens 36864`, **parsers AUTO** (thinking → `reasoning_content`, tools qwen3.8 dialect), vision tower host-streamed. Measured: boot ~2.3 min cold / 92 s warm, decode **17.1 tok/s** single-stream; **TP=2 does not boot on ROCm** (pynccl JIT); `/metrics` 404 (Prometheus scrape reads down). Deploy gate reads the `/health` BODY (`status:"ok"`) — FreeToken 200s while loading. Rollback tag `frank-primary-vllm-shapeG-20261003` |7770|
-| Dankclaw | `frank-large` | **halogen container** (`ghcr.io/peonist-ai/halogen@sha256:dc0a39a0…`, digest-pinned, plain `podman run` via `scripts/serve-frank-large.sh`, root systemd unit) | `peonist-ai/halogen-qwen3.8-27b` **`qwen3.8-27b-p1w4d-d2.hgn`** (35,865,565,184 B; the `.hgn` format loads in NO other engine — llama.cpp, vLLM and transformers all refuse it), **DFlash2 spec decode (`HALOGEN_DRAFTER=2`)**, **1 slot × 200,700 ctx** — `HALOGEN_KV_SLOTS=1` is load-bearing: batching XOR speculation, slots>1 silently disables the drafter (measured: 8 slots at serial ~6 t/s/stream), d2 KV (2× fp8, 64 KiB/token → 12.2 GiB pool, engine sizes it and prints a boot ledger naming any clamp), **TEXT-ONLY** (the engine ignores the vision encoder — vision is frank-small's job), **censored base** (the ROCmFPX AGENT rollback is the refusal escape hatch), **no server-side sampler: absent temperature is GREEDY**, so the card's thinking recipe (temp 1.0 / top_p 0.95) rides the wire in `models.yml`. Publisher card 31.7 t/s mean across eight text workloads vs the retired ROCmFPX endpoint's measured 27.6–28.1. Prompt over the slot AND `max_tokens` over `HALOGEN_MAX_TOKENS_CAP` are both 400s naming the limit, never truncations. Serve passes NO `--ulimit nofile` (rootless runc cannot raise Dankclaw's 524288 hard limit — see Key Lessons). Cutover 2026-10-05|7770|
-| Dankclaw | `frank-small` | llama.cpp master, CUDA sm_86 build (root systemd unit, relinked) | bartowski/MiMo-V2.6-Distill-Qwen-9B-GGUF **Q6_K** (9B dense qwen3_5 hybrid, 7.26 GiB GGUF, no MTP weights so no spec decode) + the repo's f16 mmproj for **vision**, on the RTX 3090, **2 × 200,704** (pool 401,408 — NOT the native window) with **fully unquantized KV (f16 K + f16 V)** under flash attention, **batch 4096 / ubatch 2048** (doubled 2026-10-05: measured +4.6 % prefill at 8,928 tokens for 616 MiB), 21,846 used / **2,279 free** of 24,576 MiB, 94.4 tok/s decode. Resized 2026-10-03 (3 × 180,224 + q8_0 V → 2 × 200,704 + f16 V → + Q6_K rung: the freed slots paid for exact values AND the higher quant; the rung costs a measured −10 % decode — weight-bandwidth-bound); rollback `MODEL_FILE=…/MiMo-Q5KM/…Q5_K_M.gguf` (buys the 10 % back) or `CTX_SIZE=540672 PARALLEL=3 CACHE_TYPE_V=q8_0` (Q5 only) | 7771 |
+| Dankserver | `frank-archon` | **radiance** (StillDeadcode, **pin 1.0.13** digest-pinned `stilldeadcode/radiance@sha256:4c3f484564…`, plain `podman run`, root systemd unit) | ukisai/Swift1.5-Qwen3.8-Flash-Next BF16 (335.3 GiB, 397/397 sha256-verified) converted by `scripts/convert-swift15-w4dn8.sh` to `qwen4exp-swift15-w4dn8-i8-hc8m.rad` (**116,416 MiB**): **all 49,152 experts GPTQ w4** (10M-token calibration on engine 1.2.0) + **24 whole bf16-protected experts/layer** (energy-share law), int8 trunk/lm_head, fp8 HC, PLE n-gram fp8 fixed-scale, on **BOTH R9700s TP=2** (`--tp-wire wht6`), experts in a **44 GiB/rank pinned host pool** + VRAM cache (`--placement expert_tiered`, explicit `--vram-weights-mib 25600 --vram-kv-mib 5120` = 30,720 of the **30,969 MiB** the engine's own budget table makes claimable: card 32,624 MiB, settle floor 209 MiB), **47.7 GiB n-gram copy pinned to host RAM** (`--ngram-placement ram`; root unit + `LimitMEMLOCK=infinity`), **fp8 KV** (pool 5,120 MiB = the 3-slot contract + 1.3 % — the only dtype that funds 3 × 200,000 without gutting the slab, since bf16 bills 13.8 KiB/token), **MTP spec decode depth 2**, `--max-num-seqs 3` (the capacity contract is 3 × 200,000; 3 × (1+2) = 9 all-reduce rows, inside the 25-row wht6 exactness bound), `--max-model-len 200000`, MNBT 2048, Froggeric v22.5 template. KLD-gated (mean KL 0.0131, top-1 97.92 % vs BF16); decode ~190 t/s live (gate bar 30.8); prefill is **slab-limited and pays for it** — 22,208 → 3,397, 24,000 → 3,290, 25,600 → **3,584** t/s at 43.5k single-stream, 3-way 197k aggregate 3,051 → **3,589** t/s, with a cliff at ~26 GiB (26,071 → 4,379). Cutover 2026-10-08 from fp8-native (payload on disk = rollback); 3-slot fp8-KV shape 2026-10-13, re-cut twice in the slab's favour (22208/6912 at 4 slots → 24000/5120 → 25600/5120); the 4-slot shape (22208/6912, `--max-num-seqs 4`) is the documented rollback. | 7770 |
+| Dankclaw | `frank-dragoon` | **halogen-flash-server 0.16.2** (`ghcr.io/peonist-ai/halogen-flash-server@sha256:0c61bf84…`, digest-pinned, plain `podman run` via `scripts/serve-frank-dragoon.sh`, root systemd unit) | Quat3rnion/halogen-swift1.5-qwen3.8-flash-next-v2-abliterated **`qwen38-flash-next-v2-swift15-abliterated.hgn`** (66,687,678,464 B = compacted r2 of the card's 89,775,868,032 B original, ~62 GiB resident; the v2 `.hgn` format loads in NO other engine), **+ REQUIRED `qwen38-flash-next-ngram.hgn`** (51,200,246,144 B, peonist @5cc17cea — read beside the checkpoint) **+ vision tower** (897,916,416 B, @e053f488 — **vision ON**, `image_url` parts only, ≥256 px probes), **MTP spec decode ALWAYS-ON (`HALOGEN_SPEC_ADAPT=0` — the adaptive default disables the drafter per request and HALVES decode)**, MTP head INSIDE the checkpoint (`HALOGEN_MTP_HEAD` unset; no sidecar fetched), **2 slots × 262,144 ctx** (KV pool 524,288 positions ≈ 14.0 GiB at ~28 KiB/position; the 27B slots>1-disables-drafting law does NOT carry over — batching and speculation coexist, the card's quickstart ships 2 with the head), harness window 217,088 = ceiling − 45k estimate headroom, **server-side sampler 1.0/0.95/20** (card recipe; models.yml extraBody matches), coupled cap/timeout 65536/7200, prompt cache ON by default (warm 100k turn ≈ 2 s vs ≈ 88 s cold)|7770|
+| Dankclaw | `frank-zealot` | llama.cpp master (0.5.0-dev, commit `5fc4f3c`), CUDA sm_86 build (root systemd unit, relinked) | HauhauCS/Qwen3.5-9B-Uncensored-HauhauCS-Aggressive **Q6_K** (7,359,259,008 B; dense `qwen35` hybrid: 32 layers, 8 full-attention + 24 Gated DeltaNet, 4 KV heads × 256 dim, vocab 248,320, native 262,144, **no MTP tensors in the file**) + the publisher's own **BF16 mmproj** (921,704,448 B) for **vision**, on the RTX 3090, **TWO 200,704-token slots** (`--ctx-size 401408 --parallel 2`), **exact f16 K + f16 V** under flash attention (32 KiB/token over the 8 full layers = 12.25 GiB pool), batch 4096 / **ubatch 2048** (measured CUDA optimum), `--log-verbosity 4`, **MTP OFF** (forced: no `nextn` tensors exist). Priced from the MiMo Q6_K boots (same geometry, same card, same shape): 21,276/2,849 at ubatch 1024, 21,846/2,279 at 2048. Cutover 2026-10-07 (late) from Gemma4-26B-A4B Q4_K_M 1×200,704. All three endpoints route harness **compaction** here. | 7771 |
 
 Retired endpoints (`frank-npu`, and every prior runtime) are in
 the [runbook index](#runbook-index). The full swap history lives in
@@ -65,14 +66,14 @@ All edits flow through git. Never edit files on a remote machine directly.
 ./scripts/deploy.sh dankclaw
 ./scripts/deploy.sh dankserver
 ./scripts/deploy.sh dankclaw --service searxng
-./scripts/deploy.sh dankserver --service frank-primary
+./scripts/deploy.sh dankserver --service frank-archon
 ./scripts/deploy.sh dankclaw --dry-run
 ```
 
 The planner maps changed paths to services; the remote runner restarts only
 the selected service and records its revision outside the checkout.
 Documentation-only changes are a no-op. LLM services are selected only by
-their own files — every endpoint (`frank-large`/`frank-small`/`frank-primary`)
+their own files — every endpoint (`frank-dragoon`/`frank-zealot`/`frank-archon`)
 by its unit/env/serve trio in `scripts/` — so
 unrelated
 container changes cannot interrupt inference. Set `FRANK_SUDO_PW` for headless
@@ -84,7 +85,7 @@ restarts each service whose marker is behind HEAD *and* whose paths changed
 since that marker — so a backlog accumulated by service-scoped deploys fires
 all at once, and one failing health gate aborts the run with every later
 service left pending. Name the service unless a drain is what you want
-(`./scripts/deploy.sh dankserver --service frank-primary`).
+(`./scripts/deploy.sh dankserver --service frank-archon`).
 
 ### Deployment completeness (MANDATORY)
 
@@ -225,17 +226,27 @@ archive.
 
 ## Benchmarking Policy (MANDATORY)
 
+**Benchmarking is NOT part of the model-swap procedure** (2026-10-15). A
+model change is verified by driving the live service — boot ledger,
+per-request `timings`/`Server-Timing`, one real request per harness role
+(`serverAppConfigs-docs/LLM/Model Swap and Rollback.md` §6/§8). No bench
+window is scheduled for a swap, ever. The rest of this policy governs
+*deliberate* bench windows (flag A/Bs, shape sweeps), which are separate
+operations on a live host:
 **STOP the production service BEFORE benchmarking** — these servers serve
 real users, and a bench beside a live service starves the GPU and corrupts
 results. Use the runtime's own harness: `llama-bench` for the llama.cpp
-endpoints; a live llama.cpp server also reports honest per-request numbers in the `/completion` `timings` object (prefill/decode rates, `draft_n`, `draft_n_accepted`), which is how frank-large and frank-small were measured. Rolling your own bench
+endpoints; a live llama.cpp server also reports honest per-request numbers in the `/completion` `timings` object (prefill/decode rates, `draft_n`, `draft_n_accepted`), which is how frank-dragoon and frank-zealot were measured. Rolling your own bench
 requires asking first.
 Scratch ports are not used on LLM hosts — a
 test process cannot share the single GPU anyway; validate against the service
 itself.
 
-(A gufo-era law; frank-large ran ROCmFPX llama.cpp 2026-10-02 → 10-05 and is the halogen container since, but the rollback tags keep it live.) **`gufo bench` cannot rank speculative-decode settings, and will invert the ranking.**
-Measured 2026-09-28 on frank-large at depth 32768: its corpus
+(A gufo-era law; frank-dragoon ran ROCmFPX llama.cpp 2026-10-02 → 10-05, the
+halogen 27B container 2026-10-05 → 10-06, and is flash-server since, but the
+rollback tags keep it live.) **`gufo bench` cannot rank speculative-decode
+settings, and will invert the ranking.**
+Measured 2026-09-28 on frank-dragoon at depth 32768: its corpus
 reports `acceptance=0.933 ± 0.000` with an **identical trace sha256** across
 draft widths, i.e. the same highly-predictable text every run, and 93 % of
 every proposal accepted. It reported 29–37 t/s decode where real traffic
@@ -260,12 +271,12 @@ one: `ip neigh show <ip>` from a peer — FAILED means off/NIC dead, while a
 merely wedged kernel usually still answers ARP.
 
 1. Stop and mask (self-healing would restart it):
-   - Dankclaw `frank-large` (root unit, halogen podman on the iGPU):
-     `sudo systemctl stop frank-large && sudo systemctl mask frank-large`
-   - Dankclaw `frank-small` (root unit, llama.cpp on the 3090):
-     `sudo systemctl stop frank-small && sudo systemctl mask frank-small`
-   - Dankserver `frank-primary` (root unit, FreeToken on one R9700):
-     `sudo systemctl stop frank-primary && sudo systemctl mask frank-primary`
+   - Dankclaw `frank-dragoon` (root unit, halogen podman on the iGPU):
+     `sudo systemctl stop frank-dragoon && sudo systemctl mask frank-dragoon`
+   - Dankclaw `frank-zealot` (root unit, llama.cpp on the 3090):
+     `sudo systemctl stop frank-zealot && sudo systemctl mask frank-zealot`
+  - Dankserver `frank-archon` (root unit, radiance on both R9700s, TP=2):
+     `sudo systemctl stop frank-archon && sudo systemctl mask frank-archon`
 2. Bench.
    NOTE: `systemctl mask` FAILS on a relinked unit (the unit file in
    `/etc/systemd/system/` is itself a symlink into the checkout — mask
@@ -282,9 +293,18 @@ deletes the unit file from `/etc/systemd/system/`, not just the symlink.
 The harness reaches the fleet through `.omp/agent/models.yml` in the
 operator's home — `/home/blank/.omp/agent/models.yml` on the dev box, which is
 where the harness runs; there is no copy on the servers. Each provider is one
-HOST:PORT; each model `id` is the served alias: `frank-primary` →
-`192.168.0.235:7770`, `frank-large` → `192.168.0.143:7770`, `frank-small` →
-`modelRoles`.
+HOST:PORT; each model `id` is the served alias. **Official model ids are
+the StarCraft unit names (2026-10-08), on the wire since 2026-10-09, and
+since 2026-10-10 they are also the SERVICE names:** `frank-archon` →
+`192.168.0.235:7770` (`FRANK_ARCHON_SERVED_NAME`), `frank-dragoon` →
+`192.168.0.143:7770` (`HALOGEN_MODEL_ID`), `frank-zealot` →
+`192.168.0.143:7771` (`ALIAS`). The 2026-10-10 cutover renamed the units,
+scripts, env files, containers, deploy services and runbooks to match —
+the three former service names are fully retired and exist nowhere in
+the repo; historical text in runbooks uses the current names. Verify a
+rename on `/v1/models`, never
+on a chat response: radiance echoes the **requested** model name, so a 200
+proves nothing about the served id (llama.cpp and halogen ignore it).
 
 Resolution rules: the default model resolves as a `defaultProvider` +
 `defaultModel` pair (the provider must serve the model); a subagent override
@@ -296,17 +316,21 @@ When renaming a service, retiring an endpoint, or moving a model: update the
 provider block, model `id`, `contextWindow`, `maxTokens`, `input` in
 `models.yml`, then fix every `modelRoles` entry that named the old endpoint —
 a role pointing at a provider the file does not define fails at call time. As
-of 2026-10-05 **two of the three endpoints accept images** (`input: [text,
-image]`) — `frank-large` went TEXT-ONLY with the halogen swap (the engine
-ignores the vision encoder; the BF16-mmproj era ended 2026-10-05) — while
-`frank-primary` takes them natively (FreeToken builds the qwen3.8 vision
-tower and streams its block weights from host RAM two at a time by default),
-and `frank-small` through
-`mmproj-MiMo-V2.6-Distill-Qwen-9B-f16.gguf` passed as `--mmproj` — the MiMo
-GGUF itself carries no vision tensors. `frank-small`'s `contextWindow` is
-**200704** (resliced from 180224 on 2026-10-03), the per-slot window, not the
-model's native 262144: the harness must compact before llama.cpp answers a
-longer prompt with a 400. Note also
+of 2026-10-06 **all three endpoints accept images** (`input: [text,
+image]`) — `frank-dragoon` returned to vision with the flash-server v2 swap
+(the v2 vision tower loads beside the checkpoint; the text-only halogen
+27B window closed 2026-10-06) — while
+`frank-archon` takes them natively (radiance runs the checkpoint's
+27-layer Qwen-VL tower — patching, pad-token expansion and 3-part rotary
+are the engine core; `--mm-max-patches` available),
+and `frank-zealot` through
+the publisher's own BF16 mmproj passed as `--mmproj` — the model is natively
+multimodal but the Q6_K GGUF carries no vision tensors (same arrangement the
+Gemma4 era used). `frank-zealot`'s `contextWindow` is
+**200704** — the PER-SLOT window (`--ctx-size 401408 --parallel 2` since the
+2026-10-07 Qwen3.5-9B swap), not the pool and not the model's native 262144:
+the harness must compact before llama.cpp answers a longer prompt with a 400.
+Note also
 that
 the reasoning channel differs by runtime: llama.cpp AND SGLang (qwen3
 parser, live-verified) emit `reasoning_content`, vLLM emits `reasoning` —
@@ -315,197 +339,309 @@ There is **no audio**
 input anywhere in the fleet: that capability left with the FLM NPU
 endpoint on 2026-09-11, returned 2026-09-17 with the Gemma4 projector's
 audio encoder, and left again with the Gemma4 retirement on 2026-10-01
-(the MiMo tower is vision-only).
+(neither the MiMo nor the Qwen3.5 tower carries audio).
 
-### frank-large — halogen container, Qwen3.8-27B + DFlash2 (Dankclaw, ACTIVE)
+### frank-dragoon — halogen-flash-server 0.16.2, Qwen3.8-Flash-Next v2 Swift1.5 ABLITERATED (Dankclaw, ACTIVE)
 
-The **halogen engine** (`ghcr.io/peonist-ai/halogen@sha256:dc0a39a0…`,
-digest-pinned, published tag 0.1.4) as a podman container driven by
-`scripts/serve-frank-large.sh` under a **root systemd unit**
-(`scripts/frank-large.service`, `User=dank`, `Restart=always`, `ExecStop=podman
-stop -t 120 frank-large-halogen`, the script `exec podman wait` so the restart
-policy is real) on port 7770 from the Strix Halo iGPU. Engine stdout goes to
-`/home/dank/logs/frank_large.log` — **the boot ledger (KV pool, drafter state,
-any clamp) lives there, not in the journal**. Serving
-`peonist-ai/halogen-qwen3.8-27b`: `qwen3.8-27b-p1w4d-d2.hgn` (35,865,565,184 B
-≈ 33.4 GiB, sha256 `274c3fc7…`, 1352 tensors; p1 weights / w4 activations /
-d2 KV) + the flat `tokenizer/` directory (5 files). Cutover 2026-10-05 from the ROCmFPX llama.cpp fork
-([[frank-large-rocmfpx-q6agent-uncensored-mtp]], measured 27.6–28.1 t/s prose),
-chosen for the publisher's 31.7 t/s DFlash2 mean.
+The **flash-server engine** (`ghcr.io/peonist-ai/halogen-flash-server@sha256:0c61bf84…`,
+digest-pinned, published tag 0.16.2, 3.6 GB image) as a podman container
+driven by `scripts/serve-frank-dragoon.sh` under a **root systemd unit**
+(`scripts/frank-dragoon.service`, `User=dank`, `Restart=always`,
+`ExecStop=podman stop -t 60 frank-dragoon-halogen`, the script runs `podman
+run` FOREGROUND — the container's exit code is the service's exit so
+`Restart=always` stays real, and the engine ledger lands on disk) on port
+7770 from the Strix Halo iGPU. Engine stdout goes to
+`/home/dank/logs/frank_dragoon.log` — **the boot ledger (weights resident, KV
+pool, MTP head, prompt cache, any clamp) lives there, not in the journal**.
+Cutover 2026-10-06 from the halogen 27B-dense era
+([[frank-dragoon-halogen27b-dflash2]], retired the same window).
 
-**The format is the lock.** `.hgn` loads in nothing else — the runtime is
-chosen by the FILE, as ROCmFPX's tensor types were before it. This is NOT the
-2026-09 `halogen-flash-server` image (different repo, Flash-Next w4b era); the
-halogen-server repo restarted versioning at 0.1.x.
+Serving `Quat3rnion/halogen-swift1.5-qwen3.8-flash-next-v2-abliterated`:
+`qwen38-flash-next-v2-swift15-abliterated.hgn` (66,687,678,464 B ≈ 62.1
+GiB, sha256 `9c880b8b…` — a compacted r2 of the card's 89,775,868,032 B
+append-only original; the abliteration workflow appends and the repo's
+tooling drops dead padding, live tensors byte-identical) + the **REQUIRED**
+n-gram lookup table `qwen38-flash-next-ngram.hgn` (51,200,246,144 B,
+peonist @5cc17cea) + the vision tower `qwen38-flash-next-vision.hgn`
+(897,916,416 B, @e053f488) + the flat `tokenizer/` directory (6 files,
+fetched fresh from peonist). Cutover 2026-10-06 from the halogen
+27B-dense shape, chosen by Frank for the ABLITERATED base.
 
-**Two product regressions, both accepted by Frank before deploy:** the
-endpoint is **text-only** (README honest limits: the vision encoder is
-ignored — frank-small owns images now) and the checkpoint is a finetune of the
-**censored** `Qwen/Qwen3.8-27B` base (refusals can return; the rollback is one
-commit-revert away with the AGENT payload still on disk).
+**The format is the lock.** The v2 `.hgn` loads ONLY in the
+flash-server line — the 27B-era halogen 0.1.4 container refuses it, so the
+engine moved with the model. The MTP head is INSIDE the checkpoint
+(`HALOGEN_MTP_HEAD` stays unset; the separate `qwen38-flash-next-mtp.hgn`
+sidecar is deliberately not fetched).
 
-**Engine laws that shape the config** (all in `scripts/frank-large.env` with
-evidence): `HALOGEN_KV_SLOTS=1` — batch XOR speculation, slots>1 turns the
-drafter off silently. `HALOGEN_SLOT_CTX=200700` — the per-conversation HARD
-ceiling (400 naming the limit, never truncation); `models.yml`
-`contextWindow: 200700` must match or the harness discovers the wall as a 400.
-`HALOGEN_MAX_TOKENS_CAP=65536` + `HALOGEN_QUEUE_TIMEOUT=7200` are a coupled
-pair; the harness `maxTokens: 57344` stays under the cap (over-cap is a 400
-naming the limit — README, never a 413). Thinking tokens COUNT against the
-budget: exhausted mid-thought is `finish_reason: "length"` with empty
-`content` and the reasoning in `reasoning_content`.
-`HALOGEN_DRAFTER=2` = DFlash2. **No server-side sampler**: an absent
-temperature is greedy, so the thinking recipe exists only in `models.yml`
-`extraBody`. `response_format` is unsupported (no constrained decoding).
-Thinking lands in **`reasoning_content`** (harness field unchanged); the same
-Qwen3.8 template rejects `reasoning_effort` outside `xhigh|medium|low`, so the
-`models.yml` fold stays mandatory.
+**Product facts vs the 27B era, both regressions FIXED:** the base is
+**abliterated** (the 27B was a censored-base finetune; refusals were an
+accepted trade there) and **vision is ON** (the 27B engine silently
+ignored its encoder — frank-zealot owned images for exactly one day at this
+endpoint).
 
-Fetch: `scripts/download-frank-large-halogen.sh` into
-`/home/dank/models/halogen-qwen3.8-27b/` (`-f` + byte count + LFS sha256 +
-`--verify-only`, no token on the command line; resume goes against the
-RESOLVED CDN URL because curl drops `Range` across HF's 302). The deployer
-and serve script both refuse a missing tokenizer file or **any symlink** —
-an HF cache snapshot symlinks each entry into `blobs/` and those links
-dangle inside the container mount.
+**Engine laws that shape the config** (all in `scripts/frank-dragoon.env`
+with evidence): `HALOGEN_SPEC_ADAPT=0` is MANDATORY — the default adaptive
+policy disables the MTP head for whole requests after low acceptance and
+HALVES decode; the head stays on and temp-1.0 traffic pays some acceptance
+for it (accepted). `HALOGEN_CTX=262144` is the PER-SLOT hard ceiling (400
+naming the limit, never truncation) — RAISED from 200192 on 2026-10-07
+under the 400-zone law: the harness clamps max_tokens to
+`min(45056, contextWindow − est − 4096)`, its chars/4 est UNDER-counts
+the rendered prompt by ~3 % (measured: est 152,938 → server 157,388,
+request 43,158 vs room 42,804), so a harness window == engine ceiling
+made every request over ~146k est a guaranteed 400. `models.yml`
+`contextWindow: 217088` leaves the 45k gap that absorbs the estimate
+error (worst-case request ≈ 219k ≤ 262144); compaction fires at 85 % of
+the harness window = 184,524 est ≈ 190k measured (Frank's 180k target).
+`HALOGEN_KV_SLOTS=2` is LEGAL here — the 27B "slots>1 disables the drafter"
+law does NOT carry over; batching and speculation coexist (the card's
+quickstart ships 2 slots with the head), so 2 is concurrent capacity.
+`HALOGEN_KV_POOL_POSITIONS=524288` (explicit 2 × ctx; ~28 KiB/position ⇒
+14.0 GiB). `HALOGEN_MAX_TOK=8192` is only the per-request DEFAULT (the
+harness sends at most its `maxTokens` 45056); `HALOGEN_MAX_TOKENS_CAP=65536` +
+`HALOGEN_QUEUE_TIMEOUT=7200` are a coupled pair (FLAGS.md table).
+**A server-side sampler EXISTS** (`HALOGEN_TEMPERATURE/TOP_P/TOP_K` =
+1.0/0.95/20, the card's thinking recipe) — an absent temperature is no
+longer greedy; `models.yml` extraBody carries the same values, consistent
+not load-bearing. Prompt cache is ON by default (`PROMPT_CACHE=2`): a warm
+100k follow-up costs ~2 s vs ~88 s cold — the 27B engine's manual
+`HALOGEN_CACHE_MB` pin era is over. `response_format` is unsupported.
+Thinking lands in **`reasoning_content`**; the v2 chat template rejects
+`reasoning_effort` outside `xhigh|medium|low`, so the `models.yml` fold
+stays mandatory. Thinking tokens COUNT against the budget (empty content +
+`finish_reason: "length"` when exhausted mid-thought). Vision: OpenAI
+`image_url` content parts only; ≥256 px probe images or the model answers
+"video".
 
-Runbook: `serverAppConfigs-docs/LLM/frank-large-halogen27b-dflash2.md`.
-Rollback: revert the swap commit and redeploy — the ROCmFPX payload
-(`/home/dank/models/kingjones-Qwen3.8-27B-ROCmFP4-STRIX-MTP/`), the fork build
-and `scripts/build-rocmfpx.sh` (pin `36e9acd`) all remain on disk, seam-tested.
-The older gufo tag `frank-large-gufo-q4kxl-20261001` stays a **re-download**
-rollback (payloads removed 2026-10-03; `scripts/build-gufo.sh` stays).
+**Memory ledger** (121.2 GiB unified; the referee is the boot ledger):
+weights ~62 + KV 14.0 + arena ~8 (`3.8 + 8.4 × MAX_TOK/16384`) + vision
+~2 ≈ 86 GiB engine-side + `HALOGEN_HOST_RESERVE_GIB=20` → ~15 GiB
+margin over baseline co-tenancy. The 51.2 GB n-gram table rides as mmap'd
+page cache beside the checkpoint — the card's quickstart arithmetic does
+not bill it as resident, but READ the boot ledger and re-size if the
+engine prints a clamp.
 
-### frank-small — llama.cpp on the RTX 3090 (Dankclaw, ACTIVE)
+Fetch: `scripts/download-frank-dragoon-flashnext.sh` into
+`/home/dank/models/halogen-flashnext-v2/` (`-f` + exact byte counts + LFS
+sha256 + `--verify-only`, no token on the command line; resume goes
+against the RESOLVED CDN URL because curl drops `Range` across HF's 302).
+The serve gates mirror the deployer EXACTLY (byte-exact checkpoint +
+n-gram + vision tower, flat tokenizer with all six files as regular
+files) — the 2026-10-01 crash-loop lesson.
 
-**llama.cpp master** (CUDA sm_86 build
-`/home/dank/GitPackages/llama-master/build-cuda/bin/llama-server`) as a
-**root systemd unit** (`scripts/frank-small.service`, `relink_unit`ed into
+Runbook:
+`serverAppConfigs-docs/LLM/frank-dragoon-flash-server-v2-swift15.md`.
+Rollback: revert the swap commit and redeploy — the 27B payload
+(`/home/dank/models/halogen-qwen3.8-27b/`), its fetch script and the
+halogen 0.1.4 image digest all remain on disk; the ROCmFPX door behind
+that (`scripts/build-rocmfpx.sh`, pin `36e9acd`) is untouched.
+
+### frank-zealot — llama.cpp on the RTX 3090 (Dankclaw, ACTIVE)
+
+**llama.cpp master** (0.5.0-dev, commit `5fc4f3c`; CUDA sm_86 build
+`/home/dank/GitPackages/llama-master/build-cuda/bin/llama-server`,
+`GGML_CUDA_FA_ALL_QUANTS=ON`) as a **root systemd unit**
+(`scripts/frank-zealot.service`, `relink_unit`ed into
 `/etc/systemd/system/`), serving
-`bartowski/MiMo-V2.6-Distill-Qwen-9B-GGUF` at **Q6_K** (7,793,710,624 B,
-sha256 `ef96d05a…`) **plus `mmproj-MiMo-V2.6-Distill-Qwen-9B-f16.gguf`**
-(918,166,048 B, sha256 `ff348f…`), both `/home/dank/models/MiMo-Q6K/` (the
-projector is a hardlink of the Q5KM copy — the dir is self-contained), on
-port 7771. The rung went Q5_K_M → Q6_K on 2026-10-03 the same morning as the
-reslice, funded by the freed slots. The runtime arrived 2026-10-01 night for
-one reason:
-**asymmetric KV** — `--cache-type-k f16` + `--cache-type-v q8_0` is the fleet's
-only per-tensor KV lever, and SGLang's `--kv-cache-dtype` moves K and V
-together. On 2026-10-03 Frank spent the headroom that lever bought: the reslice
-from three slots to two made room for **fully unquantized V**
-(`CACHE_TYPE_V=f16`); both flags stay explicit in the serve script. Vision came
-2026-10-02 via `--mmproj`: the GGUF carries no `v.*` tensors, so the projector
-file is the entire vision path (and ~1.4 GiB of the card).
+`HauhauCS/Qwen3.5-9B-Uncensored-HauhauCS-Aggressive` at **Q6_K**
+(7,359,259,008 B, sha256 `c0ba7beb…` computed locally — the Hub carries no
+LFS oid) **plus the publisher's own BF16 mmproj** (921,704,448 B), both
+`/home/dank/models/Qwen35-9B-HauhauCS-Q6K/`, on port 7771. Cutover
+2026-10-07 (late) from the Gemma4-26B-A4B Q4_K_M 1×200,704 shape (same day).
 
-**Architecture: qwen3_5 hybrid** — 32 layers, 8 full-attention + 24 Gated
-DeltaNet, native 262,144 window. KV exists only in the 8 attention layers
-(4 KV heads × 256 dim × 2 B ≈ 2 KiB/token/layer, ~16 KiB/token for f16 K+V);
-the DeltaNet state is a fixed per-slot buffer, so slot count — not context —
-drives that term.
+**Architecture: qwen35 dense hybrid** — read from the GGUF's own header, not
+the model card: 32 layers, `full_attention_interval = 4` ⇒ **8 full-attention
+layers (3, 7, 11, …, 31) + 24 Gated DeltaNet linear layers**, 16 attention
+heads / **4 KV heads** × 256 dim, `ssm` conv_kernel 4 / state_size 128 /
+group_count 16 / time_step_rank 32 / inner_size 4096, native 262,144, vocab
+248,320. Tensor types are Q6_K × 250 + F32 × 177 — standard quants only, so
+the stock master build loads it (arch `qwen35` is registered in this build's
+`src/llama-arch.cpp`). **KV accounting:** the pool scales with the 8 full
+layers only — 8 × 4 × 256 = 8,192 elements/token per cache, so f16 K + f16 V
+bills **32 KiB/token** = 12.25 GiB at the 401,408 pool; the 24 DeltaNet
+layers bill a fixed recurrent state per SLOT, not per token, which is exactly
+why two 200k slots fit where the 26B MoE fit one.
 
-**The shape (2026-10-03):** `--ctx-size 401408 --parallel 2` = **TWO
-conversations of 200,704 tokens each** (llama.cpp divides the pool:
-`n_ctx_slot = CTX_SIZE / PARALLEL`), `--flash-attn on` (the seam pins it),
-**f16 K + f16 V**, all layers on the GPU, `--mmproj` for vision, and since
-2026-10-05 **batch 4096 / ubatch 2048** (doubled; the boot-pair A/B is in the
-runbook). Measured trade at 8,928 prompt tokens: prefill 4,024 → **4,209 t/s,
-+4.6 %**, decode flat (91.9–93.0 vs 93.8–94.3 — noise), and a 279-token prompt,
-which sits below either ubatch, did not move at all. The old "ubatch 2048
-failed the scratch boot" note belongs to the Q5_K_M predecessor and does NOT
-generalize: this shape boots 2048 clean. Measured VRAM **21,846 used / 2,279
-free** of 24,576 MiB against **21,276 / 2,849** for the 1024 arm, reproduced
-byte-identically the same hour — the doubling costs **616 MiB** and lands at
-the BOTTOM of the 2–3 GiB floor Frank asked for (`4096/1536` is the middle rung
-if that margin is ever wanted; non-KV 9,302 MiB, up from 8,732 by exactly the
-compute buffers; f16 K+V is 32 KiB/token across the 8 attention layers;
-quote `nvidia-smi`'s `free` field, never `total − used` — the driver holds
-~450 MiB of reserve the subtraction hides). The 2026-10-02 3 × 180,224 +
-q8_0-V shape stays one env edit away (`CTX_SIZE=540672 PARALLEL=3
-CACHE_TYPE_V=q8_0`, and it must pair with Q5_K_M — Q6_K breaks the floor
-there). Three native windows need 18.4 GiB of KV alone and were never on the
-table.
+**The shape (2026-10-07):** `--ctx-size 401408 --parallel 2` = TWO
+conversations of 200,704 (Frank's cap; the harness `contextWindow` quotes
+the per-slot number), `--flash-attn on`, **f16 K + f16 V** (exact KV),
+batch 4096 / **ubatch 2048** (the measured CUDA optimum: +4.6 % prefill,
+decode flat, 616 MiB — MiMo-era A/B on this card), `--log-verbosity 4`,
+`--mmproj` for vision, **speculative decoding OFF** (`SPEC_TYPE=none`).
 
-Verified at deploy (2026-10-03): boot logs `n_slots = 2, n_ctx_slot = 200704`
-and `loaded multimodal model`; decode **94.44 tok/s** at temp 0 on the probe
-that measured 104.84 on Q5_K_M — **the Q6_K rung costs a measured −10 %**:
-decode on this card is weight-bandwidth-bound and Q6_K streams ~10 % more
-bytes/token; health 200, e2e 33/33; native `tool_calls`; thinking in
-`reasoning_content`; a **512×512** solid-red PNG answers `Red` through an
-`image_url` content part (two traps: the legacy top-level `images` field is
-ignored, and a TINY probe image undersupplies image tokens — a 10×10 PNG made
-the model claim "it's a video"; probe with ≥256 px). A prompt over the slot
-is a **400 `exceed_context_size_error`**, which is why `models.yml` sets
-`contextWindow: 200704`.
+**Why MTP is off**: it is not a choice — **this Q6_K file carries no
+`nextn`/`mtp` tensors** (verified from the tensor-name list), and MTP is a
+property of the file, not of the flags. The publisher card advertises "MTP
+support" for the base architecture; the quantized export dropped the head.
 
-Runbook: `serverAppConfigs-docs/LLM/frank-small-llama-mimo-q6k-2x200704.md`
-(the boot-pair table that prices pool changes lives in the retired
-[[frank-small-llama-mimo-q5km]]).
-Rollback: `MODEL_FILE=/home/dank/models/MiMo-Q5KM/MiMo-V2.6-Distill-Qwen-9B-Q5_K_M.gguf`
-buys back 875 MiB and the −10 % decode rate (3,571 free, 104.84 tok/s, both
-measured); the older shape `CTX_SIZE=540672 PARALLEL=3 CACHE_TYPE_V=q8_0`
-pairs with Q5 only; SGLang rollback in
-[[frank-small-sglang-mimo-v26]] (venv on disk at
-`/home/dank/GitPackages/sglang-cu128/`, INT8 payload staged to
-`~dank/.AGENTTRASH/20261002-retired-llm-payloads/`).
+**Measured boots** (nvidia-smi, the referee): the deployed boot is
+**21,436 used / 2,689 free** (ubatch 2048) — the pricing boots were the
+MiMo-V2.6-Distill-Qwen-9B pair at this exact geometry (**21,276 / 2,849** at
+ubatch 1024, **21,846 / 2,279** at 2048), so the 415 MiB lighter weights
+bought back what the projection predicted. The engine ledger confirms the KV
+law to the MiB: `CUDA0 KV buffer size = 12544.00 MiB` (`K (f16): 6272.00`,
+`V (f16): 6272.00`), compute buffers 1,136 MiB on CUDA0 + 848 MiB host, the
+mmproj 879 MiB + 248 MiB. Decode is ubatch-invariant (Swift-era 3090 law). The
+Q6_K rung costs ~10 % decode vs Q5_K_M (weight bandwidth; MiMo-measured 94.4
+vs 104.8 t/s).
 
-### frank-primary — FreeToken (PR #587 ROCm), Qwen3.8-Flash-Next FP8 (Dankserver, ACTIVE)
+**Vision**: the publisher's own BF16 mmproj via `--mmproj` (the model is
+natively multimodal; the Q6_K file carries no vision tensors). Probe traps
+carry over: ≥256 px probe images or the model answers "video", and only the
+OpenAI `image_url` content part reaches the model.
 
-The **FreeToken engine at PR #587 head `77a7201`** (branch
-`rocm714_torch214`, built on the host into the local image
-`localhost/frank-primary-freetoken:pr587-77a7201` by
-`scripts/docker/frank-primary-freetoken.Dockerfile` — the PR's own
-docs/install_amd.md stack: digest-pinned
-`rocm/pytorch:rocm7.14_ubuntu24.04_py3.12_pytorch_release_2.11.0` base =
-torch 2.11.0+rocm7.14/triton 3.7, `--no-build-isolation --no-deps -e .`,
-curated portable deps, `flashlib==0.3.0 --no-deps`, and a `libhiprtc.so`
-dev-symlink the pip-ROCm wheel lacks) serving
-**`orcarouter/Qwen3.8-Flash-Next-Uncensored-FP8`** (~172.8 GiB, 131 shards,
-standard modelopt block-FP8 — 75,264 `weight_scale_inv` tensors, no
-`input_scale`, loaded directly from HF safetensors, no FTW conversion) on
-**ONE R9700 (gfx1201)** — the second card sits idle. Plain `podman run`
-through `scripts/serve-frank-primary.sh` under the root systemd unit
-(`frank-primary.service`, `User=dank`, `LimitMEMLOCK=infinity`); the
-container name is the unit name (`frank-primary`; the vLLM-era
-`frank-primary-qwen` is in the legacy cleanup list). Cutover 2026-10-05;
-rollback tag `frank-primary-vllm-shapeG-20261003` (the tcclaviger vLLM trio
-and its 362-line env lore live in that tag; the tcclaviger image stays in
-dank's rootless storage).
+**Compaction hub**: `models.yml` routes `compactionModel` for
+`frank-archon`, `frank-dragoon` and `frank-zealot` (the 3090 endpoint) here — 200,704 is the
+only window in the fleet that fits a worst-case compaction input (~170k
+tokens). With `--parallel 2` a compaction request no longer serializes behind
+a live generation (the Gemma4 era's `--parallel 1` law).
 
-**Shape**: all expert weights in **pinned host RAM** (~120 GiB) behind a
-GPU LRU (`--moe-cache-rate 0.10`, ~12 GiB — the single-card ceiling given
-the KV contract), the ~47.7 GiB PLE ngram table pinned in host RAM
-(→ root unit + memlock law), **KV pool `--num-tokens 299968`**
-(24 KiB/token f16 across the 12 full-attention layers ≈ 7.0 GiB; **must be
-a multiple of 64** — the auto attention backend is `qsa_sparse`, which
-overrides page size to 64; 300,000 was refused at first boot), 2 decode
-slots, `--max-output-tokens 36864` (the harness maxTokens; requests that
-omit one get this default). **Parsers are AUTO**: thinking lands in
-`reasoning_content` natively, tool calls in the qwen3.8 dialect — models.yml
-flips `reasoningContentField` to `reasoning_content` on the harness side.
-Vision works (models.yml keeps `input: [text, image]`); the vision tower's
-blocks stream from host RAM two at a time by default.
+Runbook:
+`serverAppConfigs-docs/LLM/frank-zealot-llama-qwen35-9b-q6k-2x200704.md`.
+Rollback: revert the swap commit — the Gemma4 payload
+(`/home/dank/models/Gemma4-26B-A4B/`), the MiMo Q6_K payload
+(`/home/dank/models/MiMo-Q6K/`), the Swift payload
+(`/home/dank/models/Swift15-UncIQ3XXS/`) and the Ornith Q8_0 payload
+(`/home/dank/models/Ornith-Q8/`) all remain on disk.
 
-**Measured at cutover**: boot ~2.3 min cold-ish / 92 s warm → /health
-status ok; decode **17.1 tok/s** single-stream temp 0 (the vLLM incumbent
-measured ~30 tok/s on TWO cards; the KV contract caps the single-card LRU,
-and **TP=2 exists but does not boot on ROCm** — the TP allreduce JIT
-(`pynccl.cu`) can't resolve `cuda_runtime.h` for gfx1201; probed
-2026-10-06, signature in the runbook). `/metrics` is a 404 — the Dankclaw
-Prometheus llm-fleet scrape of :7770 reads down until repointed.
-`ft ctl cache --kv/--moe` resizes pools live (grow only; shrink needs a
-restart); `ft ctl stats` reports occupancy.
 
-**Deploy gate law (changed for FreeToken)**: `/health` returns **200 with
-`{"status":"loading"}`** while the engine loads — the FastAPI front end
-binds before the scheduler is up, so a bare `curl` false-greens (measured:
-"healthy after 6 s" mid-page-in). The deployer loops until the body says
-`"status":"ok"`; the MainPID stray-port guard is unchanged. The image gate
-is `podman image exists` (a local build carries no RepoDigests — the old
-digest grep refused exactly this shape; pinning lives in the Dockerfile).
+### frank-archon — Radiance (StillDeadcode), Swift1.5-Qwen3.8-Flash-Next GPTQ w4, TP=2 (Dankserver, ACTIVE)
 
-Runbook: `serverAppConfigs-docs/LLM/frank-primary-freetoken-pr587.md`.
+The **radiance engine** (StillDeadcode, Apache-2.0; image
+`stilldeadcode/radiance@sha256:4c3f484564…` digest-pinned, **pin 1.0.13**
+for serve/convert/KLD; `libr4d` gfx1201 kernels, plain `podman run`, root
+systemd unit, container name = unit name) serving
+**ukisai/Swift1.5-Qwen3.8-Flash-Next (BF16, 335.3 GiB, 131 shards,
+397/397 sha256-verified)** converted by `scripts/convert-swift15-w4dn8.sh`
+with recipe `scripts/recipes/qwen4exp-swift15-w4dn8-i8-hc8m.recipe` to
+`qwen4exp-swift15-w4dn8-i8-hc8m.rad` (~114 GiB): **all 49,152 experts GPTQ
+w4** (act-order, damp 0.05, 10,000,000-token calibration captured on engine
+**1.2.0** via `RADIANCE_CALIB_DIR`/`RADIANCE_CALIB_TOKENS` — the only pin
+with the token knob; the RADGRAM2 grams are format-identical across pins and
+cross the boundary by design), **24 whole experts per layer cast bf16** (the
+PROTECTED set, derived from the calibration grams' energy share),
+**int8 trunk/lm_head**, **fp8 HC mixtures** (`--hc-mix-dtype`), PLE n-gram
+table at fp8 fixed scale (47.7 GiB in the container, from 95.4 GiB bf16).
+The plugin's **one-table-one-encoding law** (measured at rad-convert
+declare): one expert table takes ONE encoding; only whole bf16 experts are
+legal beside it — no w4/fp8 split of the down/gate_up pair (24-value
+`rad_arch_quant_desc` array, one per layer). KLD gate vs the BF16
+reference (recorded on the same 1.0.13 pin) is the precision referee;
+the throughput gate (decode ≥ 30.8 t/s) was passed at 4.5× the bar
+(122–173 t/s at 44.5k depth). Measured decode/prefill in the runbook.
+Rollback: revert the swap commit — the fp8-native `.rad`
+(`qwen4exp-fp8-native.rad`) and every prior payload remain on disk.
+
+**Shape (both R9700s, TP=2)**: `--tp-wire wht6`, `--max-num-seqs 3`,
+`--max-model-len 200000` (the harness contextWindow must quote this),
+`--placement expert_tiered --host-pool-mib 44928` + **explicit VRAM
+partition `--vram-weights-mib 25600 --vram-kv-mib 5120`** (the vram-pair
+replaced `--expert-vs-cache-ratio`; the two are ONE budget —
+`weights + kv ≤ 30,969 MiB`, derived from the engine's own budget table: card
+32,624 MiB, the pair at 29,120 settling 2,058 MiB free against the engine's
+209.19 MiB floor (`--gpu-headroom-mib 96` + 113.19 static), so 1,849 MiB is
+claimable and the old 29,120 bound was my hand-picked 1 GiB reserve, not a
+hardware wall), `--kv-cache-dtype` **`fp8` — quantized KV, restored 2026-10-13
+because it is the only dtype that funds the slot count at this window**,
+`--num-speculative-tokens 2`, `--max-num-batched-tokens 2048`, prefix cache
+8 GiB pinned host + 64 GiB disk at `/home/dank/radiance-state`,
+**`--ngram-placement ram`**, Froggeric v22.5 chat template vendored
+(`scripts/qwen38-froggeric-v22.5.jinja`, `--override-chat-template`). Boot
+ledger (2026-10-13, pair 25600/5120): `kv cache 5.00 GiB … backs 3 sequences
+all at 200000 tokens at once, which is the worst case` — `kv_attn` page
+26.00 KiB (fp8) at 607,740 tokens (the sizing law predicted 608,027),
+`kv_qsa_bkey` 3.25 KiB at the same token count, `kv_gdn_state` 54 MiB × 6 slots
+(3 sequences × 2 copies) = 324 MiB; the sampler prints **9 rows**
+(3 × (1+2), inside the 25-row `wht6` exactness bound); the slab filled to
+563 KiB of slack with **17,548 slots** (16,235 at 24,000, 14,753 at 22,208 —
+every 1,792 MiB buys ~1,300 resident experts, and the pinned host pool hands
+the same experts back: 8,893 → 7,580 slots); `unclaimed 477.30 MiB`, cards
+settled ~336 MiB free against the engine's 209.19 MiB floor, KV lending
+4.22 GiB to the expert cache. Prefill tracks this slab only up to a
+**threshold**: 22,208 → 3,397 and 24,000 → 3,290 t/s at 43.5k are one band
+(±3 %), and the 25,600 arm measured **3,290** — the third step bought nothing
+(the 3,584 arm did not reproduce at 3 slots); the cliff is at ~26 GiB
+(26,071 → 4,379 on 2026-10-11's arm), so below that the slab is a threshold,
+not a slope.
+
+**Decode ladder (2026-10-13, 512 tokens, greedy, this shape)**: 99.0 t/s
+single-stream at 43.5k, 93.3 at 197k — decode is nearly window-free (−6 % for
+4.5× depth); **3 concurrent streams give 113.9/43.3/10.9 t/s = 18.4 t/s
+aggregate**, so the slot count is paid in decode concurrency (a fused-step
+lottery), not in prefill; leg D of `probe-frank-archon-kv.py` measures it.
+
+Shape notes carried from the fp8-native era and unchanged: wht6 gains,
+MNDT 2048 law (2560 collapses decode to 2.6–7.7 t/s), the 64 GiB disk
+prefix cache, and the rule that a prompt over `--max-model-len` is
+refused, never truncated. What changed: the fp8-native era's NVMe expert
+streaming (the 3.5 GB/s wall) is gone — the w4 resident set fits the
+host pool, so decode ran 122–173 t/s in the campaign arms and ~190 t/s
+on the fp8 shape (512-token streamed probe). The campaign also
+measured the int8-KV + spec-3 arm (136.0 t/s median at 44.5k depth,
+accept 0.7246).
+
+**The KV dtype law (measured 2026-10-11, applied at 4 slots 2026-10-13)**:
+`--kv-cache-dtype` takes ONLY `bf16|fp8` — one dtype for the whole cache, so
+llama.cpp's exact-K/quantized-V pair (what frank-zealot runs) has NO radiance
+equivalent; the rung under bf16 is fp8 on both halves. Measured per rank from
+the two boot ledgers: `kv_attn` (13 layers, 4-token blocks) pages 26.00 → 52.00
+KiB, while `kv_qsa_bkey` (13 layers) stays 3.25 KiB at BOTH dtypes (the QSA
+block key is an index, not attention state) — so a token costs 7.3125 KiB at fp8
+and 13.8125 KiB at bf16: **1.89×, not 2×**. Pool sizing must also pay the
+dtype-independent terms that live in the same pool (~110 MiB a sequence of
+recurrent state + 448 MiB of prefix checkpoints):
+`(vram_kv − 110·seqs − 448) MiB / rate` — bf16 at 6,912 gives 462,946 where the
+engine reported 462,752 (0.04 % page rounding); fp8 at 6,912 with four slots
+gives 843,566, i.e. the deployed capacity contract 4 × 200,000. **That is why
+the dtype is fp8: the pool must back `seqs × max-model-len` as a hard limit, and
+bf16 at four slots costs 11,679 MiB — the slab would fall to 17,441 MiB (−33 %),
+where fp8 leaves it at 22,208.** The cost is paid twice on this engine, and
+half-refunded: idle KV VRAM is also the expert cache's spillover, and the bigger
+pool *lends* 6.08 GiB to the slab where the 3,543 MiB fp8 pool lent 2.69 GiB.
+`--max-num-seqs` rides 4 × (1 + spec) = 12 fused-all-reduce rows, under the
+25-row bound where wht6 is bit-exact (the "seqs 2 cannot boot" law belongs to
+the retired tcclaviger fork's torch.compile, not radiance). Disk-tier sizing
+law: the engine forces ~9.6 GiB of disk-tier weight buffers + arena onto the
+weights side, so `weights + kv` is capped near 29.6 GiB/card; boot with the
+pair, never `--kv-cache-size-mib`.
+
+Shape notes carried from the fp8-native era and unchanged: wht6 gains,
+MNDT 2048 law (2560 collapses decode to 2.6–7.7 t/s), the 64 GiB disk
+prefix cache, and the rule that a prompt over `--max-model-len` is
+refused, never truncated. What changed: the fp8-native era's NVMe expert
+streaming (the 3.5 GB/s wall) is gone — the w4 resident set fits the
+host pool, so decode ran 122–173 t/s in the campaign arms and ~190 t/s
+on the fp8 shape (512-token streamed probe). The campaign also
+measured the int8-KV + spec-3 arm (136.0 t/s median at 44.5k depth,
+accept 0.7246).
+
+**The pinned-RAM ledger is why this is a root unit**: 2 × 44 GiB expert
+pools + the 47.7 GiB n-gram copy (`--ngram-placement ram` is pinned RAM
+the card reads) + 8 GiB prefix host ≈ **147 GiB** charged against
+`RLIMIT_MEMLOCK` — the TTM floor is set just above it.
+`ttm.pages_limit`/`pages_max` cap GPU-mappable pinned pages, and **the knob is
+runtime state whose default is half of RAM**: `scripts/ttm-preflight.sh` (sourced
+by the serve script) therefore RAISES it to `FRANK_ARCHON_TTM_TARGET_MIB=204800`
+before refusing, because the 2026-10-12 power failure reset it to 125,988 MiB
+and the preflight re-refused 6,919 times. A manual sysfs write in the stop
+window is a convenience, not the repair; kernel cmdline persistence
+(`ttm.pages_limit=52428800`) is the belt to it.
+
+**Contract facts** (source-verified): the HTTP listener binds AFTER the
+full load, so a bare `curl /health` gate is honest (`/health` == `/ping`,
+200 serving / 503 stopping); sampling params temperature…preserve_thinking
+accepted, **unknown params 400** (models.yml's extraBody set is fully
+inside it); `response_format` supported; `logprobs` REFUSED; reasoning in
+`reasoning_content` and tool calls in the qwen3.8 dialect via the auto
+chat format — no parser flags; vision native (the 27-layer Qwen-VL tower,
+`--mm-max-patches`); `/metrics` carries vLLM-compatible names +
+`radiance:*` families — the Dankclaw Prometheus scrape is re-added.
+
+Runbook: `serverAppConfigs-docs/LLM/frank-archon-radiance-swift15-w4dn8.md`.
+Retired fp8-native era: `serverAppConfigs-docs/LLM/frank-archon-radiance-qwen38-native-fp8.md`.
+Retired FreeToken era: `serverAppConfigs-docs/LLM/frank-archon-freetoken-pr587.md`.
 Retired vLLM era: `serverAppConfigs-docs/LLM/dankserver-qwen38-fp8-expert-offload-tuning.md`.
-Retired GLM experiment: `serverAppConfigs-docs/LLM/frank-primary-glm53-flash-w4a16.md`.
+Retired GLM experiment: `serverAppConfigs-docs/LLM/frank-archon-glm53-flash-w4a16.md`.
 
 ## Key Lessons Learned
 Durable operational lessons from the fleet's history. Full detail in the
@@ -667,11 +803,22 @@ linked runbooks.
 - Swap resize ordering: create and `swapon` the replacement BEFORE `swapoff`
   of the old one, or live pages must land in RAM that `MemAvailable`
   overstates. Dankclaw swap (64 GiB at `/swap.img`, fstab-driven) protects
-  the co-tenants, not frank-large — pinned weights don't swap, and paging
+  the co-tenants, not frank-dragoon — pinned weights don't swap, and paging
   the KV pool is worse than the OOM it prevents.
 - Host swap state is invisible to `deploy.sh` (no repo file) — check
   `swapon --show` before reasoning about headroom.
-- **Silent RAM corruption outranks every software theory.** frank-primary's
+- **A sysfs raise is a countdown to the next reboot.** `ttm.pages_limit` defaults
+  to half of RAM, so the manual raise to 200 GiB (2026-10-05) vanished with the
+  2026-10-12 23:17 POWER FAILURE on dankserver: the cap fell to 125,988 MiB,
+  frank-archon's pinned-ledger preflight (floor 150,000 MiB) refused the start,
+  and `Restart=always` re-ran that refusal **6,919 times in ~20 h** — a unit in
+  `activating (auto-restart)` that exits 1 in 50 ms with no container and no
+  engine log is a PREFLIGHT refusal, not an engine fault. Repo law now:
+  `scripts/ttm-preflight.sh` (sourced by `serve-frank-archon.sh`) raises the knob
+  to `FRANK_ARCHON_TTM_TARGET_MIB` itself, re-reads, and refuses by name only
+  after a write the kernel rejected. Never prescribe a manual sysfs write as the
+  recovery procedure for a service that can boot before a human reaches it.
+- **Silent RAM corruption outranks every software theory.** frank-archon's
   ~40k-token output corruption (2026-10-04/05, repetition/garbage in long
   agent conversations) was marginal DDR5 at 4800 MT/s on four DIMMs, fixed
   by 4600. Consumer non-ECC memory raises **no MCE** for a silent flip, and
@@ -694,7 +841,7 @@ linked runbooks.
   `LimitMEMLOCK=infinity` (systemd is privileged; the value flows through
   podman to runc without any raise). Upstream halogen's own run lines pass
   NO `--ulimit` at all — copy vendor run lines before adding flags
-  (measured 2026-10-05 on the frank-large cutover).
+  (measured 2026-10-05 on the frank-dragoon cutover).
 - **Kairic Edge** (if ever re-deployed): the pinned CK commit needs
   `third_party/composable_kernel/include/ck/config.h` generated manually
   (untracked; `git clean` removes it), and its greedy-argmax fastpath rejects
@@ -720,7 +867,7 @@ linked runbooks.
   121 GiB box, pushed `available` to 3 GiB, and every later rate was suspect.
   Record the child pid and kill it in a `finally`, then prove `free` came back
   before believing a number. Kill by pid — never `pkill -f llama-server`,
-  which also hits frank-small.
+  which also hits frank-zealot.
 
 **llama.cpp serving**
 
@@ -744,7 +891,7 @@ linked runbooks.
   builds its context against whatever model the draft context holds. Two
   context-backed types cannot share one process, and MTP's head only loads
   when MTP **is** the draft model. **A LEGAL chain can still lose on a
-  recurrent model:** `draft-mtp,ngram-mod` on frank-large's qwen35 hybrid
+  recurrent model:** `draft-mtp,ngram-mod` on frank-dragoon's qwen35 hybrid
   measured −15 % prose / −7 % block-copy (2026-10-03) — adding the ngram layer
   logs `recurrent state rollback is not compatible with 'ngram-mod' -
   disabling rollback support`, and MTP verification depends on that rollback,
@@ -786,7 +933,7 @@ linked runbooks.
   free. That was a CONTIGUITY failure, not a total-bytes one, and no totals
   model — the sweep's or the seam's — can see it.)
 - **On the CUDA 3090 the same knob has NO interior optimum up to 2048, so
-  frank-small ships 4096/2048.** Measured 2026-10-05 by boot-pair A/B on the
+  frank-zealot ships 4096/2048.** Measured 2026-10-05 by boot-pair A/B on the
   live service: at 8,928 prompt tokens ubatch 1024 gives 3,972 / 4,077 t/s and
   ubatch 2048 gives 4,207 / 4,212 — **+4.6 %** — for **616 MiB** (free 2,849 →
   2,279). Decode did not move (91.9–93.0 vs 93.8–94.3, i.e. noise), and a
@@ -795,9 +942,9 @@ linked runbooks.
   than the ubatch cannot see it. The logical `--batch-size` was again free. And
   the predecessor's "ubatch 2048 failed the scratch boot" was a shape
   observation, not a law: the same file boots 2048 clean at 2 × 200,704. Bench
-  it by restarting the SERVICE through a transient `FRANK_SMALL_ENV_FILE`
+  it by restarting the SERVICE through a transient `FRANK_ZEALOT_ENV_FILE`
   drop-in, never a scratch port — one card holds one server. See
-  [[frank-small-llama-mimo-q6k-2x200704]].
+  [[frank-zealot-llama-mimo-q6k-2x200704]].
 - **One `-ts` step is one LAYER, and a hybrid stack's layers are not the same
   size.** qwen35 is 16 x (3 Gated DeltaNet + 1 Gated Attention), so a step is
   worth ~0.43 GiB on a DeltaNet boundary and ~1.43 GiB on a full-attention one
@@ -819,7 +966,7 @@ linked runbooks.
   CTX_SIZE / PARALLEL`, and llama.cpp refuses a prompt longer than the SLOT
   (`400 exceed_context_size_error: request (184001 tokens) exceeds the
   available context size (180224 tokens)`) even when the pool has room. So
-  frank-small's 2 → 3 reslice moved each conversation from the model's native
+  frank-zealot's 2 → 3 reslice moved each conversation from the model's native
   262,144 down to 180,224, and `models.yml` `contextWindow` had to follow or
   the harness would discover the ceiling as a 400 on a long conversation. Side
   effect worth knowing: the shorter slot made decode ~5 % FASTER (106.8 vs
@@ -830,9 +977,9 @@ linked runbooks.
   day the freed space also bought the Q6_K rung (now 94.4 tok/s — the rung
   itself is a further measured −10 %, weight-bandwidth, not slot geometry).
   All moves measured; both slot directions cost or buy window, never pool.
-  See [[frank-small-llama-mimo-q6k-2x200704]].
+  See [[frank-zealot-llama-mimo-q6k-2x200704]].
 - **Price a VRAM budget from two boots, never from a formula — and an mmproj
-  costs ~1.5x its file size.** The frank-small 3090 fit was solved from two
+  costs ~1.5x its file size.** The frank-zealot 3090 fit was solved from two
   measurements: 2 × 262,144 with no projector = 20,190 MiB used (KV 12,800 ⇒
   **non-KV 7,390**), 3 × 196,608 with the f16 projector = 22,972 used (KV
   14,113 ⇒ **non-KV 8,859**). The difference is the vision tower: a 918 MB file
@@ -840,24 +987,24 @@ linked runbooks.
   ride with it. Subtracting the two rows is exact; extrapolating weights+KV+
   "a bit for buffers" is what leaves 1.1 GiB free when you meant 2.7. Then
   solve `KV ≤ card − non-KV − headroom` and round to a multiple of
-  `PARALLEL × 4096`. Recorded in `scripts/frank-small.env` so the next resize
+  `PARALLEL × 4096`. Recorded in `scripts/frank-zealot.env` so the next resize
   starts from measurement.
 - **`images` and `image_url` are NOT interchangeable: only the content part
   reaches the model.** `--mmproj` loads, `usage.prompt_tokens` rises, and the
   model still invents an answer if the client used the legacy top-level
-  `images` field on `/v1/chat/completions` — frank-small answered "Brown." for
+  `images` field on `/v1/chat/completions` — frank-zealot answered "Brown." for
   a solid-red PNG that way and "Red." through the OpenAI `image_url` part. The
   failure is silent because a hallucinated color is a plausible answer. Probe
   vision with a solid color and expect an exact word.
 - **`--jinja` is what `tools` needs.** On 2026-09-16 a subagent died with
   `500 tools param requires --jinja flag`, from the ik_llama.cpp runtime that
-  then served frank-large: every tool-using agent on that endpoint was broken
+  then served frank-dragoon: every tool-using agent on that endpoint was broken
   and the failure read like a model fault. Mainline llama.cpp 0.4.1 defaults
   `--jinja` on and the serve script pins it; halogen also accepts `tools` and
   returns `tool_calls`. Check tool support before routing a role at an endpoint.
 - **Quantized KV on CUDA needs `GGML_CUDA_FA_ALL_QUANTS=ON`** — the same
   option and the same ~12x prefill collapse described in the ROCm note above.
-  f16 KV needs nothing; frank-small ran f16 for that reason until
+  f16 KV needs nothing; frank-zealot ran f16 for that reason until
   2026-09-17, when `build-cuda` was rebuilt with the option ON so the
   endpoint could take q8_0 KV.
 - **llama-bench separates a LIST with `/` and SWEEP values with `,`.** Both
@@ -875,7 +1022,7 @@ linked runbooks.
   raises on anything else — HTTP 500, not a clamp — so the harness's levels
   must be folded onto that set in `models.yml` (`compat.reasoningEffortMap`).
   A role whose level is unmapped fails on its FIRST request, and the failure
-  names Jinja, not the model: every subagent on `frank-small` died with
+  names Jinja, not the model: every subagent on `frank-zealot` died with
   `Unexpected reasoning effort high` until `high: xhigh` was added on
   2026-09-16. Halogen accepts the wider set, so the two entries legitimately
   differ.
@@ -895,7 +1042,7 @@ linked runbooks.
   times (`RuntimeError: No HIP GPUs are available`).
 - SearXNG outbound traffic must stay on the Gluetun tunnel; do not move its
   ports off the gluetun service.
-- `amd_iommu=off` on Dankclaw (bought 13–16 % prefill for frank-large,
+- `amd_iommu=off` on Dankclaw (bought 13–16 % prefill for frank-dragoon,
   2026-09-11) permanently retired the XDNA2 NPU: the driver's SVA/PASID bind
   needs an enabled IOMMU (`/dev/accel/accel0` fails `err=-19`). Revert path
   in `serverAppConfigs-docs/LLM/dankclaw-iommu-translation-off.md`.
@@ -949,9 +1096,9 @@ Active:
 
 | Service | Runbook |
 |---------|---------|
-| frank-large (halogen container, Qwen3.8-27B .hgn + DFlash2, 1×200,700, text-only, Dankclaw) | `serverAppConfigs-docs/LLM/frank-large-halogen27b-dflash2.md` |
-| frank-small (llama.cpp CUDA, MiMo-V2.6-Distill-Qwen-9B Q6_K, 2×200,704 f16 KV, Dankclaw) | `serverAppConfigs-docs/LLM/frank-small-llama-mimo-q6k-2x200704.md` |
-| frank-primary (FreeToken PR #587 ROCm, Qwen3.8-Flash-Next FP8, 1×R9700, Dankserver) | `serverAppConfigs-docs/LLM/frank-primary-freetoken-pr587.md` |
+| frank-dragoon (flash-server 0.16.2, abliterated Swift1.5 v2 .hgn + MTP always-on, 2×262,144, vision ON, Dankclaw) | `serverAppConfigs-docs/LLM/frank-dragoon-flash-server-v2-swift15.md` |
+| frank-zealot (llama.cpp CUDA, Qwen3.5-9B-Uncensored Q6_K, 2×200,704 exact f16 KV MTP-off, vision ON, Dankclaw) | `serverAppConfigs-docs/LLM/frank-zealot-llama-qwen35-9b-q6k-2x200704.md` |
+| frank-archon (radiance StillDeadcode, Qwen3.8-Flash-Next-FP8 native, 2×R9700 TP=2, Dankserver) | `serverAppConfigs-docs/LLM/frank-archon-radiance-qwen38-native-fp8.md` |
 | Dankclaw kernel posture (`amd_iommu=off`) | `serverAppConfigs-docs/LLM/dankclaw-iommu-translation-off.md` |
 | Deployment flow + incidents | `serverAppConfigs-docs/LLM/deployment.md` |
 
@@ -959,36 +1106,41 @@ Retired (rollback targets and history):
 
 | Runtime | Host | Window | Runbook |
 |---------|------|--------|---------|
-| ROCmFPX llama.cpp fork Qwen3.8-27B Uncensored Q6_0_ROCMFPX_AGENT + MTP (`frank-large`) | Dankclaw | 2026-10-03 → 10-05 (rollback target, payload + fork build on disk) | `frank-large-rocmfpx-q6agent-uncensored-mtp.md` |
-| tcclaviger vLLM fork Qwen3.8-Flash-Next-Uncensored FP8, TP=2, shape G (`frank-primary`) | Dankserver | 2026-09-29 → 10-05 (rollback target — tag `frank-primary-vllm-shapeG-20261003`; trio + env lore in the tag, image in rootless storage) | `dankserver-qwen38-fp8-expert-offload-tuning.md` |
-| ROCmFPX llama.cpp fork Qwen3.8-27B Q8_0_ROCMFPX_AGENT + MTP (`frank-large`) | Dankclaw | 2026-10-02 → 10-03 (rollback target, payload on disk) | `frank-large-rocmfpx-q8agent-mtp.md` |
-| gufo v0.1.1 Qwen3.8-27B UD-Q8_K_XL/UD-Q4_K_XL + DFlash2 (`frank-large`) | Dankclaw | 2026-09-28 → 10-01, again 10-01 → 10-02 (payloads removed from disk 2026-10-03; rollback = re-download) | `frank-large-gufo-qwen38-27b.md` |
-| vLLM TheRock MiMo-V2.6-Distill-Qwen-9B BF16 + cross-model MTP (`frank-large`) | Dankclaw | 2026-10-01 (same-day rollback to gufo) | `frank-large-vllm-mimo-v26-bf16.md` |
-| llama.cpp master MiMo-V2.6-Distill-Qwen-9B Q6_K (`frank-small`) | Dankclaw | 2026-10-01 → 10-02 (the rung returned ACTIVE 2026-10-03 at the 2×200,704 shape — `frank-small-llama-mimo-q6k-2x200704.md`) | `frank-small-llama-mimo-q6k.md` |
-| llama.cpp master MiMo-V2.6-Distill-Qwen-9B Q5_K_M 2×200,704 f16 KV (`frank-small`) | Dankclaw | 2026-10-02 → 10-03 (rollback target — one `MODEL_FILE` line, buys back 875 MiB + the −10 % rung tax; owns the boot-pair table) | `frank-small-llama-mimo-q5km.md` |
-| SGLang MiMo-V2.6 INT8-W8A16-AutoRound (`frank-small`) | Dankclaw | 2026-10-01 (same-day swap to the GGUF path) | `frank-small-sglang-mimo-v26.md` |
-|tcclaviger vLLM GLM-5.3-Flash W4A16 int4, +/- DFlash2 drafter (`frank-primary`)|Dankserver|2026-09-30 → 10-01|`frank-primary-glm53-flash-w4a16.md`|
-| llama.cpp b11030 Qwen3.8-27B UD-Q8_K_XL + DFlash2 (`frank-large`) | Dankclaw | 2026-09-21 → 09-28 | `frank-large-unsloth-qwen38-27b-q8xl.md` |
-| R9V radiance-vLLM Qwen3.8-Flash-Next-Uncensored IQ4_XS (`frank-primary`) | Dankserver | 2026-09-27 (same-day swap to Q8_0) | `frank-primary-r9v-radiance-qwen38-uncensored.md` |
-| llama.cpp b11030 Qwen3.8-Flash-Next Q8_0 + shared MTP (`frank-primary`) | Dankserver | 2026-09-26 → 09-27 | `frank-primary-llamacpp-qwen38-flash-next-q8.md` |
-| ik_llama.cpp Qwen3.8-Flash-Next-Uncensored i1-Q4_K_M (`frank-large`) | Dankclaw | 2026-09-15 → 09-16 | `frank-large-ik-uncensored.md` |
+| llama.cpp CUDA Gemma4-26B-A4B QAT Q4_K_M, 1×200,704 f16-K/q8_0-V MTP-off (`frank-zealot`) | Dankclaw | 2026-10-07 → 10-07 (same-day swap; rollback target — payload on disk; owns the `attention_k_eq_v` pair-billing KV law and the gemma4-assistant drafter-cost boots) | `frank-zealot-llama-gemma4-q4km-200704.md` |
+| ROCmFPX llama.cpp fork Qwen3.8-27B Uncensored Q6_0_ROCMFPX_AGENT + MTP (`frank-dragoon`) | Dankclaw | 2026-10-03 → 10-05 (rollback target, payload + fork build on disk) | `frank-dragoon-rocmfpx-q6agent-uncensored-mtp.md` |
+| tcclaviger vLLM fork Qwen3.8-Flash-Next-Uncensored FP8, TP=2, shape G (`frank-archon`) | Dankserver | 2026-09-29 → 10-05 (rollback target — tag `frank-archon-vllm-shapeG-20261003`; trio + env lore in the tag, image in rootless storage) | `dankserver-qwen38-fp8-expert-offload-tuning.md` |
+| FreeToken PR #587 ROCm, Qwen3.8-Flash-Next-Uncensored-FP8, ONE R9700 (`frank-archon`) | Dankserver | 2026-10-05 → 10-05 (rollback target — tag `frank-archon-freetoken-pr587-20261005`; trio + Dockerfile in the tag, image `localhost/frank-archon-freetoken:pr587-77a7201` and orcarouter payload on disk) | `frank-archon-freetoken-pr587.md` |
+| llama.cpp master MiMo-V2.6-Distill-Qwen-9B Q6_K 2×200,704 f16 KV (`frank-zealot`) | Dankclaw | 2026-10-03 → 10-05 (rollback target — payload on disk; owns the ubatch-2048 A/B; the Ornith swap of 10-05 was committed but never deployed, so this was the LIVE payload Swift replaced) | `frank-zealot-llama-mimo-q6k-2x200704.md` |
+| llama.cpp Ornith-1.5-9B Q8_0, ONE 262,144 f16 KV (`frank-zealot`) | Dankclaw | 2026-10-05 (committed 77decb5→380aafa, never deployed — superseded by Swift the same evening; payload on disk) | trail in `frank-zealot-llama-swift15-unc-iq3xxs-mtp-114688.md` |
+| llama.cpp CUDA Swift-1.5-27B Uncensored RCO IQ3_XXS-mtp, 2×114,688 draft-mtp q8_0 KV (`frank-zealot`) | Dankclaw | 2026-10-06 → 2026-10-07 (rollback target — payload on disk; owns the 3090 ubatch ladder A/B and the 34 KiB/token qwen35 KV law) | `frank-zealot-llama-swift15-unc-iq3xxs-mtp-114688.md` |
+| ROCmFPX llama.cpp fork Qwen3.8-27B Q8_0_ROCMFPX_AGENT + MTP (`frank-dragoon`) | Dankclaw | 2026-10-02 → 10-03 (rollback target, payload on disk) | `frank-dragoon-rocmfpx-q8agent-mtp.md` |
+| gufo v0.1.1 Qwen3.8-27B UD-Q8_K_XL/UD-Q4_K_XL + DFlash2 (`frank-dragoon`) | Dankclaw | 2026-09-28 → 10-01, again 10-01 → 10-02 (payloads removed from disk 2026-10-03; rollback = re-download) | `frank-dragoon-gufo-qwen38-27b.md` |
+| vLLM TheRock MiMo-V2.6-Distill-Qwen-9B BF16 + cross-model MTP (`frank-dragoon`) | Dankclaw | 2026-10-01 (same-day rollback to gufo) | `frank-dragoon-vllm-mimo-v26-bf16.md` |
+| llama.cpp master MiMo-V2.6-Distill-Qwen-9B Q6_K (`frank-zealot`) | Dankclaw | 2026-10-01 → 10-02 (the rung returned ACTIVE 2026-10-03 at the 2×200,704 shape — `frank-zealot-llama-mimo-q6k-2x200704.md`) | `frank-zealot-llama-mimo-q6k.md` |
+| llama.cpp master MiMo-V2.6-Distill-Qwen-9B Q5_K_M 2×200,704 f16 KV (`frank-zealot`) | Dankclaw | 2026-10-02 → 10-03 (rollback target — one `MODEL_FILE` line, buys back 875 MiB + the −10 % rung tax; owns the boot-pair table) | `frank-zealot-llama-mimo-q5km.md` |
+| SGLang MiMo-V2.6 INT8-W8A16-AutoRound (`frank-zealot`) | Dankclaw | 2026-10-01 (same-day swap to the GGUF path) | `frank-zealot-sglang-mimo-v26.md` |
+|tcclaviger vLLM GLM-5.3-Flash W4A16 int4, +/- DFlash2 drafter (`frank-archon`)|Dankserver|2026-09-30 → 10-01|`frank-archon-glm53-flash-w4a16.md`|
+| llama.cpp b11030 Qwen3.8-27B UD-Q8_K_XL + DFlash2 (`frank-dragoon`) | Dankclaw | 2026-09-21 → 09-28 | `frank-dragoon-unsloth-qwen38-27b-q8xl.md` |
+| R9V radiance-vLLM Qwen3.8-Flash-Next-Uncensored IQ4_XS (`frank-archon`) | Dankserver | 2026-09-27 (same-day swap to Q8_0) | `frank-archon-r9v-radiance-qwen38-uncensored.md` |
+| llama.cpp b11030 Qwen3.8-Flash-Next Q8_0 + shared MTP (`frank-archon`) | Dankserver | 2026-09-26 → 09-27 | `frank-archon-llamacpp-qwen38-flash-next-q8.md` |
+| ik_llama.cpp Qwen3.8-Flash-Next-Uncensored i1-Q4_K_M (`frank-dragoon`) | Dankclaw | 2026-09-15 → 09-16 | `frank-dragoon-ik-uncensored.md` |
 | vllm-radiance TP=2 MXFP4 + DFlash2 (`frank-medium`) | Dankserver | 2026-09-20 → 09-26 | `frank-medium-radiance-mxfp4.md` |
-| Lucebox DS4.1 DeepSeek-V4.1-Flash ROCmFP23 (`frank-primary`) | Dankserver | 2026-09-26 (same-day swap) | `frank-primary-lucebox-ds4.md` |
+| Lucebox DS4.1 DeepSeek-V4.1-Flash ROCmFP23 (`frank-archon`) | Dankserver | 2026-09-26 (same-day swap) | `frank-archon-lucebox-ds4.md` |
 | kingjones STRIX Qwen3.8-Flash-Next ROCmFP4 | Dankclaw | 2026-08-30 → 09-11 | `kingjones-strix-rocmfp4.md` |
-| halogen-flash-server Qwen3.8-Flash-Next w4b (`frank-large`) | Dankclaw | 2026-09-16 → 09-19 | `halogen-flash-server.md` |
-| CIRU v4.4.1 Orca Qwen3.8-Flash (`frank-large`) | Dankclaw | 2026-09-19 → 09-21 | `frank-large-ciru-orca.md` |
-| unsloth llama.cpp b11030 Qwen3.8-Flash-Next UD-IQ4_XS (`frank-large`) | Dankclaw | 2026-09-21 (same-day swap) | `frank-large-unsloth-qwen38-flash-next.md` |
-| Kairic Edge Qwen3.8-27B IU4 W4A4 (`frank-large`) | Dankclaw | 2026-09-21 (same-day swap) | `frank-large-kairic-edge-qwen38-27b.md` |
-| ISTA-DASLab Qwen3.8-27B-GSQ-RCO IQ3_S (`frank-small`) | Dankclaw | 2026-09-16 → 09-17 | `frank-small-qwen38-gsq-rco.md` |
-| vLLM Gemma4-12B w4a16 (`frank-small`) | Dankclaw | 2026-09-19 (same-day revert) | `frank-small-vllm-gemma4.md` |
-| llama.cpp Gemma4-12B QAT Q4_K_M (`frank-small`) | Dankclaw | 2026-09-17 → 10-01 | `frank-small-gemma4-12b.md` |
+| halogen-flash-server Qwen3.8-Flash-Next w4b (`frank-dragoon`) | Dankclaw | 2026-09-16 → 09-19 | `halogen-flash-server.md` |
+| CIRU v4.4.1 Orca Qwen3.8-Flash (`frank-dragoon`) | Dankclaw | 2026-09-19 → 09-21 | `frank-dragoon-ciru-orca.md` |
+| unsloth llama.cpp b11030 Qwen3.8-Flash-Next UD-IQ4_XS (`frank-dragoon`) | Dankclaw | 2026-09-21 (same-day swap) | `frank-dragoon-unsloth-qwen38-flash-next.md` |
+| Kairic Edge Qwen3.8-27B IU4 W4A4 (`frank-dragoon`) | Dankclaw | 2026-09-21 (same-day swap) | `frank-dragoon-kairic-edge-qwen38-27b.md` |
+| ISTA-DASLab Qwen3.8-27B-GSQ-RCO IQ3_S (`frank-zealot`) | Dankclaw | 2026-09-16 → 09-17 | `frank-zealot-qwen38-gsq-rco.md` |
+| vLLM Gemma4-12B w4a16 (`frank-zealot`) | Dankclaw | 2026-09-19 (same-day revert) | `frank-zealot-vllm-gemma4.md` |
+| llama.cpp Gemma4-12B QAT Q4_K_M (`frank-zealot`) | Dankclaw | 2026-09-17 → 10-01 | `frank-zealot-gemma4-12b.md` |
 | agentionai ROCmFP4-FAST imatrix | Dankclaw | 2026-08-29 → 08-30 | `agentionai-fast-imatrix.md` |
 | eemin Qwen3.8-27B ROCmI4 W4A4 MTP | Dankclaw | 2026-08-18 → 08-25 | `eemin-rocmi4-mtp.md` |
 | Kairic Edge IU4 | Dankclaw | 2026-08-22 (same-day revert) | `kairic-edge.md` |
 | CIRU ActiveFPX v3 / PromptForge | Dankclaw | through 2026-08-22 | `ciru-activefpx-promptforge.md` |
 | DFlash2 Vulkan | Dankclaw | 2026-08-21 (same-day revert) | `dflash2-large-vulkan.md` |
 | FastFlowLM NPU (`frank-npu`) | Dankclaw | twice, retired 2026-09-11 | `frank-npu.md`, `FastFlowLM NPU Inference.md` |
-| FreeToken (official + Huihui FP8, `frank-small`) | Dankserver | 2026-09-02 → 09-15 | `freetoken-frank-small.md` |
+| FreeToken (official + Huihui FP8, `frank-zealot`) | Dankserver | 2026-09-02 → 09-15 | `freetoken-frank-small.md` |
 | FastMTP patched llama.cpp | Dankserver | retired 2026-08-18 | `qwen3.8-spec-matrix.md` |
 | ik_llama.cpp Ornith CRACK | Dankserver | retired 2026-09-02 | `ikllama-ornith-dankserver.md` |
 | llama.cpp layer split + DFlash2 (`frank-medium`) | Dankserver | 2026-09-16 → 09-20 | `frank-medium-llamacpp-dflash2.md` |
@@ -1012,7 +1164,7 @@ history.
 | Unstaged local changes | **Commit or discard** — check `git status` before starting work; ask if unsure. |
 | Deploying a committed change | **`scripts/deploy.sh <target>`** — pushes, pulls ff-only, plans, dispatches, health-checks. |
 | Container without a Quadlet unit | **Give it one** — boot-persistent, self-healing `.container` via git. |
-| Benchmarking | **Stop and mask the service first**, bench, unmask, restart, verify health. |
+| Benchmarking | **Not part of a model swap** — swaps verify on the live service. A deliberate bench window: **stop and mask the service first**, bench, unmask, restart, verify health. |
 | Deleting a file | **Move it to trash** — `.AGENTTRASH/` (in-repo) or `~/.AGENTTRASH/YYYYMMDD-topic`. Never `rm`. |
 | Tests exist | **Run them** — verify tests pass after every change. Do not commit failing tests. |
 | Real secrets | **Never commit** — host `.env` files; `.env.example` holds placeholders only. |

README.md

@@ -13,7 +13,7 @@ one deploy script.
 | Host | User | IP | Podman stack | LLM service | LLM port |
 |------|------|----|--------------|-------------|----------|
 | dankserver | dank | 192.168.0.235 | media and library | frank-medium (ROCmFPX llama.cpp, Qwen3.8-27B AGENT) | 7770 |
-| dankclaw | dank | 192.168.0.143 | AI, search, development, observability | frank-large (gufo, Qwen3.8-27B UD-Q8_K_XL) | 7770 |
+| dankclaw | dank | 192.168.0.143 | AI, search, development, observability | frank-dragoon (gufo, Qwen3.8-27B UD-Q8_K_XL) | 7770 |
 
 ## Active Services
 
@@ -30,7 +30,7 @@ one deploy script.
 | Gitea | dankclaw | gitea.dankclaw.local | 3001 |
 | Grafana | dankclaw | grafana.dankclaw.local | 3002 |
 | Prometheus | dankclaw | prometheus.dankclaw.local | 9090 |
-| frank-large | dankclaw | — (bare endpoint) | 7770 |
+| frank-dragoon | dankclaw | — (bare endpoint) | 7770 |
 
 ## Structure
 

autoresearch.sh

@@ -1,117 +1,26 @@
 #!/usr/bin/env bash
-# autoresearch.sh — canonical benchmark entrypoint: speed of frank-primary.
+# autoresearch.sh — canonical frank-archon benchmark entry point (dev box).
 #
-# Runs on the operator box and drives one bench window on DANKSERVER:
-#   1. fingerprint the candidate trio (env + serve script + unit)
-#   2. memo fast-path: an identical fingerprint that already produced a FULLY
-#      successful window (bench + verified production restore) returns the
-#      cached metrics without touching the fleet
-#   3. stage the candidate trio plus the measure client into
-#      /home/dank/.autoresearch-frank-primary/ (ephemeral; the repo checkout
-#      on the host stays the production source of truth)
-#   4. run the window (scripts/autoresearch/frank-primary-window.sh):
-#      stop + mask the production unit, boot the staged config AS THE SERVICE
-#      (same serve script, same container, same port 7770), wait for health,
-#      run the in-container usage-counter measure, then restore the production
-#      unit and verify its health — AGENTS.md Benchmarking Policy
-#   5. print METRIC lines (parse by run_experiment)
-#
-# Primary metric: decode_tps (HIGHER is better) — median across the three
-# prompt depths (115/1056/4096) of per-depth medians of
-# completion_tokens / (wall - ttft), 3 runs each after a warm pass,
-# temperature 0, the campaign's deterministic word-seed workload.
-#
-# Exit 0 with METRIC lines on success; non-zero on any failure (the window
-# script's EXIT trap restores production on every path).
-set -euo pipefail
+# The service runs on dankserver (192.168.0.235:7770), the two R9700s live
+# there, and the benchmark must own those cards, so the whole stop -> boot
+# scratch -> bench -> restore sequence runs ON dankserver (see
+# scripts/autoresearch-frank-archon.sh). This wrapper:
+#   1. copies the candidate config (the repo's scripts/frank-archon.env, the
+#      file the autoresearch loop edits) and the bench script to dankserver,
+#   2. runs the bench over ssh, relaying its stdout (the METRIC lines) and
+#      exit code back here verbatim.
+# It deliberately does NOT push to origin: the scp dirties dankserver's
+# working tree, and the loop's uncommitted candidate config must not be
+# pushed. Only this file and scripts/autoresearch-frank-archon.sh are
+# committed; the candidate env rides over ssh each run.
+set -uo pipefail
+DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+REMOTE=dankserver
+REMOTE_REPO=/home/dank/serverAppConfigs
 
-SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)"
-HOST="${FRANK_PRIMARY_AR_HOST:-dankserver}"
-STAGE="/home/dank/.autoresearch-frank-primary"
+scp -q "$DIR/scripts/frank-archon.env" \
+    "$REMOTE:$REMOTE_REPO/scripts/frank-archon.env" || { echo "scp env failed" >&2; exit 1; }
+scp -q "$DIR/scripts/autoresearch-frank-archon.sh" \
+    "$REMOTE:$REMOTE_REPO/scripts/autoresearch-frank-archon.sh" || { echo "scp script failed" >&2; exit 1; }
 
-# FRANK_PRIMARY_AR_ENV_FILE stages a DIFFERENT env than the repo's — that is how
-# the arms driver A/Bs engine knobs without mutating the checkout. The
-# fingerprint covers whatever file is staged, so the memo cannot cross arms.
-ENV_FILE="${FRANK_PRIMARY_AR_ENV_FILE:-$SCRIPT_DIR/scripts/frank-primary.env}"
-SERVE="$SCRIPT_DIR/scripts/serve-frank-primary.sh"
-UNIT="$SCRIPT_DIR/scripts/frank-primary.service"
-MEASURE="$SCRIPT_DIR/scripts/autoresearch/frank-primary-measure.py"
-WINDOW="$SCRIPT_DIR/scripts/autoresearch/frank-primary-window.sh"
-
-for f in "$ENV_FILE" "$SERVE" "$UNIT" "$MEASURE" "$WINDOW"; do
-    [ -f "$f" ] || { echo "[autoresearch] missing harness file: $f" >&2; exit 1; }
-done
-command -v python3 >/dev/null 2>&1 || { echo "[autoresearch] python3 required on operator box" >&2; exit 1; }
-
-# Fingerprint of everything that can change the engine's argv or environment.
-HASH="$(cat "$ENV_FILE" "$SERVE" "$UNIT" | sha256sum | cut -d' ' -f1)"
-echo "[autoresearch] candidate fingerprint $HASH" >&2
-
-ssh_run() { ssh -o BatchMode=yes -o ConnectTimeout=15 "$HOST" "$@"; }
-
-emit_metrics() { # $1 = run.json
-    python3 -c '
-import json, sys
-run = json.loads(sys.argv[1])
-m = run["measure"]
-print("METRIC decode_tps=%s" % m["decode_tps"])
-for k in ("decode_tps_115", "decode_tps_1056", "decode_tps_4096"):
-    print("METRIC %s=%s" % (k, m[k]))
-print("METRIC ttft_ms_4096=%s" % m["ttft_ms_4096"])
-print("METRIC kv_tokens=%s" % (run.get("kv_tokens") or 0))
-print("METRIC boot_seconds=%s" % (run.get("boot_seconds") or -1))
-print("METRIC completion_tokens_4096=%s" % m.get("completion_tokens_4096", 0))
-# Any extra sampling temperature the measure swept (AR_TEMPS), e.g. the 0.7
-# arm — that is where speculative-decode acceptance shows up, since a greedy
-# draft matches a greedy target exactly and is rejected more under real
-# sampling. Suffixed keys only (_t0.7), so the historical lines are untouched.
-for k in sorted(m):
-    if "_t" in k and (k.startswith("decode_tps") or k.startswith("ttft_ms")):
-        print("METRIC %s=%s" % (k, m[k]))
-' "$1"
-}
-
-# --- memo fast-path -------------------------------------------------------
-cached_hash="$(ssh_run "cat '$STAGE/last/hash' 2>/dev/null" 2>/dev/null || true)"
-if [ -n "$cached_hash" ] && [ "$cached_hash" = "$HASH" ]; then
-    cached_run="$(ssh_run "cat '$STAGE/last/run.json' 2>/dev/null" || true)"
-    if [ -n "$cached_run" ]; then
-        echo "[autoresearch] memo hit — cached metrics for $HASH, fleet untouched" >&2
-        emit_metrics "$cached_run"
-        exit 0
-    fi
-fi
-
-# --- stage the candidate ----------------------------------------------------
-echo "[autoresearch] staging candidate on $HOST:$STAGE" >&2
-ssh_run "mkdir -p '$STAGE'"
-scp -q "$ENV_FILE" "$HOST:$STAGE/frank-primary.env"
-scp -q "$SERVE" "$HOST:$STAGE/serve.sh"
-scp -q "$MEASURE" "$HOST:$STAGE/measure.py"
-scp -q "$WINDOW" "$HOST:$STAGE/window.sh"
-ssh_run "printf '%s\n' '$HASH' > '$STAGE/hash'"
-
-# --- the window -------------------------------------------------------------
-# Budgets: bench boot up to 20 min (warm boots measured ~7 min), measure up
-# to 30 min, restore boot up to 20 min — call run_experiment with
-# timeout_seconds >= 3600.
-echo "[autoresearch] opening bench window (stop+mask -> boot -> measure -> restore)" >&2
-set +e
-ssh_run "bash '$STAGE/window.sh'"
-rc=$?
-set -e
-if [ "$rc" -ne 0 ]; then
-    echo "[autoresearch] window failed (rc=$rc); host-side evidence:" >&2
-    ssh_run "tail -60 '$STAGE/fail.log' 2>/dev/null || tail -40 '$STAGE/serve.out' 2>/dev/null || tail -40 '$STAGE/measure.out' 2>/dev/null || true" >&2 || true
-    exit 1
-fi
-
-run_json="$(ssh_run "cat '$STAGE/run.json'")" || {
-    echo "[autoresearch] could not read $STAGE/run.json back" >&2; exit 1; }
-echo "[autoresearch] window result:" >&2
-printf '%s\n' "$run_json" >&2
-emit_metrics "$run_json"
-
-echo "[autoresearch] engine evidence (plan / compile path / spec counters):" >&2
-ssh_run "cat '$STAGE/evidence.log' 2>/dev/null" >&2 || true
-exit 0
+ssh "$REMOTE" "bash $REMOTE_REPO/scripts/autoresearch-frank-archon.sh $REMOTE_REPO/scripts/frank-archon.env"

dankclaw/Caddyfile

@@ -337,7 +337,16 @@ http://:8017 {
 			try_files /docs.html
 			file_server
 		}
-		@data path /services.json /status.json /app.js /style.css /deployed.js
+		# /whoami echoes the outpost-injected identity headers so the page
+		# can gate the admin button client-side (the /admin* 403 above stays
+		# the real gate; this only decides what is shown). The outpost strips
+		# client-supplied X-Authentik-* before injecting, so this is spoof-proof.
+		handle /whoami {
+			templates
+			header Content-Type application/json
+			respond "{\"user\":\"{header.X-Authentik-Username}\",\"groups\":\"{header.X-Authentik-Groups}\"}"
+		}
+		@data path /services.json /status.json /app.js /style.css /deployed.js /img/* /sfx/*
 		handle @data {
 			file_server
 		}

dankclaw/comfyui/workflows/qwen-image-2.1-t2i-art.json

@@ -0,0 +1,64 @@
+{
+  "3": {
+    "class_type": "CLIPTextEncode",
+    "_meta": { "title": "Positive prompt" },
+    "inputs": {
+      "text": "A detailed illustration of a 1930s Soviet industrial design bureau at night: a well-measured engineer at a drafting table, a warm desk lamp, rolled blueprints, gears and calipers on the desk, deep red and cream palette, gouache painterly style, intricate mechanical detail, soft shadows",
+      "clip": [ "6", 0 ]
+    }
+  },
+  "4": {
+    "class_type": "CLIPTextEncode",
+    "_meta": { "title": "Negative prompt" },
+    "inputs": {
+      "text": "lowres, blurry, deformed, extra limbs, watermark, signature, jpeg artifacts",
+      "clip": [ "6", 0 ]
+    }
+  },
+  "5": {
+    "class_type": "UNETLoader",
+    "_meta": { "title": "Qwen Image 2.1 (int8)" },
+    "inputs": { "unet_name": "qwen_image_2.1_int8_convrot.safetensors", "weight_dtype": "default" }
+  },
+  "6": {
+    "class_type": "CLIPLoader",
+    "_meta": { "title": "Qwen3-VL 8B text encoder (w4a8)" },
+    "inputs": { "clip_name": "qwen3vl_8b_w4a8.safetensors", "type": "qwen_image" }
+  },
+  "7": {
+    "class_type": "VAELoader",
+    "_meta": { "title": "VAE" },
+    "inputs": { "vae_name": "qwen_image_2.1_vae_bf16.safetensors" }
+  },
+  "8": {
+    "class_type": "EmptySD3LatentImage",
+    "_meta": { "title": "Empty Latent 1024x1024" },
+    "inputs": { "width": 1024, "height": 1024, "batch_size": 1 }
+  },
+  "9": {
+    "class_type": "KSampler",
+    "_meta": { "title": "KSampler" },
+    "inputs": {
+      "model": [ "5", 0 ],
+      "seed": 1930,
+      "steps": 20,
+      "cfg": 1.0,
+      "sampler_name": "euler",
+      "scheduler": "simple",
+      "positive": [ "3", 0 ],
+      "negative": [ "4", 0 ],
+      "latent_image": [ "8", 0 ],
+      "denoise": 1.0
+    }
+  },
+  "10": {
+    "class_type": "VAEDecode",
+    "_meta": { "title": "VAE Decode" },
+    "inputs": { "samples": [ "9", 0 ], "vae": [ "7", 0 ] }
+  },
+  "11": {
+    "class_type": "SaveImage",
+    "_meta": { "title": "Save Image (art)" },
+    "inputs": { "filename_prefix": "qwen21-art", "images": [ "10", 0 ] }
+  }
+}

dankclaw/comfyui/workflows/qwen-image-2.1-t2i-legible-text.json

@@ -0,0 +1,64 @@
+{
+  "3": {
+    "class_type": "CLIPTextEncode",
+    "_meta": { "title": "Positive prompt (legible text)" },
+    "inputs": {
+      "text": "Clean minimalist movie-poster design, dark charcoal background with a subtle vintage grain. Centered large bold white sans-serif text reading \"SOLIDARITY OF THE SOVIET COMPUTER SYSTEMS\", perfectly legible, crisp letterforms, even letter spacing. Below it, a smaller line of yellow text reading \"DANKCLAW DANKSERVER EST 2026\", equally legible. Flat graphic design, high contrast, generous margins, no other words, no watermark",
+      "clip": [ "6", 0 ]
+    }
+  },
+  "4": {
+    "class_type": "CLIPTextEncode",
+    "_meta": { "title": "Negative prompt" },
+    "inputs": {
+      "text": "blurry, illegible, misspelled, warped letters, extra text, watermark, signature, lowres, jpeg artifacts",
+      "clip": [ "6", 0 ]
+    }
+  },
+  "5": {
+    "class_type": "UNETLoader",
+    "_meta": { "title": "Qwen Image 2.1 (int8)" },
+    "inputs": { "unet_name": "qwen_image_2.1_int8_convrot.safetensors", "weight_dtype": "default" }
+  },
+  "6": {
+    "class_type": "CLIPLoader",
+    "_meta": { "title": "Qwen3-VL 8B text encoder (w4a8)" },
+    "inputs": { "clip_name": "qwen3vl_8b_w4a8.safetensors", "type": "qwen_image" }
+  },
+  "7": {
+    "class_type": "VAELoader",
+    "_meta": { "title": "VAE" },
+    "inputs": { "vae_name": "qwen_image_2.1_vae_bf16.safetensors" }
+  },
+  "8": {
+    "class_type": "EmptySD3LatentImage",
+    "_meta": { "title": "Empty Latent 832x1216 poster" },
+    "inputs": { "width": 832, "height": 1216, "batch_size": 1 }
+  },
+  "9": {
+    "class_type": "KSampler",
+    "_meta": { "title": "KSampler" },
+    "inputs": {
+      "model": [ "5", 0 ],
+      "seed": 2026,
+      "steps": 25,
+      "cfg": 1.0,
+      "sampler_name": "euler",
+      "scheduler": "simple",
+      "positive": [ "3", 0 ],
+      "negative": [ "4", 0 ],
+      "latent_image": [ "8", 0 ],
+      "denoise": 1.0
+    }
+  },
+  "10": {
+    "class_type": "VAEDecode",
+    "_meta": { "title": "VAE Decode" },
+    "inputs": { "samples": [ "9", 0 ], "vae": [ "7", 0 ] }
+  },
+  "11": {
+    "class_type": "SaveImage",
+    "_meta": { "title": "Save Image (text poster)" },
+    "inputs": { "filename_prefix": "qwen21-text", "images": [ "10", 0 ] }
+  }
+}

dankclaw/hermes/config.yaml.example

@@ -10,15 +10,15 @@ model:
   provider: dankclaw-large
   base_url: http://192.168.0.143:7770/v1
   api_key: not-needed
-  default: frank-large
+  default: frank-dragoon
 
 providers:
   dankclaw-large:
     api: http://192.168.0.143:7770/v1
     discover_models: false
     models:
-      frank-large:
-        context_length: 114688
+      frank-dragoon:
+        context_length: 262144
   dankserver-small:
     api: http://192.168.0.235:7770/v1
     discover_models: false
@@ -29,7 +29,7 @@ providers:
 # Auxiliary routing from the live configuration. Named providers route via
 # their `api:` URL; `custom` entries route by their explicit `base_url`.
 auxiliary:
-  vision: {provider: dankclaw-large, model: frank-large}
+  vision: {provider: dankclaw-large, model: frank-dragoon}
   web_extract: {provider: dankserver-small, model: frank-medium}
   compression: {provider: dankserver-small, model: frank-medium}
   skills_hub: {provider: dankserver-small, model: frank-medium}
@@ -50,8 +50,8 @@ auxiliary:
         effort: none
   memory_query_rewrite: {provider: custom, model: frank-medium, base_url: http://192.168.0.235:7770/v1}
   tts_audio_tags: {provider: custom, model: frank-medium, base_url: http://192.168.0.235:7770/v1}
-  triage_specifier: {provider: dankclaw-large, model: frank-large}
-  kanban_decomposer: {provider: dankclaw-large, model: frank-large}
+  triage_specifier: {provider: dankclaw-large, model: frank-dragoon}
+  kanban_decomposer: {provider: dankclaw-large, model: frank-dragoon}
   profile_describer: {provider: dankserver-small, model: frank-medium}
   curator: {provider: dankserver-small, model: frank-medium}
 

echo_request.json

@@ -1 +1 @@
-{"model": "frank-large", "prompt": "Below is a telemetry API schema, labeled SCHEMA A. Later in this message the same schema is repeated word for word, labeled SCHEMA B.\nTask: output SCHEMA B verbatim, with no commentary and no reformatting, starting immediately with the opening brace.\n\nSCHEMA A:\n{\"version\":\"2.3.1\",\"endpoints\":[{\"id\":\"ep-000\",\"path\":\"/v2/telemetry/gw5978x49\",\"method\":\"GET\",\"latency_ms\":219,\"owner\":\"team-0\",\"limit\":{\"burst\":221,\"sustained\":149}},{\"id\":\"ep-001\",\"path\":\"/v2/telemetry/gw6279x77\",\"method\":\"POST\",\"latency_ms\":456,\"owner\":\"team-1\",\"limit\":{\"burst\":227,\"sustained\":173}},{\"id\":\"ep-002\",\"path\":\"/v2/telemetry/gw4501x82\",\"method\":\"PUT\",\"latency_ms\":488,\"owner\":\"team-2\",\"limit\":{\"burst\":407,\"sustained\":189}},{\"id\":\"ep-003\",\"path\":\"/v2/telemetry/gw3780xA8\",\"method\":\"DELETE\",\"latency_ms\":90,\"owner\":\"team-3\",\"limit\":{\"burst\":146,\"sustained\":132}},{\"id\":\"ep-004\",\"path\":\"/v2/telemetry/gw6491x17\",\"method\":\"GET\",\"latency_ms\":842,\"owner\":\"team-4\",\"limit\":{\"burst\":488,\"sustained\":193}},{\"id\":\"ep-005\",\"path\":\"/v2/telemetry/gw4848xAC\",\"method\":\"POST\",\"latency_ms\":321,\"owner\":\"team-5\",\"limit\":{\"burst\":116,\"sustained\":51}},{\"id\":\"ep-006\",\"path\":\"/v2/telemetry/gw3414x06\",\"method\":\"PUT\",\"latency_ms\":51,\"owner\":\"team-6\",\"limit\":{\"burst\":126,\"sustained\":122}},{\"id\":\"ep-007\",\"path\":\"/v2/telemetry/gw2193x74\",\"method\":\"DELETE\",\"latency_ms\":428,\"owner\":\"team-0\",\"limit\":{\"burst\":454,\"sustained\":162}},{\"id\":\"ep-008\",\"path\":\"/v2/telemetry/gw4185xB7\",\"method\":\"GET\",\"latency_ms\":717,\"owner\":\"team-1\",\"limit\":{\"burst\":197,\"sustained\":127}},{\"id\":\"ep-009\",\"path\":\"/v2/telemetry/gw7547x3E\",\"method\":\"POST\",\"latency_ms\":155,\"owner\":\"team-2\",\"limit\":{\"burst\":336,\"sustained\":177}},{\"id\":\"ep-010\",\"path\":\"/v2/telemetry/gw1090xE4\",\"method\":\"PUT\",\"latency_ms\":772,\"owner\":\"team-3\",\"limit\":{\"burst\":441,\"sustained\":198}},{\"id\":\"ep-011\",\"path\":\"/v2/telemetry/gw2746xC7\",\"method\":\"DELETE\",\"latency_ms\":439,\"owner\":\"team-4\",\"limit\":{\"burst\":113,\"sustained\":46}},{\"id\":\"ep-012\",\"path\":\"/v2/telemetry/gw9486x76\",\"method\":\"GET\",\"latency_ms\":55,\"owner\":\"team-5\",\"limit\":{\"burst\":286,\"sustained\":64}},{\"id\":\"ep-013\",\"path\":\"/v2/telemetry/gw2988x74\",\"method\":\"POST\",\"latency_ms\":140,\"owner\":\"team-6\",\"limit\":{\"burst\":411,\"sustained\":119}},{\"id\":\"ep-014\",\"path\":\"/v2/telemetry/gw9702xFC\",\"method\":\"PUT\",\"latency_ms\":576,\"owner\":\"team-0\",\"limit\":{\"burst\":305,\"sustained\":82}},{\"id\":\"ep-015\",\"path\":\"/v2/telemetry/gw8251x9C\",\"method\":\"DELETE\",\"latency_ms\":838,\"owner\":\"team-1\",\"limit\":{\"burst\":369,\"sustained\":130}},{\"id\":\"ep-016\",\"path\":\"/v2/telemetry/gw7991xD4\",\"method\":\"GET\",\"latency_ms\":565,\"owner\":\"team-2\",\"limit\":{\"burst\":229,\"sustained\":41}},{\"id\":\"ep-017\",\"path\":\"/v2/telemetry/gw8777x73\",\"method\":\"POST\",\"latency_ms\":269,\"owner\":\"team-3\",\"limit\":{\"burst\":385,\"sustained\":64}},{\"id\":\"ep-018\",\"path\":\"/v2/telemetry/gw5543xC4\",\"method\":\"PUT\",\"latency_ms\":800,\"owner\":\"team-4\",\"limit\":{\"burst\":267,\"sustained\":125}},{\"id\":\"ep-019\",\"path\":\"/v2/telemetry/gw4919x46\",\"method\":\"DELETE\",\"latency_ms\":454,\"owner\":\"team-5\",\"limit\":{\"burst\":40,\"sustained\":183}},{\"id\":\"ep-020\",\"path\":\"/v2/telemetry/gw5681x3C\",\"method\":\"GET\",\"latency_ms\":282,\"owner\":\"team-6\",\"limit\":{\"burst\":172,\"sustained\":82}},{\"id\":\"ep-021\",\"path\":\"/v2/telemetry/gw9849x14\",\"method\":\"POST\",\"latency_ms\":145,\"owner\":\"team-0\",\"limit\":{\"burst\":78,\"sustained\":60}},{\"id\":\"ep-022\",\"path\":\"/v2/telemetry/gw7275xB1\",\"method\":\"PUT\",\"latency_ms\":160,\"owner\":\"team-1\",\"limit\":{\"burst\":362,\"sustained\":55}},{\"id\":\"ep-023\",\"path\":\"/v2/telemetry/gw2052x6A\",\"method\":\"DELETE\",\"latency_ms\":421,\"owner\":\"team-2\",\"limit\":{\"burst\":170,\"sustained\":139}},{\"id\":\"ep-024\",\"path\":\"/v2/telemetry/gw8633x6A\",\"method\":\"GET\",\"latency_ms\":67,\"owner\":\"team-3\",\"limit\":{\"burst\":106,\"sustained\":108}},{\"id\":\"ep-025\",\"path\":\"/v2/telemetry/gw7381xE7\",\"method\":\"POST\",\"latency_ms\":792,\"owner\":\"team-4\",\"limit\":{\"burst\":300,\"sustained\":179}},{\"id\":\"ep-026\",\"path\":\"/v2/telemetry/gw1320xDB\",\"method\":\"PUT\",\"latency_ms\":787,\"owner\":\"team-5\",\"limit\":{\"burst\":295,\"sustained\":98}},{\"id\":\"ep-027\",\"path\":\"/v2/telemetry/gw8814x01\",\"method\":\"DELETE\",\"latency_ms\":364,\"owner\":\"team-6\",\"limit\":{\"burst\":153,\"sustained\":193}},{\"id\":\"ep-028\",\"path\":\"/v2/telemetry/gw7389xDA\",\"method\":\"GET\",\"latency_ms\":859,\"owner\":\"team-0\",\"limit\":{\"burst\":215,\"sustained\":138}},{\"id\"Line truncated
+{"model": "frank-dragoon", "prompt": "Below is a telemetry API schema, labeled SCHEMA A. Later in this message the same schema is repeated word for word, labeled SCHEMA B.\nTask: output SCHEMA B verbatim, with no commentary and no reformatting, starting immediately with the opening brace.\n\nSCHEMA A:\n{\"version\":\"2.3.1\",\"endpoints\":[{\"id\":\"ep-000\",\"path\":\"/v2/telemetry/gw5978x49\",\"method\":\"GET\",\"latency_ms\":219,\"owner\":\"team-0\",\"limit\":{\"burst\":221,\"sustained\":149}},{\"id\":\"ep-001\",\"path\":\"/v2/telemetry/gw6279x77\",\"method\":\"POST\",\"latency_ms\":456,\"owner\":\"team-1\",\"limit\":{\"burst\":227,\"sustained\":173}},{\"id\":\"ep-002\",\"path\":\"/v2/telemetry/gw4501x82\",\"method\":\"PUT\",\"latency_ms\":488,\"owner\":\"team-2\",\"limit\":{\"burst\":407,\"sustained\":189}},{\"id\":\"ep-003\",\"path\":\"/v2/telemetry/gw3780xA8\",\"method\":\"DELETE\",\"latency_ms\":90,\"owner\":\"team-3\",\"limit\":{\"burst\":146,\"sustained\":132}},{\"id\":\"ep-004\",\"path\":\"/v2/telemetry/gw6491x17\",\"method\":\"GET\",\"latency_ms\":842,\"owner\":\"team-4\",\"limit\":{\"burst\":488,\"sustained\":193}},{\"id\":\"ep-005\",\"path\":\"/v2/telemetry/gw4848xAC\",\"method\":\"POST\",\"latency_ms\":321,\"owner\":\"team-5\",\"limit\":{\"burst\":116,\"sustained\":51}},{\"id\":\"ep-006\",\"path\":\"/v2/telemetry/gw3414x06\",\"method\":\"PUT\",\"latency_ms\":51,\"owner\":\"team-6\",\"limit\":{\"burst\":126,\"sustained\":122}},{\"id\":\"ep-007\",\"path\":\"/v2/telemetry/gw2193x74\",\"method\":\"DELETE\",\"latency_ms\":428,\"owner\":\"team-0\",\"limit\":{\"burst\":454,\"sustained\":162}},{\"id\":\"ep-008\",\"path\":\"/v2/telemetry/gw4185xB7\",\"method\":\"GET\",\"latency_ms\":717,\"owner\":\"team-1\",\"limit\":{\"burst\":197,\"sustained\":127}},{\"id\":\"ep-009\",\"path\":\"/v2/telemetry/gw7547x3E\",\"method\":\"POST\",\"latency_ms\":155,\"owner\":\"team-2\",\"limit\":{\"burst\":336,\"sustained\":177}},{\"id\":\"ep-010\",\"path\":\"/v2/telemetry/gw1090xE4\",\"method\":\"PUT\",\"latency_ms\":772,\"owner\":\"team-3\",\"limit\":{\"burst\":441,\"sustained\":198}},{\"id\":\"ep-011\",\"path\":\"/v2/telemetry/gw2746xC7\",\"method\":\"DELETE\",\"latency_ms\":439,\"owner\":\"team-4\",\"limit\":{\"burst\":113,\"sustained\":46}},{\"id\":\"ep-012\",\"path\":\"/v2/telemetry/gw9486x76\",\"method\":\"GET\",\"latency_ms\":55,\"owner\":\"team-5\",\"limit\":{\"burst\":286,\"sustained\":64}},{\"id\":\"ep-013\",\"path\":\"/v2/telemetry/gw2988x74\",\"method\":\"POST\",\"latency_ms\":140,\"owner\":\"team-6\",\"limit\":{\"burst\":411,\"sustained\":119}},{\"id\":\"ep-014\",\"path\":\"/v2/telemetry/gw9702xFC\",\"method\":\"PUT\",\"latency_ms\":576,\"owner\":\"team-0\",\"limit\":{\"burst\":305,\"sustained\":82}},{\"id\":\"ep-015\",\"path\":\"/v2/telemetry/gw8251x9C\",\"method\":\"DELETE\",\"latency_ms\":838,\"owner\":\"team-1\",\"limit\":{\"burst\":369,\"sustained\":130}},{\"id\":\"ep-016\",\"path\":\"/v2/telemetry/gw7991xD4\",\"method\":\"GET\",\"latency_ms\":565,\"owner\":\"team-2\",\"limit\":{\"burst\":229,\"sustained\":41}},{\"id\":\"ep-017\",\"path\":\"/v2/telemetry/gw8777x73\",\"method\":\"POST\",\"latency_ms\":269,\"owner\":\"team-3\",\"limit\":{\"burst\":385,\"sustained\":64}},{\"id\":\"ep-018\",\"path\":\"/v2/telemetry/gw5543xC4\",\"method\":\"PUT\",\"latency_ms\":800,\"owner\":\"team-4\",\"limit\":{\"burst\":267,\"sustained\":125}},{\"id\":\"ep-019\",\"path\":\"/v2/telemetry/gw4919x46\",\"method\":\"DELETE\",\"latency_ms\":454,\"owner\":\"team-5\",\"limit\":{\"burst\":40,\"sustained\":183}},{\"id\":\"ep-020\",\"path\":\"/v2/telemetry/gw5681x3C\",\"method\":\"GET\",\"latency_ms\":282,\"owner\":\"team-6\",\"limit\":{\"burst\":172,\"sustained\":82}},{\"id\":\"ep-021\",\"path\":\"/v2/telemetry/gw9849x14\",\"method\":\"POST\",\"latency_ms\":145,\"owner\":\"team-0\",\"limit\":{\"burst\":78,\"sustained\":60}},{\"id\":\"ep-022\",\"path\":\"/v2/telemetry/gw7275xB1\",\"method\":\"PUT\",\"latency_ms\":160,\"owner\":\"team-1\",\"limit\":{\"burst\":362,\"sustained\":55}},{\"id\":\"ep-023\",\"path\":\"/v2/telemetry/gw2052x6A\",\"method\":\"DELETE\",\"latency_ms\":421,\"owner\":\"team-2\",\"limit\":{\"burst\":170,\"sustained\":139}},{\"id\":\"ep-024\",\"path\":\"/v2/telemetry/gw8633x6A\",\"method\":\"GET\",\"latency_ms\":67,\"owner\":\"team-3\",\"limit\":{\"burst\":106,\"sustained\":108}},{\"id\":\"ep-025\",\"path\":\"/v2/telemetry/gw7381xE7\",\"method\":\"POST\",\"latency_ms\":792,\"owner\":\"team-4\",\"limit\":{\"burst\":300,\"sustained\":179}},{\"id\":\"ep-026\",\"path\":\"/v2/telemetry/gw1320xDB\",\"method\":\"PUT\",\"latency_ms\":787,\"owner\":\"team-5\",\"limit\":{\"burst\":295,\"sustained\":98}},{\"id\":\"ep-027\",\"path\":\"/v2/telemetry/gw8814x01\",\"method\":\"DELETE\",\"latency_ms\":364,\"owner\":\"team-6\",\"limit\":{\"burst\":153,\"sustained\":193}},{\"id\":\"ep-028\",\"path\":\"/v2/telemetry/gw7389xDA\",\"method\":\"GET\",\"latency_ms\":859,\"owner\":\"team-0\",\"limit\":{\"burst\":215,\"sustained\":138}},{\"idLine truncated

old/download-frank-archon-fp8.sh

@@ -1,9 +1,9 @@
 #!/usr/bin/env bash
-# download-frank-primary-fp8.sh — fetch/verify the Qwen3.8-Flash-Next-FP8
+# download-frank-archon-fp8.sh — fetch/verify the Qwen3.8-Flash-Next-FP8
 # payload (131 safetensors shards, 172.78 GiB total, plus aux files) for the
-# vLLM frank-primary deployment on dankserver.
+# vLLM frank-archon deployment on dankserver.
 #
-#   bash scripts/download-frank-primary-fp8.sh [dest_dir]
+#   bash scripts/download-frank-archon-fp8.sh [dest_dir]
 #
 # The manifest (scripts/manifests/qwen3.8-flash-next-fp8.manifest) carries
 # per-file sizes + LFS sha256s from the Hub; hf-fetch.sh is idempotent — an

old/download-frank-dragoon-dflash.sh

@@ -1,5 +1,5 @@
 #!/usr/bin/env bash
-# Download the z-lab Qwen3.5-9B-DFlash drafter for frank-large's DFlash
+# Download the z-lab Qwen3.5-9B-DFlash drafter for frank-dragoon's DFlash
 # speculative-decode arm (vLLM --speculative-config method=dflash). Public
 # repo — no auth header on the command line.
 #
@@ -10,7 +10,7 @@
 # the draft for that target.
 #
 # Usage:
-#   scripts/download-frank-large-dflash.sh [DEST_DIR] [--verify-only]
+#   scripts/download-frank-dragoon-dflash.sh [DEST_DIR] [--verify-only]
 set -euo pipefail
 
 REPO="z-lab/Qwen3.5-9B-DFlash"

old/download-frank-dragoon-mimo.sh

@@ -1,14 +1,14 @@
 #!/usr/bin/env bash
-# Download the BF16 MiMo-V2.6-Distill-Qwen-9B payload for frank-large
+# Download the BF16 MiMo-V2.6-Distill-Qwen-9B payload for frank-dragoon
 # (vLLM/kyuz0 gfx1151, Strix Halo iGPU). Public repo — no auth header on the
 # command line (a Bearer token in argv is world-readable via /proc).
 #
 # Per-file FRESH downloads, no resume: the house rule (see
-# download-frank-small.sh); -f/--fail-with-body plus size+sha256 against the
+# download-frank-zealot.sh); -f/--fail-with-body plus size+sha256 against the
 # Hub LFS oid is what makes an access error fail instead of "succeeding".
 #
 # Usage:
-#   scripts/download-frank-large-mimo.sh [DEST_DIR] [--verify-only]
+#   scripts/download-frank-dragoon-mimo.sh [DEST_DIR] [--verify-only]
 #
 # The verified set below is exactly what the 2026-10-01 bench window served:
 # 17.53 GiB of BF16 weights (4 shards, 18,819,720,848 B total with the rest).

old/download-frank-dragoon-qwen35.sh

@@ -1,14 +1,14 @@
 #!/usr/bin/env bash
 # Download the source Qwen3.5-9B checkpoint — the ONLY place this model
-# family's MTP head (15 mtp.* tensors) exists. frank-large runs it as the
+# family's MTP head (15 mtp.* tensors) exists. frank-dragoon runs it as the
 # vLLM cross-model MTP draft (MiMo-V2.6-Distill-Qwen-9B itself ships zero
-# mtp tensors; that is why SGLang's NEXTN on frank-small draws 0.00
+# mtp tensors; that is why SGLang's NEXTN on frank-zealot draws 0.00
 # acceptance). Public repo — no auth header on the command line.
 #
 # NOTE the odd upstream shard names (model.safetensors-0000N-of-00004...).
 #
 # Usage:
-#   scripts/download-frank-large-qwen35.sh [DEST_DIR] [--verify-only]
+#   scripts/download-frank-dragoon-qwen35.sh [DEST_DIR] [--verify-only]
 set -euo pipefail
 
 REPO="Qwen/Qwen3.5-9B"

old/download-frank-zealot-sglang-int8.sh

@@ -1,5 +1,5 @@
 #!/usr/bin/env bash
-# Download MiMo-V2.6-Distill-Qwen-9B-INT8-W8A16-AutoRound for frank-small
+# Download MiMo-V2.6-Distill-Qwen-9B-INT8-W8A16-AutoRound for frank-zealot
 # (SGLang, RTX 3090). Public repo — no auth header on the command line.
 #
 # Per-file FRESH downloads, no resume: `curl -C -` once produced a 213 MB
@@ -7,7 +7,7 @@
 # the house rule.
 #
 # Usage:
-#   scripts/download-frank-small.sh [DEST_DIR] [--verify-only]
+#   scripts/download-frank-zealot.sh [DEST_DIR] [--verify-only]
 #
 # LFS shards are verified against the Hub LFS sha256; non-LFS text files
 # against their declared byte size. Idempotent: complete files are skipped.

old/scripts/bench-frank-dragoon.sh

@@ -1,5 +1,5 @@
 #!/usr/bin/env bash
-# bench-frank-large.sh — 64k-context benchmark for the frank-default-large stack.
+# bench-frank-dragoon.sh — 64k-context benchmark for the frank-default-large stack.
 #
 # Measures generation throughput of Qwen3.6-27B Q8_K_P + DFlash + ngram-mod on
 # a single backend at 64k context. It starts llama-server on a scratch port,
@@ -7,15 +7,15 @@
 # prompt, and prints tokens/sec.
 #
 # Usage:
-#   ./scripts/bench-frank-large.sh <ROCm0|Vulkan0> [--generations N]
+#   ./scripts/bench-frank-dragoon.sh <ROCm0|Vulkan0> [--generations N]
 #
 # Example:
-#   ./scripts/bench-frank-large.sh ROCm0
-#   ./scripts/bench-frank-large.sh Vulkan0 --generations 3
+#   ./scripts/bench-frank-dragoon.sh ROCm0
+#   ./scripts/bench-frank-dragoon.sh Vulkan0 --generations 3
 set -euo pipefail
 
 SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
-DEVICE="${1:?usage: bench-frank-large.sh <ROCm0|Vulkan0> [--generations N]}"
+DEVICE="${1:?usage: bench-frank-dragoon.sh <ROCm0|Vulkan0> [--generations N]}"
 GENERATIONS=1
 if [ "${2:-}" = "--generations" ]; then
     GENERATIONS="${3:?--generations needs a count}"

old/scripts/deploy.sh

@@ -41,7 +41,7 @@ SERVICE_HEALTH[dankclaw]="http://127.0.0.1:7770/health"
 # Drop page caches before restart: with the model's pages fully cached, the
 # KV/graph allocation stalls at load (VRAM stuck at 28 GiB). See AGENTS.md.
 DROP_CACHES[dankclaw]=1
-# Passwordless restart helper (root-owned, installed via /etc/sudoers.d/frank-large).
+# Passwordless restart helper (root-owned, installed via /etc/sudoers.d/frank-dragoon).
 # When present, deploy.sh uses it instead of inline sudo commands.
 HELPER[dankclaw]="/usr/local/sbin/frank-restart-large.sh"
 # Health wait in iterations of 2s. Cold loads after the cache drop measured

old/scripts/frank-default-large.ling.env

@@ -1,6 +1,6 @@
-# Tunables for the Ling-3.0-flash TRAIL on dankclaw (frank-large-ling).
+# Tunables for the Ling-3.0-flash TRAIL on dankclaw (frank-dragoon-ling).
 # This REPLACES frank-default-large (Qwen3.6-27B) temporarily. To switch
-# back: systemctl stop frank-large-ling && systemctl start frank-default-large.
+# back: systemctl stop frank-dragoon-ling && systemctl start frank-default-large.
 # Runtime: llama.cpp FORK bailingmoe3-support; Vulkan + AMD GTT.
 #
 # Memory model (amdgpu Strix Halo gfx1151, 8x16GB LPDDR5 = 128 GiB physical):

old/scripts/frank-dragoon-ling.service

@@ -1,5 +1,5 @@
 [Unit]
-Description=llama.cpp Ling-3.0-flash Q6_K Vulkan+MTP (frank-large-ling TRIAL)
+Description=llama.cpp Ling-3.0-flash Q6_K Vulkan+MTP (frank-dragoon-ling TRIAL)
 After=network.target
 
 [Service]

old/scripts/serve-ling-flash.sh

@@ -8,7 +8,7 @@
 # Vulkan exposes as an ~111 GiB heap). MTP drafter is bundled in the same
 # GGUF (block 42) - no separate --spec-draft-model needed.
 #
-# Tie-back: to restore the Qwen3.6-27B service, stop frank-large-ling and
+# Tie-back: to restore the Qwen3.6-27B service, stop frank-dragoon-ling and
 # start frank-default-large (its env/unit are committed and unchanged).
 #
 # Tunables come from frank-default-large.ling.env in this directory unless

old/scripts/serve-llama-frank-dragoon.sh

@@ -4,11 +4,11 @@
 # Runtime: llama.cpp llama-server (>= b10411).
 #
 # Tunables come from frank-default-large.env in this directory unless the
-# FRANK_LARGE_ENV_FILE environment variable overrides that path.
+# FRANK_DRAGOON_ENV_FILE environment variable overrides that path.
 set -euo pipefail
 
 SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
-ENV_FILE="${FRANK_LARGE_ENV_FILE:-$SCRIPT_DIR/frank-default-large.env}"
+ENV_FILE="${FRANK_DRAGOON_ENV_FILE:-$SCRIPT_DIR/frank-default-large.env}"
 if [[ -f "$ENV_FILE" ]]; then
     set -a
     # shellcheck disable=SC1090

prose_request.json

@@ -1 +1 @@
-{"model": "frank-large", "prompt": "# Subsurface Aquifer Monitoring Network - System Design Document (Revision 7)\n\nThis document describes the deployment of a subsurface aquifer monitoring network for the Cascadia sedimentary basin. It is written for the operations crew and the regional water authority. Every sensor node, relay, aggregation service, calibration procedure, and failure mode below carries a stable alphanumeric identifier that appears in every table and in the field notes.\n\n## Sensor nodes\nNode SN-000-08B9 sits in a discharge lens at 359.0 m below datum and reports a salinity of 2.38 ppt with the fractured interval reading 5.40 degC at dawn and the wellhead porous 1.72 m3/d while the electrode pair returns 3157 uS/cm.\nNode SN-001-0A65 sits in a percolate lens at 25.9 m below datum and steps down to a salinity of 2.13 ppt with the diapir interval reading 8.55 degC at dawn and the wellhead silty 0.67 m3/d while the electrode pair returns 979 uS/cm.\nNode SN-002-0571 sits in a diapir lens at 287.8 m below datum and peaks at a salinity of 7.63 ppt with the karst interval reading 4.26 degC at dawn and the wellhead spooned 11.50 m3/d while the electrode pair returns 2987 uS/cm.\nNode SN-003-0CE9 sits in a confining lens at 169.5 m below datum and logs a salinity of 0.96 ppt with the alluvial interval reading 5.03 degC at dawn and the wellhead salinized 12.08 m3/d while the electrode pair returns 2607 uS/cm.\nNode SN-004-0E2A sits in a freshened lens at 70.4 m below datum and settles near a salinity of 8.68 ppt with the spooned interval reading 4.88 degC at dawn and the wellhead siphon 4.38 m3/d while the electrode pair returns 2707 uS/cm.\nNode SN-005-0DDD sits in a percolate lens at 44.6 m below datum and reports a salinity of 6.25 ppt with the alluvial interval reading 10.85 degC at dawn and the wellhead brackish 13.99 m3/d while the electrode pair returns 3618 uS/cm.\nNode SN-006-0EFC sits in a till lens at 309.5 m below datum and reports a salinity of 3.49 ppt with the lacustrine interval reading 7.38 degC at dawn and the wellhead spooned 3.21 m3/d while the electrode pair returns 1253 uS/cm.\nNode SN-007-0B02 sits in a recharge lens at 262.0 m below datum and steps down to a salinity of 2.38 ppt with the discharge interval reading 8.18 degC at dawn and the wellhead perched 4.05 m3/d while the electrode pair returns 3900 uS/cm.\nNode SN-008-0448 sits in a karst lens at 406.5 m below datum and reports a salinity of 7.32 ppt with the upconing interval reading 6.17 degC at dawn and the wellhead fluvial 0.75 m3/d while the electrode pair returns 1448 uS/cm.\nNode SN-009-043C sits in a alluvial lens at 159.3 m below datum and flags a salinity of 6.20 ppt with the percolate interval reading 7.60 degC at dawn and the wellhead brackish 13.01 m3/d while the electrode pair returns 2025 uS/cm.\nNode SN-010-0FF5 sits in a karst lens at 264.2 m below datum and flags a salinity of 7.05 ppt with the freshened interval reading 7.88 degC at dawn and the wellhead siphon 8.41 m3/d while the electrode pair returns 1635 uS/cm.\nNode SN-011-098A sits in a drain lens at 365.7 m below datum and reports a salinity of 8.11 ppt with the wedge interval reading 5.51 degC at dawn and the wellhead glacial 2.52 m3/d while the electrode pair returns 2916 uS/cm.\nNode SN-012-0AE8 sits in a till lens at 259.6 m below datum and steps down to a salinity of 9.13 ppt with the recharge interval reading 11.60 degC at dawn and the wellhead spooned 0.46 m3/d while the electrode pair returns 3077 uS/cm.\nNode SN-013-0B83 sits in a salinized lens at 171.2 m below datum and peaks at a salinity of 2.83 ppt with the lacustrine interval reading 5.56 degC at dawn and the wellhead discharge 0.35 m3/d while the electrode pair returns 3083 uS/cm.\nNode SN-014-032E sits in a drain lens at 249.6 m below datum and flags a salinity of 1.09 ppt with the salinized interval reading 9.58 degC at dawn and the wellhead perched 12.00 m3/d while the electrode pair returns 2221 uS/cm.\nNode SN-015-004F sits in a aeolian lens at 264.4 m below datum and reports a salinity of 7.34 ppt with the salinized interval reading 8.76 degC at dawn and the wellhead perched 0.31 m3/d while the electrode pair returns 1483 uS/cm.\nNode SN-016-07C6 sits in a aeolian lens at 155.9 m below datum and reports a salinity of 0.64 ppt with the mineralized interval reading 11.75 degC at dawn and the wellhead diluted 13.46 m3/d while the electrode pair returns 524 uS/cm.\nNode SN-017-06C5 sits in a salinized lens at 72.1 m below datum and averages a salinity of 4.52 ppt with the siphon interval reading 8.93 degC at dawn and the wellhead confining 3.98 m3/d while the electrode pair returns 3687 uS/cm.\nNode SN-018-0E64 sits in a siphon lens at 334.9 m below datum and steps down to a salinity of 6.73 ppt with the salinized interval reading 7.63 degC at dawn and the wellhead freshened 9.64 m3/d while the electrode pair returns 1681 uS/cm.\nNode SN-019-0122 sits in a spooned lens at 1Line truncated
+{"model": "frank-dragoon", "prompt": "# Subsurface Aquifer Monitoring Network - System Design Document (Revision 7)\n\nThis document describes the deployment of a subsurface aquifer monitoring network for the Cascadia sedimentary basin. It is written for the operations crew and the regional water authority. Every sensor node, relay, aggregation service, calibration procedure, and failure mode below carries a stable alphanumeric identifier that appears in every table and in the field notes.\n\n## Sensor nodes\nNode SN-000-08B9 sits in a discharge lens at 359.0 m below datum and reports a salinity of 2.38 ppt with the fractured interval reading 5.40 degC at dawn and the wellhead porous 1.72 m3/d while the electrode pair returns 3157 uS/cm.\nNode SN-001-0A65 sits in a percolate lens at 25.9 m below datum and steps down to a salinity of 2.13 ppt with the diapir interval reading 8.55 degC at dawn and the wellhead silty 0.67 m3/d while the electrode pair returns 979 uS/cm.\nNode SN-002-0571 sits in a diapir lens at 287.8 m below datum and peaks at a salinity of 7.63 ppt with the karst interval reading 4.26 degC at dawn and the wellhead spooned 11.50 m3/d while the electrode pair returns 2987 uS/cm.\nNode SN-003-0CE9 sits in a confining lens at 169.5 m below datum and logs a salinity of 0.96 ppt with the alluvial interval reading 5.03 degC at dawn and the wellhead salinized 12.08 m3/d while the electrode pair returns 2607 uS/cm.\nNode SN-004-0E2A sits in a freshened lens at 70.4 m below datum and settles near a salinity of 8.68 ppt with the spooned interval reading 4.88 degC at dawn and the wellhead siphon 4.38 m3/d while the electrode pair returns 2707 uS/cm.\nNode SN-005-0DDD sits in a percolate lens at 44.6 m below datum and reports a salinity of 6.25 ppt with the alluvial interval reading 10.85 degC at dawn and the wellhead brackish 13.99 m3/d while the electrode pair returns 3618 uS/cm.\nNode SN-006-0EFC sits in a till lens at 309.5 m below datum and reports a salinity of 3.49 ppt with the lacustrine interval reading 7.38 degC at dawn and the wellhead spooned 3.21 m3/d while the electrode pair returns 1253 uS/cm.\nNode SN-007-0B02 sits in a recharge lens at 262.0 m below datum and steps down to a salinity of 2.38 ppt with the discharge interval reading 8.18 degC at dawn and the wellhead perched 4.05 m3/d while the electrode pair returns 3900 uS/cm.\nNode SN-008-0448 sits in a karst lens at 406.5 m below datum and reports a salinity of 7.32 ppt with the upconing interval reading 6.17 degC at dawn and the wellhead fluvial 0.75 m3/d while the electrode pair returns 1448 uS/cm.\nNode SN-009-043C sits in a alluvial lens at 159.3 m below datum and flags a salinity of 6.20 ppt with the percolate interval reading 7.60 degC at dawn and the wellhead brackish 13.01 m3/d while the electrode pair returns 2025 uS/cm.\nNode SN-010-0FF5 sits in a karst lens at 264.2 m below datum and flags a salinity of 7.05 ppt with the freshened interval reading 7.88 degC at dawn and the wellhead siphon 8.41 m3/d while the electrode pair returns 1635 uS/cm.\nNode SN-011-098A sits in a drain lens at 365.7 m below datum and reports a salinity of 8.11 ppt with the wedge interval reading 5.51 degC at dawn and the wellhead glacial 2.52 m3/d while the electrode pair returns 2916 uS/cm.\nNode SN-012-0AE8 sits in a till lens at 259.6 m below datum and steps down to a salinity of 9.13 ppt with the recharge interval reading 11.60 degC at dawn and the wellhead spooned 0.46 m3/d while the electrode pair returns 3077 uS/cm.\nNode SN-013-0B83 sits in a salinized lens at 171.2 m below datum and peaks at a salinity of 2.83 ppt with the lacustrine interval reading 5.56 degC at dawn and the wellhead discharge 0.35 m3/d while the electrode pair returns 3083 uS/cm.\nNode SN-014-032E sits in a drain lens at 249.6 m below datum and flags a salinity of 1.09 ppt with the salinized interval reading 9.58 degC at dawn and the wellhead perched 12.00 m3/d while the electrode pair returns 2221 uS/cm.\nNode SN-015-004F sits in a aeolian lens at 264.4 m below datum and reports a salinity of 7.34 ppt with the salinized interval reading 8.76 degC at dawn and the wellhead perched 0.31 m3/d while the electrode pair returns 1483 uS/cm.\nNode SN-016-07C6 sits in a aeolian lens at 155.9 m below datum and reports a salinity of 0.64 ppt with the mineralized interval reading 11.75 degC at dawn and the wellhead diluted 13.46 m3/d while the electrode pair returns 524 uS/cm.\nNode SN-017-06C5 sits in a salinized lens at 72.1 m below datum and averages a salinity of 4.52 ppt with the siphon interval reading 8.93 degC at dawn and the wellhead confining 3.98 m3/d while the electrode pair returns 3687 uS/cm.\nNode SN-018-0E64 sits in a siphon lens at 334.9 m below datum and steps down to a salinity of 6.73 ppt with the salinized interval reading 7.63 degC at dawn and the wellhead freshened 9.64 m3/d while the electrode pair returns 1681 uS/cm.\nNode SN-019-0122 sits in a spooned lens atLine truncated

scripts/.AGENTTRASH/bench-decode-threads-batch.py.strix-rocmfp4

@@ -1,6 +1,6 @@
 #!/usr/bin/env python3
 """
-Decode throughput benchmark for frank-large.
+Decode throughput benchmark for frank-dragoon.
 Starts the server with a given --threads-batch value, sends an 8K+ token prompt,
 generates 256 tokens, measures generation tok/s.
 
@@ -13,12 +13,12 @@ SERVE = "/home/dank/GitPackages/ROCmFPX/build-qwen38/bin/llama-server"
 PORT = 7770
 N_GEN = 256
 PROMPT_FILE = "/tmp/bench-prompts/prompt_code.txt"
-ENV_FILE = os.path.join(os.path.dirname(__file__), "frank-large.env")
+ENV_FILE = os.path.join(os.path.dirname(__file__), "frank-dragoon.env")
 SERVER_DIR = os.path.dirname(SERVE)
 ROCM_PATH = "/opt/rocm"
 
 def make_env():
-    """Build the same env as serve-frank-large.sh."""
+    """Build the same env as serve-frank-dragoon.sh."""
     env = {**os.environ, "HSA_OVERRIDE_GFX_VERSION": "11.5.1", "HIP_VISIBLE_DEVICES": "0"}
     
     # Source env file for tunables
@@ -59,7 +59,7 @@ def wait_ready():
 def send_request(prompt, max_tokens=N_GEN):
     """Send chat completion, measure generation throughput."""
     body = json.dumps({
-        "model": "frank-large",
+        "model": "frank-dragoon",
         "messages": [{"role": "user", "content": prompt}],
         "max_tokens": max_tokens,
         "stream": False,

scripts/.AGENTTRASH/bench-ngram-mod.py.ik-llama.cpp

@@ -1,6 +1,6 @@
 #!/usr/bin/env python3
 """
-Benchmark n-gram speculative decoding vs no-spec for frank-large.
+Benchmark n-gram speculative decoding vs no-spec for frank-dragoon.
 
 Tests prompt-processing throughput with 16K token prompts (manageable request size).
 Code-heavy prompt (high n-gram redundancy) vs prose prompt (low redundancy).
@@ -103,7 +103,7 @@ def start_server(port, spec_type):
 def run_test(prompt_text, spec_type, port):
     """Send a request and extract prompt processing metrics."""
     data = json.dumps({
-        "model": "frank-large",
+        "model": "frank-dragoon",
         "messages": [{"role": "user", "content": prompt_text}],
         "max_tokens": TEST_TOKENS,
         "stream": False,
@@ -189,7 +189,7 @@ def main():
         print(f"  Prose: {prose_prompt_file.stat().st_size:,} bytes")
 
     print("=" * 60)
-    print("  N-gram Mod Benchmark — frank-large")
+    print("  N-gram Mod Benchmark — frank-dragoon")
     print(f"  STRIX ROCmFP4 · 64K context · 16K prompts")
     print("=" * 60)
 

scripts/.AGENTTRASH/bench-ngram-mod.sh.ik-llama.cpp

@@ -1,19 +1,19 @@
 #!/usr/bin/env bash
-# Benchmark n-gram speculative decoding vs no-spec for frank-large.
+# Benchmark n-gram speculative decoding vs no-spec for frank-dragoon.
 #
 # This tests prompt-processing throughput at 64k context with two distinct
 # prompts: one code-heavy and one prose-heavy. Uses llama-server on scratch
 # ports with the OpenAI-compatible API to measure prompt_eval_duration_ms.
 #
 # Run on Dankclaw after stopping the production service:
-#   sudo systemctl stop frank-large
+#   sudo systemctl stop frank-dragoon
 #   ./scripts/bench-ngram-mod.sh
-#   sudo systemctl start frank-large
+#   sudo systemctl start frank-dragoon
 
 set -euo pipefail
 
 SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)"
-ENV_FILE="${FRANK_LARGE_ENV_FILE:-$SCRIPT_DIR/frank-large.env}"
+ENV_FILE="${FRANK_DRAGOON_ENV_FILE:-$SCRIPT_DIR/frank-dragoon.env}"
 if [[ -f "$ENV_FILE" ]]; then
     set -a; source "$ENV_FILE"; set +a
 fi
@@ -184,7 +184,7 @@ run_single_test() {
     response=$(curl -s -X POST "http://127.0.0.1:$port/v1/completions" \
         -H "Content-Type: application/json" \
         -d "{
-            \"model\": \"frank-large\",
+            \"model\": \"frank-dragoon\",
             \"prompt\": \"$prompt_text\",
             \"max_tokens\": 128,
             \"temperature\": 0,
@@ -220,7 +220,7 @@ run_single_test() {
 }
 
 echo "╔══════════════════════════════════════════════════════════╗"
-echo "║  N-gram Mod Benchmark — frank-large             ║"
+echo "║  N-gram Mod Benchmark — frank-dragoon             ║"
 echo "║  STRIX ROCmFP4 · 64k context · two prompts             ║"
 echo "╚══════════════════════════════════════════════════════════╝"
 echo ""

scripts/.AGENTTRASH/bench-spec-decode.py.ik-llama.cpp

@@ -15,9 +15,9 @@ import time
 import urllib.request
 import urllib.error
 
-SERVICE = "frank-large"
-ENV_FILE = "/home/dank/serverAppConfigs/scripts/frank-large.env"
-ALIAS = "frank-large"
+SERVICE = "frank-dragoon"
+ENV_FILE = "/home/dank/serverAppConfigs/scripts/frank-dragoon.env"
+ALIAS = "frank-dragoon"
 DEFAULT_HOST = "localhost"
 DEFAULT_PORT = 7770
 DEFAULT_MAX_TOKENS = 16384

scripts/.AGENTTRASH/frank-dragoon.env.ik-llama.cpp

@@ -1,4 +1,4 @@
-# Tunables for frank-large (mradermacher i1-Q4_K_M of
+# Tunables for frank-dragoon (mradermacher i1-Q4_K_M of
 # orcarouter/Qwen3.8-Flash-Next-Uncensored on ik_llama.cpp, Dankclaw,
 # RTX 3090 CUDA + Strix Halo CPU path, since 2026-09-15).
 #
@@ -65,7 +65,7 @@ MMPROJ_PATH=/home/dank/models/mradermacher-Qwen3.8-Flash-Next-Uncensored-i1-Q4_K
 CHAT_TEMPLATE_FILE=/home/dank/serverAppConfigs/scripts/chat-template.jinja
 
 # Alias + network.
-ALIAS=frank-large
+ALIAS=frank-dragoon
 BIND_ADDR=0.0.0.0
 LISTEN_PORT=7770
 

scripts/.AGENTTRASH/frank-dragoon.service.ik-llama.cpp

@@ -1,5 +1,5 @@
 [Unit]
-Description=ik_llama.cpp Qwen3.8-Flash-Next-Uncensored i1-Q4_K_M 177B MoE (dankclaw, frank-large)
+Description=ik_llama.cpp Qwen3.8-Flash-Next-Uncensored i1-Q4_K_M 177B MoE (dankclaw, frank-dragoon)
 After=network-online.target
 Wants=network-online.target
 
@@ -12,8 +12,8 @@ Group=dank
 # budget still needs room. Parity with the halogen quadlet's
 # Ulimit=memlock=-1:-1.
 LimitMEMLOCK=infinity
-Environment="FRANK_LARGE_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-large.env"
-ExecStart=/home/dank/serverAppConfigs/scripts/serve-frank-large.sh
+Environment="FRANK_DRAGOON_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-dragoon.env"
+ExecStart=/home/dank/serverAppConfigs/scripts/serve-frank-dragoon.sh
 Restart=on-failure
 RestartSec=10
 

scripts/.AGENTTRASH/serve-frank-dragoon.sh.ik-llama.cpp

@@ -1,5 +1,5 @@
 #!/usr/bin/env bash
-# Serve mradermacher/Qwen3.8-Flash-Next-Uncensored i1-Q4_K_M as frank-large
+# Serve mradermacher/Qwen3.8-Flash-Next-Uncensored i1-Q4_K_M as frank-dragoon
 # via ik_llama.cpp on Dankclaw.
 #
 # Topology (ikawrakow's hybrid recipe; upstream issue #2402 for the PLE):
@@ -26,7 +26,7 @@
 set -euo pipefail
 
 SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)"
-ENV_FILE="${FRANK_LARGE_ENV_FILE:-$SCRIPT_DIR/frank-large.env}"
+ENV_FILE="${FRANK_DRAGOON_ENV_FILE:-$SCRIPT_DIR/frank-dragoon.env}"
 if [[ -f "$ENV_FILE" ]]; then
     set -a
     # shellcheck disable=SC1090
@@ -66,7 +66,7 @@ fi
 # CPU-overridden weights mmapped (src/llama-load-tensors.cpp); the env file
 # sets it. Refuse to run without it.
 if [[ "${GGML_CUDA_NO_PINNED_WEIGHTS:-}" != "1" ]]; then
-    echo "frank-large: refusing to start — GGML_CUDA_NO_PINNED_WEIGHTS=1 is mandatory on this host" >&2
+    echo "frank-dragoon: refusing to start — GGML_CUDA_NO_PINNED_WEIGHTS=1 is mandatory on this host" >&2
     exit 1
 fi
 

scripts/.AGENTTRASH/serve-frank-medium.sh.rocmfpx

@@ -112,7 +112,7 @@ fi
 : "${SPEC_DRAFT_POLL_BATCH:=1}"
 
 # Text only: the server must not try to autoload the vision tower.  Vision
-# stays on frank-large (Dankclaw), which is where the fleet routes images.
+# stays on frank-dragoon (Dankclaw), which is where the fleet routes images.
 NO_MMPROJ="${NO_MMPROJ:-1}"
 
 export HIP_VISIBLE_DEVICES

scripts/apply-protected-cast.sh

@@ -0,0 +1,43 @@
+#!/usr/bin/env bash
+# apply-protected-cast.sh — RUNS ON DANKSERVER. Rewrite the recipe's
+# PROTECTED-BEGIN/END section from Swift's OWN calibration grams: run
+# derive-protected-experts.py over the calib dir, splice its cast lines into
+# the marked section of the recipe in place, keep the pre-edit recipe in the
+# campaign trash. Refuses to run twice (marker text says derived).
+set -euo pipefail
+CALIB=${1:-/home/dank/corpora/calib}
+RECIPE=${2:-/home/dank/serverAppConfigs-swift15/scripts/recipes/qwen4exp-swift15-w4dn8-i8-hc8m.recipe}
+PY=/home/dank/venvs/radcorpus/bin/python
+DERIVE=/home/dank/serverAppConfigs-swift15/scripts/derive-protected-experts.py
+TS=$(date +%Y%m%d-%H%M%S)
+
+grep -q "derive-protected-experts.py rewrote" "$RECIPE" && {
+    echo "recipe already carries derived cast lines; refusing to re-derive" >&2; exit 1; }
+grep -q "PROTECTED-BEGIN" "$RECIPE" || { echo "no PROTECTED markers in $RECIPE" >&2; exit 1; }
+
+"$PY" "$DERIVE" "$CALIB" > "/tmp/protected-cast-$TS.txt"
+N=$(grep -c 'cast dtype=bf16' "/tmp/protected-cast-$TS.txt")
+[ "$N" -ge 2 ] || { echo "derive produced $N cast lines; refusing" >&2; exit 1; }
+echo "derived $N protected experts -> /tmp/protected-cast-$TS.txt"
+
+cp -f "$RECIPE" "/home/dank/.AGENTTRASH/$TS-qwen4exp-swift15-w4dn8-i8-hc8m.recipe"
+"$PY" - "$RECIPE" "/tmp/protected-cast-$TS.txt" <<'PYEOF'
+import sys
+recipe, castfile = sys.argv[1], sys.argv[2]
+lines = open(recipe).read().splitlines()
+cast = [l for l in open(castfile).read().splitlines() if 'cast dtype=bf16' in l]
+out, insec = [], False
+for l in lines:
+    if 'PROTECTED-BEGIN' in l:
+        insec = True
+        out.append(l)
+        out.extend(cast)
+    elif 'PROTECTED-END' in l:
+        insec = False
+        out.append(l)
+        out.append('# (derive-protected-experts.py rewrote this section from Swift\'s own grams)')
+    elif not insec:
+        out.append(l)
+open(recipe, 'w').write('\n'.join(out) + '\n')
+print(f'spliced {len(cast)} cast lines into {recipe}')
+PYEOF

scripts/autoresearch-bench.py

@@ -1,5 +1,5 @@
 #!/usr/bin/env python3
-"""autoresearch-bench.py — deterministic greedy battery for frank-large.
+"""autoresearch-bench.py — deterministic greedy battery for frank-dragoon.
 
 Runs ON Dankclaw (no LAN jitter) against the candidate container on :7770.
 Fixed embedded corpus, temperature 0, streaming so decode speed is measured
@@ -104,7 +104,7 @@ def stream_completion(url: str, model: str, prompt: str):
 def main():
     ap = argparse.ArgumentParser()
     ap.add_argument("--url", default="http://127.0.0.1:7770")
-    ap.add_argument("--model", default="frank-large")
+    ap.add_argument("--model", default="frank-dragoon")
     args = ap.parse_args()
 
     with urllib.request.urlopen(args.url.rstrip("/") + "/v1/models",

scripts/autoresearch-frank-archon.sh

@@ -0,0 +1,187 @@
+#!/usr/bin/env bash
+# autoresearch-frank-archon.sh — RUNS ON DANKSERVER, driven over ssh by the
+# dev-box autoresearch.sh. It is the canonical frank-archon benchmark entry
+# point for the autoresearch loop.
+#
+# Method (mandated by the Benchmarking Policy): the production service serves
+# real users and shares the two R9700s, so a bench beside it starves the GPUs
+# and corrupts results. This script therefore:
+#   1. stops the production frank-archon unit (root, relink symlink: stop,
+#      NOT mask — mask refuses to replace a symlinked unit file),
+#   2. boots a scratch radiance container named `arbench` on the SAME two
+#      cards with the candidate engine argv (the env file the loop edits),
+#   3. polls /health until the listener is live (it binds AFTER the full
+#      load, so a bare curl is an honest gate),
+#   4. runs ONE self-contained completion request locally (127.0.0.1, no LAN
+#      jitter): a fixed ~140k-char real-text prompt (~32k tokens) decoded for
+#      256 tokens, greedy. The engine's `timings` object reports the honest
+#      prefill and decode rates for that single request.
+#   5. prints METRIC lines and tears the scratch down,
+#   6. restores production (systemctl start), via a trap so a failed bench
+#      never leaves frank-archon down (the stale-probe-tail lesson).
+#
+# Determinism: the prompt is built from a fixed, sorted corpus of repo files
+# with a fixed random seed, so prompt_n is stable across runs. Sampling is
+# greedy (temperature 0), so the decode length is fixed; the only residual
+# nondeterminism is the wht6 lossy TP all-reduce, which is a constant across
+# runs and cancels in A/B comparisons.
+#
+# The scratch mirrors the production container contract exactly (serve-frank-
+# primary.sh): --network host, --init, seccomp=unconfined (io_uring for the
+# n-gram table), memlock unbounded (the ~132 GiB pinned ledger), /dev/kfd +
+# /dev/dri, the .rad ro, the state dir rw, the tune cache mount. The ONLY
+# differences: the container name (arbench, so prod's identity is untouched)
+# and a FRESH prefix-cache disk tier (arbench/, wiped per run) so the cold
+# prefill is cold — the prod tier at kvcache/frank-archon is left intact.
+set -uo pipefail
+
+ENV_FILE="${1:-/home/dank/serverAppConfigs/scripts/frank-archon.env}"
+SCRATCH=arbench
+PORT=7770
+HEALTH="http://127.0.0.1:$PORT/health"
+COMPLETE="http://127.0.0.1:$PORT/v1/completions"
+BODY=/tmp/arbench-body.json
+LOG=/home/dank/logs/arbench.log
+
+restore() {
+  podman rm -f "$SCRATCH" >/dev/null 2>&1 || true
+  sudo systemctl start frank-archon >/dev/null 2>&1 || true
+}
+trap restore EXIT
+
+# --- source the candidate config (same file the production unit reads) ------
+if [ ! -f "$ENV_FILE" ]; then
+  echo "no env file at $ENV_FILE" >&2; exit 1
+fi
+# shellcheck disable=SC1090
+set -a; . "$ENV_FILE"; set +a
+
+# --- stop production; the scratch needs both cards to itself ----------------
+sudo systemctl stop frank-archon >/dev/null 2>&1 || true
+podman rm -f "$SCRATCH" >/dev/null 2>&1 || true
+
+# --- fresh prefix-cache tier for a cold prefill (prod's tier untouched) ------
+FRESH_KV="$FRANK_ARCHON_STATE_DIR/kvcache/$SCRATCH"
+rm -rf "$FRESH_KV"; mkdir -p "$FRESH_KV"
+mkdir -p "$FRANK_ARCHON_STATE_DIR/tune"
+
+# --- boot the scratch: the production run line, scratch name + fresh KV ------
+podman run -d --name "$SCRATCH" \
+  --network host \
+  --init \
+  --security-opt seccomp=unconfined \
+  --ulimit memlock=-1:-1 \
+  --device /dev/kfd --device /dev/dri \
+  -v "$FRANK_ARCHON_MODEL_DIR":/models:ro \
+  -v "$FRANK_ARCHON_STATE_DIR":/data \
+  -v "$FRANK_ARCHON_STATE_DIR/tune":/opt/radiance/share/radiance/tune \
+  -v "$FRANK_ARCHON_TEMPLATE":/templates/template.jinja:ro \
+  "$FRANK_ARCHON_IMAGE" \
+  --model "/models/$FRANK_ARCHON_MODEL_FILE" \
+  --host :: --port "$PORT" \
+  --served-model-name "$FRANK_ARCHON_SERVED_NAME" \
+  --override-chat-template /templates/template.jinja \
+  --tp "$FRANK_ARCHON_TP" --tp-wire "$FRANK_ARCHON_TP_WIRE" \
+  --max-num-seqs "$FRANK_ARCHON_MAX_SEQS" \
+  --max-model-len "$FRANK_ARCHON_MAX_MODEL_LEN" \
+  --placement "$FRANK_ARCHON_PLACEMENT" \
+  --host-pool-mib "$FRANK_ARCHON_HOST_POOL_MIB" \
+  --gpu-headroom-mib "$FRANK_ARCHON_GPU_HEADROOM_MIB" \
+  --vram-weights-mib "$FRANK_ARCHON_VRAM_WEIGHTS_MIB" \
+  --vram-kv-mib "$FRANK_ARCHON_VRAM_KV_MIB" \
+  --kv-cache-dtype "$FRANK_ARCHON_KV_DTYPE" \
+  --prefix-cache-host-mib "$FRANK_ARCHON_PREFIX_HOST_MIB" \
+  --prefix-cache-dir "/data/kvcache/$SCRATCH" \
+  --prefix-cache-disk-mib "$FRANK_ARCHON_PREFIX_DISK_MIB" \
+  --ngram-placement "$FRANK_ARCHON_NGRAM_PLACEMENT" \
+  --num-speculative-tokens "$FRANK_ARCHON_SPEC_TOKENS" \
+  --max-num-batched-tokens "$FRANK_ARCHON_MAX_BATCHED_TOKENS" \
+  ${FRANK_ARCHON_EXTRA_ARGS:+$FRANK_ARCHON_EXTRA_ARGS} \
+  > "$LOG" 2>&1
+if [ $? -ne 0 ]; then echo "scratch boot failed; see $LOG" >&2; exit 1; fi
+
+# --- poll health (listener binds after the full load; cold boot ~110 s) ------
+ok=0
+for _ in $(seq 1 360); do
+  code=$(curl -s -o /dev/null -w "%{http_code}" --max-time 3 "$HEALTH" 2>/dev/null || echo 000)
+  if [ "$code" = "200" ]; then ok=1; break; fi
+  sleep 2
+done
+if [ "$ok" -ne 1 ]; then
+  echo "scratch never reached health 200; tail of $LOG:" >&2
+  tail -30 "$LOG" >&2; exit 1
+fi
+
+# --- build the workload: a fixed ~140k-char real-text prompt (repo corpus) ---
+python3 - "$BODY" <<'PY'
+import json, sys, random, glob
+random.seed(1234)
+root = "/home/dank/serverAppConfigs"
+files = sorted(
+    glob.glob(f"{root}/serverAppConfigs-docs/**/*.md", recursive=True)
+    + glob.glob(f"{root}/scripts/*.sh")
+    + glob.glob(f"{root}/scripts/*.py")
+    + glob.glob(f"{root}/AGENTS.md")
+)
+corpus = []
+total = 0
+for f in files:
+    try:
+        t = open(f, encoding="utf-8", errors="ignore").read()
+    except Exception:
+        continue
+    if not t.strip():
+        continue
+    corpus.append(t)
+    total += len(t)
+    if total > 240000:
+        break
+corpus = "\n".join(corpus)
+TGT = 140000
+parts, n = [], 0
+while n < TGT:
+    start = random.randint(0, max(0, len(corpus) - 500))
+    seg = corpus[start:start + random.randint(200, 500)]
+    parts.append(seg)
+    n += len(seg) + 1
+prompt = " ".join(parts)
+json.dump(
+    {"model": "frank-archon", "prompt": prompt,
+     "max_tokens": 256, "temperature": 0.0, "stream": False,
+     "stop": ["<|im_end|>"]},
+    open(sys.argv[1], "w"),
+)
+PY
+if [ ! -f "$BODY" ]; then echo "prompt build failed" >&2; exit 1; fi
+
+# --- the bench request (prefill ~32k + decode 256, greedy) -------------------
+RESP=$(curl -s --max-time 600 -X POST "$COMPLETE" \
+  -H 'Content-Type: application/json' -d "@$BODY")
+echo "$RESP" > /tmp/arbench-resp.json
+
+# --- parse the timings into METRIC lines -------------------------------------
+python3 - <<'PY'
+import json, sys
+try:
+    r = json.load(open("/tmp/arbench-resp.json"))
+except Exception as e:
+    sys.stderr.write(f"unparseable response: {e}\n"); sys.exit(1)
+if "timings" not in r:
+    sys.stderr.write(f"no timings in response: {json.dumps(r)[:500]}\n"); sys.exit(1)
+t = r["timings"]
+dtps = t.get("predicted_per_second")
+ptps = t.get("prompt_per_second")
+pms  = t.get("prompt_ms")
+dn   = t.get("draft_n", 0)
+da   = t.get("draft_n_accepted", 0)
+if dtps is None:
+    sys.stderr.write("predicted_per_second null (no decode produced)\n"); sys.exit(1)
+print(f"METRIC decode_tps={dtps:.4f}")
+if ptps is not None:
+    print(f"METRIC prefill_tps={ptps:.4f}")
+if pms is not None:
+    print(f"METRIC ttft_ms={pms:.4f}")
+if dn:
+    print(f"METRIC draft_accept={da/dn:.4f}")
+print(f"INFO prompt_n={t.get('prompt_n')} cache_n={t.get('cache_n')} predicted_n={t.get('predicted_n')}")
+PY

scripts/autoresearch/frank-archon-arms.sh

@@ -1,19 +1,19 @@
 #!/usr/bin/env bash
-# frank-primary-arms.sh — run a SEQUENCE of frank-primary bench arms and keep
+# frank-archon-arms.sh — run a SEQUENCE of frank-archon bench arms and keep
 # every arm's evidence. Runs on the operator box; each arm is one full window
 # of ./autoresearch.sh (stop+mask -> boot the arm as the service -> measure ->
 # restore production and verify), so the fleet is only ever down for one arm at
 # a time and the production unit is back up between arms.
 #
-# An arm is the repo's own frank-primary.env plus an OVERLAY of engine knobs
+# An arm is the repo's own frank-archon.env plus an OVERLAY of engine knobs
 # appended after it (later assignment wins when the serve script sources it),
-# staged through FRANK_PRIMARY_AR_ENV_FILE so the checkout is never mutated and
+# staged through FRANK_ARCHON_AR_ENV_FILE so the checkout is never mutated and
 # each arm gets its own fingerprint (the memo can never answer one arm with
 # another arm's numbers).
 #
-# Usage:  scripts/autoresearch/frank-primary-arms.sh [arm ...]
-#         scripts/autoresearch/frank-primary-arms.sh --list
-# Output, under /tmp/frank-primary-arms-<UTC stamp>/ (override with ARMS_DIR):
+# Usage:  scripts/autoresearch/frank-archon-arms.sh [arm ...]
+#         scripts/autoresearch/frank-archon-arms.sh --list
+# Output, under /tmp/frank-archon-arms-<UTC stamp>/ (override with ARMS_DIR):
 #
 #   <arm>.out        full autoresearch output (metrics + engine evidence)
 #   <arm>.env        the exact staged env
@@ -26,8 +26,8 @@ set -uo pipefail
 
 SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)"
 REPO="$(cd -- "$SCRIPT_DIR/../.." && pwd)"
-BASE_ENV="$REPO/scripts/frank-primary.env"
-ARMS_DIR="${ARMS_DIR:-/tmp/frank-primary-arms-$(date -u +%Y%m%dT%H%M%SZ)}"
+BASE_ENV="$REPO/scripts/frank-archon.env"
+ARMS_DIR="${ARMS_DIR:-/tmp/frank-archon-arms-$(date -u +%Y%m%dT%H%M%SZ)}"
 
 # --- arms ------------------------------------------------------------------
 # baseline: the shipped shape E, measured with THIS harness so the comparison is
@@ -45,18 +45,18 @@ LADDER3='{"cudagraph_capture_sizes":[4,8,12],"max_cudagraph_capture_size":12,"in
 # the engine as {temperature:0.7}.
 GEN07='{"temperature":0.7}'
 OVER_B=(
-    "FRANK_PRIMARY_SPEC='$SPEC3'"
-    "FRANK_PRIMARY_COMPCONFIG='$LADDER3'"
-    'FRANK_PRIMARY_GEN_CONFIG='"'$GEN07'"
+    "FRANK_ARCHON_SPEC='$SPEC3'"
+    "FRANK_ARCHON_COMPCONFIG='$LADDER3'"
+    'FRANK_ARCHON_GEN_CONFIG='"'$GEN07'"
 )
 # B2: identical to B with the default (7.60 GiB) overhead, i.e. precise memory
 # OFF. It is the fallback if B dies at graph capture, and it prices the arena
 # that precise memory buys (7,522 slots -> ~6,496).
 OVER_B2=(
-    "FRANK_PRIMARY_SPEC='$SPEC3'"
-    "FRANK_PRIMARY_COMPCONFIG='$LADDER3'"
-    'FRANK_PRIMARY_GEN_CONFIG='"'$GEN07'"
-    'FRANK_PRIMARY_PRECISE_MEMORY='
+    "FRANK_ARCHON_SPEC='$SPEC3'"
+    "FRANK_ARCHON_COMPCONFIG='$LADDER3'"
+    'FRANK_ARCHON_GEN_CONFIG='"'$GEN07'"
+    'FRANK_ARCHON_PRECISE_MEMORY='
 )
 # C: the vendor's concurrency shape — SEQS 16 with the [4..32] ladder and util
 # 0.95. This is also the direct test of the theory that pinning the capture
@@ -64,12 +64,12 @@ OVER_B2=(
 # the constant 3, which is NOT in the default ladder; 4 is).
 LADDER16='{"cudagraph_capture_sizes":[4,8,12,16,20,24,28,32],"max_cudagraph_capture_size":32,"inductor_compile_config":{"combo_kernels":false,"benchmark_combo_kernel":false}}'
 OVER_C=(
-    "FRANK_PRIMARY_SPEC='$SPEC3'"
-    "FRANK_PRIMARY_COMPCONFIG='$LADDER16'"
-    'FRANK_PRIMARY_GEN_CONFIG='"'$GEN07'"
-    'FRANK_PRIMARY_SEQS=16'
-    'FRANK_PRIMARY_MNBT=4096'
-    'FRANK_PRIMARY_UTIL=0.95'
+    "FRANK_ARCHON_SPEC='$SPEC3'"
+    "FRANK_ARCHON_COMPCONFIG='$LADDER16'"
+    'FRANK_ARCHON_GEN_CONFIG='"'$GEN07'"
+    'FRANK_ARCHON_SEQS=16'
+    'FRANK_ARCHON_MNBT=4096'
+    'FRANK_ARCHON_UTIL=0.95'
 )
 
 # D/E: the CONTEXT arms. Measured 2026-10-02 (arms run 20261002T233855Z): the
@@ -83,11 +83,11 @@ OVER_C=(
 # D is arm B with EXACTLY ONE variable changed (the KV bytes), so its result
 # says whether the 4k-depth collapse (B 23.09 vs baseline 33.99) was KV or the
 # batch shape.
-KV401K='FRANK_PRIMARY_KV_BYTES=4050000000'
+KV401K='FRANK_ARCHON_KV_BYTES=4050000000'
 OVER_D=(
-    "FRANK_PRIMARY_SPEC='$SPEC3'"
-    "FRANK_PRIMARY_COMPCONFIG='$LADDER3'"
-    'FRANK_PRIMARY_GEN_CONFIG='"'$GEN07'"
+    "FRANK_ARCHON_SPEC='$SPEC3'"
+    "FRANK_ARCHON_COMPCONFIG='$LADDER3'"
+    'FRANK_ARCHON_GEN_CONFIG='"'$GEN07'"
     "$KV401K"
 )
 # E: D with C's max_num_batched_tokens (4096 — C is the only arm that did NOT
@@ -97,12 +97,12 @@ OVER_D=(
 # only 0.32 GiB above the allowance while the CUDA-graph cost is an ANALYTIC
 # estimate (C's was 1.47 GiB over 24 graphs), so it is measured, not assumed.
 OVER_E=(
-    "FRANK_PRIMARY_SPEC='$SPEC3'"
-    "FRANK_PRIMARY_COMPCONFIG='$LADDER3'"
-    'FRANK_PRIMARY_GEN_CONFIG='"'$GEN07'"
+    "FRANK_ARCHON_SPEC='$SPEC3'"
+    "FRANK_ARCHON_COMPCONFIG='$LADDER3'"
+    'FRANK_ARCHON_GEN_CONFIG='"'$GEN07'"
     "$KV401K"
-    'FRANK_PRIMARY_MNBT=4096'
-    'FRANK_PRIMARY_UTIL=0.99'
+    'FRANK_ARCHON_MNBT=4096'
+    'FRANK_ARCHON_UTIL=0.99'
 )
 
 arm_overlay() {
@@ -142,7 +142,7 @@ for arm in "${ARMS[@]}"; do
     # holds JSON must still be one valid JSON object after the file is SOURCED
     # (that is the step that silently eats unquoted braces).
     if ! bash -c 'set -a; . "$1" >/dev/null; set +a
-        for k in FRANK_PRIMARY_SPEC FRANK_PRIMARY_COMPCONFIG FRANK_PRIMARY_GEN_CONFIG; do
+        for k in FRANK_ARCHON_SPEC FRANK_ARCHON_COMPCONFIG FRANK_ARCHON_GEN_CONFIG; do
             v="${!k:-}"
             [ -n "$v" ] || continue
             case "$v" in
@@ -158,7 +158,7 @@ for arm in "${ARMS[@]}"; do
     fi
 
     echo "[arms] === $arm: opening window $(date -u +%H:%M:%S)Z ===" >&2
-    FRANK_PRIMARY_AR_ENV_FILE="$ARMS_DIR/$arm.env" \
+    FRANK_ARCHON_AR_ENV_FILE="$ARMS_DIR/$arm.env" \
         "$REPO/autoresearch.sh" >"$ARMS_DIR/$arm.out" 2>&1
     rc=$?
     echo "$rc" >"$ARMS_DIR/$arm.rc"

scripts/autoresearch/frank-archon-measure.py

@@ -1,5 +1,5 @@
 #!/usr/bin/env python3
-"""frank-primary decode measurement — runs INSIDE the engine container.
+"""frank-archon decode measurement — runs INSIDE the engine container.
 
 The method is the fleet's established one (the 2026-09-29 / 2026-10-01
 tuning campaigns, /home/dank/mtp_measure.py): SSE chunk counting is invalid
@@ -28,7 +28,7 @@ Workload (fixed, deterministic, offline):
 
 Env:
   AR_BASE             endpoint (default http://127.0.0.1:7770)
-  AR_MODEL            served name (default frank-primary)
+  AR_MODEL            served name (default frank-archon)
   AR_PROMPT_CEILING   hard prompt ceiling in tokens (default 100000)
   AR_TEMPS            comma-separated sampling temperatures (default "0,0.7")
 
@@ -45,7 +45,7 @@ import urllib.error
 import urllib.request
 
 BASE = os.environ.get("AR_BASE", "http://127.0.0.1:7770")
-MODEL = os.environ.get("AR_MODEL", "frank-primary")
+MODEL = os.environ.get("AR_MODEL", "frank-archon")
 PROMPT_CEILING = int(os.environ.get("AR_PROMPT_CEILING", "100000"))
 DEPTHS = (115, 1056, 4096)
 WARM_TOKENS = 64

scripts/autoresearch/frank-archon-window.sh

@@ -1,5 +1,5 @@
 #!/usr/bin/env bash
-# frank-primary-window.sh — one full bench window for frank-primary, run ON
+# frank-archon-window.sh — one full bench window for frank-archon, run ON
 # DANKSERVER as the deploy user (invoked over ssh by ./autoresearch.sh).
 #
 # Discipline (AGENTS.md Benchmarking Policy): the production unit is
@@ -12,9 +12,9 @@
 #
 # Staging layout (created by the orchestrator, ephemeral — never a config
 # source; the repo checkout is):
-#   /home/dank/.autoresearch-frank-primary/
+#   /home/dank/.autoresearch-frank-archon/
 #     serve.sh             staged candidate serve script
-#     frank-primary.env    staged candidate env (the candidate knobs)
+#     frank-archon.env    staged candidate env (the candidate knobs)
 #     measure.py           the in-container measure client
 #     hash                 candidate fingerprint
 #     run.json             result (metrics + boot + kv + fingerprint)
@@ -27,16 +27,16 @@
 # outcome; a failed restore forces exit 1).
 set -uo pipefail
 
-STAGE="${FRANK_PRIMARY_AR_STAGE:-/home/dank/.autoresearch-frank-primary}"
-UNIT="${FRANK_PRIMARY_AR_UNIT:-frank-primary}"
-CTR="${FRANK_PRIMARY_AR_CTR:-frank-primary-qwen}"
+STAGE="${FRANK_ARCHON_AR_STAGE:-/home/dank/.autoresearch-frank-archon}"
+UNIT="${FRANK_ARCHON_AR_UNIT:-frank-archon}"
+CTR="${FRANK_ARCHON_AR_CTR:-frank-archon-qwen}"
 HEALTH_URL="http://127.0.0.1:7770/health"
 MODELS_URL="http://127.0.0.1:7770/v1/models"
-BOOT_TIMEOUT="${FRANK_PRIMARY_AR_BOOT_TIMEOUT:-1200}"
-RESTORE_TIMEOUT="${FRANK_PRIMARY_AR_RESTORE_TIMEOUT:-1200}"
-MEASURE_TIMEOUT="${FRANK_PRIMARY_AR_MEASURE_TIMEOUT:-1800}"
-SERVED="$(sed -n 's/^FRANK_PRIMARY_SERVED_NAME=//p' "$STAGE/frank-primary.env" 2>/dev/null | head -1)"
-SERVED="${SERVED:-frank-primary}"
+BOOT_TIMEOUT="${FRANK_ARCHON_AR_BOOT_TIMEOUT:-1200}"
+RESTORE_TIMEOUT="${FRANK_ARCHON_AR_RESTORE_TIMEOUT:-1200}"
+MEASURE_TIMEOUT="${FRANK_ARCHON_AR_MEASURE_TIMEOUT:-1800}"
+SERVED="$(sed -n 's/^FRANK_ARCHON_SERVED_NAME=//p' "$STAGE/frank-archon.env" 2>/dev/null | head -1)"
+SERVED="${SERVED:-frank-archon}"
 
 RESTORED=0
 
@@ -72,7 +72,7 @@ capture_bench_failure() {
         echo "=== staged serve.out (tail 60) ==="
         tail -60 "$STAGE/serve.out" 2>/dev/null || true
         echo "=== engine log (tail 60) ==="
-        tail -60 /home/dank/logs/frank_primary.log 2>/dev/null || true
+        tail -60 /home/dank/logs/frank_archon.log 2>/dev/null || true
     } >"$STAGE/fail.log" 2>&1 || true
     grep -E 'OutOfMemory|Tried to allocate|Engine core initialization failed|Error|error' \
         "$STAGE/fail.log" 2>/dev/null | tail -25 >&2 || true
@@ -114,7 +114,7 @@ trap 'restore; rc=$?; [ "$rc" -ne 0 ] && exit 1' EXIT
 
 main() {
     local f
-    for f in serve.sh frank-primary.env measure.py hash; do
+    for f in serve.sh frank-archon.env measure.py hash; do
         [ -f "$STAGE/$f" ] || { log "staged file missing: $STAGE/$f"; exit 1; }
     done
     mkdir -p "$STAGE/last"
@@ -133,7 +133,7 @@ main() {
 
     t0="$(date +%s)"
     log "starting bench instance from staged config (fingerprint $(tr -d '[:space:]' <"$STAGE/hash"))"
-    FRANK_PRIMARY_ENV_FILE="$STAGE/frank-primary.env" \
+    FRANK_ARCHON_ENV_FILE="$STAGE/frank-archon.env" \
         setsid nohup bash "$STAGE/serve.sh" >"$STAGE/serve.out" 2>&1 </dev/null &
     echo "$!" >"$STAGE/serve.pid"
 

scripts/bench-decode.sh

@@ -1,5 +1,5 @@
 #!/usr/bin/env bash
-# Decode throughput benchmark for frank-large.
+# Decode throughput benchmark for frank-dragoon.
 # Measures generation tok/s with 8K+ token prompts and 256 generated tokens.
 set -euo pipefail
 
@@ -57,7 +57,7 @@ run_bench() {
     # Warmup (small request)
     curl -s -m 60 http://127.0.0.1:$PORT/v1/chat/completions \
         -H "Content-Type: application/json" \
-        -d '{"model":"frank-large","messages":[{"role":"user","content":"Hi"}],"max_tokens":16,"stream":false}' > /dev/null 2>&1 || true
+        -d '{"model":"frank-dragoon","messages":[{"role":"user","content":"Hi"}],"max_tokens":16,"stream":false}' > /dev/null 2>&1 || true
     
     # Build 8K prompt
     local prompt
@@ -75,7 +75,7 @@ print(json.dumps(' '.join(words)))
     t0=$(date +%s%N)
     resp=$(curl -s -m 600 http://127.0.0.1:$PORT/v1/chat/completions \
         -H "Content-Type: application/json" \
-        -d "{\"model\":\"frank-large\",\"messages\":[{\"role\":\"user\",\"content\":$prompt}],\"max_tokens\":$N_GEN,\"stream\":false}" 2>&1)
+        -d "{\"model\":\"frank-dragoon\",\"messages\":[{\"role\":\"user\",\"content\":$prompt}],\"max_tokens\":$N_GEN,\"stream\":false}" 2>&1)
     t1=$(date +%s%N)
     
     if ! echo "$resp" | python3 -c "import sys,json; json.load(sys.stdin)" 2>/dev/null; then

scripts/bench-probe.py

@@ -0,0 +1,48 @@
+#!/usr/bin/env python3
+"""bench-probe.py — RUNS ON DANKSERVER. The campaign's decode probe: one
+/completion request, a prompt assembled from calib.jsonl to ~TARGET tokens,
+temperature 0, max_tokens 512. Reports the engine's own timings: decode rate,
+prefill rate, draft accept. Run 3x; the median is the arm's number."""
+import json, sys, urllib.request
+
+TARGET = 43600  # tokens
+BYTES_PER_TOK = 3.8
+URL = "http://localhost:7770/v1/completions"
+
+def build_prompt():
+    want = int(TARGET * BYTES_PER_TOK)
+    parts = []
+    n = 0
+    with open("/home/dank/corpora/out/calib.jsonl") as f:
+        for line in f:
+            d = json.loads(line)
+            p = d.get("prompt") or d.get("messages", [{}])[0].get("content", "")
+            parts.append(p)
+            n += len(p.encode())
+            if n >= want:
+                break
+    return "".join(parts)
+
+def probe(salt):
+    prompt = f"[probe {salt}]\n" + build_prompt()
+    body = json.dumps({
+        "model": "frank-archon",
+        "prompt": prompt, "temperature": 0.0, "max_tokens": 512,
+    }).encode()
+    req = urllib.request.Request(URL, data=body,
+        headers={"Content-Type": "application/json"})
+    with urllib.request.urlopen(req, timeout=1800) as r:
+        d = json.load(r)
+    t = d.get("timings", {})
+    return {
+        "prompt_n": t.get("prompt_n"),
+        "prefill_tps": round(t.get("prompt_per_second", 0), 1),
+        "pred_n": t.get("predicted_n"),
+        "decode_tps": round(t.get("predicted_per_second", 0), 2),
+        "draft_n": t.get("draft_n"),
+        "accept": (round(t["draft_n_accepted"] / t["draft_n"], 4)
+                   if t.get("draft_n") else None),
+    }
+
+if __name__ == "__main__":
+    print(json.dumps(probe(sys.argv[1] if len(sys.argv) > 1 else "a")))

scripts/bench-threads-batch-http.py

@@ -1,6 +1,6 @@
 #!/usr/bin/env python3
 """
-HTTP-based prefill-throughput sweep for frank-large.
+HTTP-based prefill-throughput sweep for frank-dragoon.
 Starts the server with a given --threads-batch value, sends a 64K-prompt via
 the chat API (max_tokens=0), measures prompt_tokens/wall_time.
 
@@ -39,7 +39,7 @@ def send_prefill_request():
     with open(PROMPT_FILE, "r") as f:
         prompt = f.read()
     body = json.dumps({
-        "model": "frank-large",
+        "model": "frank-dragoon",
         "messages": [{"role": "user", "content": prompt}],
         "max_tokens": 1,
         "stream": False

scripts/bench-threads-batch.sh

@@ -1,5 +1,5 @@
 #!/usr/bin/env bash
-# Threads-batch sweep for frank-large on dankclaw
+# Threads-batch sweep for frank-dragoon on dankclaw
 # Benches prefill throughput at 65536 prompt tokens across threads-batch values.
 set -uo pipefail
 
@@ -10,7 +10,7 @@ TB_LIST=(16 32 48 64 80 96 128)
 ENV_FILE="/home/dank/GitPackages/ROCmFPX/build-qwen38/bin"
 
 echo "========================================"
-echo "THREADS-BATCH SWEEP — frank-large"
+echo "THREADS-BATCH SWEEP — frank-dragoon"
 echo "Model: $(basename "$MODEL") ($(du -h "$MODEL" | cut -f1))"
 echo "Threads-batch values: ${TB_LIST[*]}"
 echo "Prompt: 65536 tokens, n-gen: 0 (prefill-only)"

scripts/bench-ubatch.sh

@@ -1,14 +1,14 @@
 #!/usr/bin/env bash
-# Benchmark ubatch with llama-bench for frank-large.
+# Benchmark ubatch with llama-bench for frank-dragoon.
 #
 # This is intentionally a ubatch-only benchmark. It uses one llama-bench
 # process, an 8K prompt workload, and equal batch/ubatch values. No server
 # process, HTTP requests, or log scraping are used.
 #
-# Run on Dankclaw after stopping frank-large:
-#   sudo systemctl stop frank-large
+# Run on Dankclaw after stopping frank-dragoon:
+#   sudo systemctl stop frank-dragoon
 #   ./scripts/bench-ubatch.sh
-#   sudo systemctl start frank-large
+#   sudo systemctl start frank-dragoon
 set -euo pipefail
 
 : "${LLAMA_BENCH:=/home/dank/GitPackages/ROCmFPX/build-strix-rocmfp4/bin/llama-bench}"

scripts/build-frank-archon-rad.sh

@@ -0,0 +1,166 @@
+#!/usr/bin/env bash
+# build-frank-archon-rad.sh — build frank-archon's .rad container from the
+# OFFICIAL Qwen/Qwen3.8-Flash-Next-FP8 checkpoint, at NATIVE precision.
+#
+#   bash scripts/build-frank-archon-rad.sh                # convert
+#   bash scripts/build-frank-archon-rad.sh --plan-only    # declare, no I/O
+#   bash scripts/build-frank-archon-rad.sh --restage      # redo staging
+#   bash scripts/build-frank-archon-rad.sh --force        # rebuild existing
+#
+# WHY A STAGING DIR (the one non-obvious step): rad-convert selects its
+# architecture plugin by the checkpoint's quantisation DESCRIPTOR —
+# derived from config.json's quantization_config (core/format/checkpoint.cpp:
+# "fp8" here). No shipped plugin claims (qwen4exp, "fp8"): the shipped
+# qwen4exp plugin claims (qwen4exp, ""), the descriptor recipe-built
+# containers carry (they are built from the bf16 upstream, which has no
+# quantization_config at all). The match is exact with no fallback, so an
+# unmodified convert refuses before declare. The descriptor is only a
+# selection key; per-weight encodings are data — the checkpoint reader
+# derives them from the tensors themselves (X.weight_scale_inv is the
+# scale plane; checkpoint.h). Staging drops the quantization_config key
+# (everything else is a relative symlink into the pristine download) so
+# the convert selects the shipped plugin. EVERY weight is then copied through
+# in its own encoding — block-FP8 codes + bf16 scale planes stay block-FP8 —
+# except TWO value-preserving reshapes that stack-qwen38-official-fp8.py
+# performs on the staging dir first, and ONE recipe rule that finishes the
+# PLE table:
+#   * experts: the plugin maps the STACKED layout (mlp.experts.gate_up_proj
+#     [E,2F,H] with the _scale_inv plane at the same index) while the official
+#     repo ships per-expert unfused tensors — staging byte-stacks them
+#     (gate rows first, no requantisation).
+#   * PLE: the plugin's fp8 branch wants the table codes beside a ONE-ELEMENT
+#     bf16 scale plane; the official repo ships 128 SCALELESS fp8 shards plus
+#     one bf16 scalar. Staging decodes to bf16 with the checkpoint's own
+#     scale, and the convert's rtn rule re-encodes at that same scale —
+#     every original code is restored exactly and the scale plane lands in
+#     the form the plugin declares.
+#
+# WHY A CONTAINER AT ALL: a checkpoint dir has no mapped/file tiers, and a
+# weight only a host kernel reads (the n-gram / PLE table, 51B params)
+# cannot be served from one (GUIDE §3.4). rad-convert also bakes the
+# tokenizer and the checkpoint's chat template; the runtime replaces the
+# template with froggeric's (--override-chat-template).
+#
+# The convert runs rad-convert inside the digest-pinned radiance image
+# (the host has no ROCm and needs none): /home/dank/models is mounted at
+# /models so the staging dir's RELATIVE symlinks resolve inside the
+# container. Output lands beside the raw download, owned by dank
+# (rootless podman maps container-root to the invoking user).
+set -euo pipefail
+
+SRC="/home/dank/models/Qwen/Qwen3.8-Flash-Next-FP8"
+STAGE="/home/dank/models/stage-qwen4exp-fp8"
+OUT_DIR="/home/dank/models/rad"
+OUT="$OUT_DIR/qwen4exp-fp8-native.rad"
+
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+# shellcheck disable=SC1091
+source "$SCRIPT_DIR/frank-archon.env"
+IMAGE="$FRANK_ARCHON_IMAGE"
+
+plan_only=0 restage=0 force=0
+for a in "$@"; do
+    case "$a" in
+        --plan-only) plan_only=1 ;;
+        --restage)   restage=1 ;;
+        --force)     force=1 ;;
+        *) echo "unknown flag: $a" >&2; exit 2 ;;
+    esac
+done
+
+if [ ! -f "$SRC/config.json" ]; then
+    echo "ERROR: raw checkpoint missing: $SRC (run scripts/download-frank-archon.sh --fetch)" >&2
+    exit 1
+fi
+echo "verifying raw checkpoint first..."
+bash "$SCRIPT_DIR/download-frank-archon.sh"
+
+if [ -f "$OUT" ] && [ "$plan_only" -eq 0 ] && [ "$force" -eq 0 ]; then
+    echo "container already exists: $OUT"
+    echo "rebuild it with --force (the old file moves to ~/.AGENTTRASH)"
+    exit 0
+fi
+
+# ---- staging ----------------------------------------------------------------
+if [ "$restage" -eq 1 ] && [ -e "$STAGE" ]; then
+    TRASH="$HOME/.AGENTTRASH/$(date +%Y%m%d)-frank-archon-stage"
+    mkdir -p "$TRASH"
+    mv "$STAGE" "$TRASH/stage-$(date +%H%M%S)"
+    echo "old staging dir moved to $TRASH"
+fi
+if [ ! -f "$STAGE/config.json" ]; then
+    mkdir -p "$STAGE"
+    python3 - "$SRC/config.json" "$STAGE/config.json" <<'PY'
+import json, sys
+src, dst = sys.argv[1], sys.argv[2]
+cfg = json.load(open(src))
+dropped = cfg.pop("quantization_config", None)
+json.dump(cfg, open(dst, "w"), indent=2)
+print(f"staging config.json written (quantization_config dropped: {dropped is not None})")
+PY
+    # The index is COPIED like config.json, never symlinked: the reshape step
+    # rewrites the stage's index, and a symlink would write through to the
+    # raw checkpoint (measured 2026-10-05: the raw index was restamped with
+    # the stacked layout and the raw verify failed 143/144). Shards stay
+    # relative symlinks — relative so the targets resolve inside the convert
+    # container (the stage's parent is mounted at /models).
+    for f in "$SRC"/*; do
+        name="$(basename "$f")"
+        case "$name" in config.json|model.safetensors.index.json) continue ;; esac
+        ln -sfn "../Qwen/Qwen3.8-Flash-Next-FP8/$name" "$STAGE/$name"
+    done
+    cp "$SRC/model.safetensors.index.json" "$STAGE/"
+    echo "staging dir ready: $STAGE ($(ls "$STAGE" | wc -l) entries)"
+fi
+
+# ---- checkpoint reshape (stacked experts + bf16 PLE table) -------------------
+# stack-qwen38-official-fp8.py reshapes the staged checkpoint in place
+# (idempotent) and writes the PLE scale to $STAGE/ple_scale.txt — see the
+# script's docstring for why each transform is value-preserving.
+echo "stacking experts + merging the PLE table (value-preserving)..."
+python3 "$SCRIPT_DIR/stack-qwen38-official-fp8.py" --stage "$STAGE"
+PLE_SCALE="$(tr -d '\n' < "$STAGE/ple_scale.txt")"
+echo "PLE fixed scale: $PLE_SCALE"
+
+# ---- convert ----------------------------------------------------------------
+# rad-convert needs no GPU: declare resolves kernels and asks each about the
+# encoding it will read — CPU-side layout questions only. (If a plugin load
+# ever demands a card, add --device /dev/kfd --device /dev/dri to this run.)
+# --plan-only runs the same declare phase and exits before a byte is written.
+echo "rad-convert: $SRC (staged) -> $OUT"
+mkdir -p "$OUT_DIR"
+CONVERT_ARGS=(/models/stage-qwen4exp-fp8 -o /models/rad/qwen4exp-fp8-native.rad
+              --home /opt/radiance/share/radiance)
+[ "$plan_only" -eq 1 ] && CONVERT_ARGS+=(--plan-only -v)
+# THE ONE RECIPE RULE (see header): the PLE table arrives from staging as a
+# bf16 merge of the checkpoint's own fp8 codes decoded with the checkpoint's
+# own scale; rtn re-encodes it at that same scale — the codes come back
+# exactly and the plugin's one-element scale plane is produced.
+CONVERT_ARGS+=(--quant "blk.*.ple_ngram.weight=rtn:codes=fp8_e4m3,block=*x*,scale=bf16,rule=fixed,scale_value=$PLE_SCALE")
+[ "$force" -eq 1 ] && [ -f "$OUT" ] && {
+    TRASH="$HOME/.AGENTTRASH/$(date +%Y%m%d)-frank-archon-rad"
+    mkdir -p "$TRASH"
+    mv "$OUT" "$TRASH/qwen4exp-fp8-native.rad.$(date +%H%M%S)"
+    echo "previous container moved to $TRASH"
+}
+podman run --rm \
+    --entrypoint rad-convert \
+    -v /home/dank/models:/models \
+    "$IMAGE" "${CONVERT_ARGS[@]}"
+
+if [ "$plan_only" -eq 1 ]; then
+    echo "plan-only run complete (no container written)"
+    exit 0
+fi
+
+# ---- record -----------------------------------------------------------------
+echo "rad-info summary:"
+podman run --rm --entrypoint rad-info -v /home/dank/models:/models:ro \
+    "$IMAGE" "/models/rad/qwen4exp-fp8-native.rad" | head -20
+MIB=$(( $(stat -c %s "$OUT") / 1048576 ))
+echo "container: $OUT (${MIB} MiB; env floor $FRANK_ARCHON_RAD_MIN_MIB MiB)"
+if [ "$MIB" -lt "$FRANK_ARCHON_RAD_MIN_MIB" ]; then
+    echo "ERROR: container below the env floor — the convert was truncated" >&2
+    exit 1
+fi
+echo "build complete"

scripts/build-gufo.sh

@@ -1,5 +1,5 @@
 #!/usr/bin/env bash
-# Build the gufo runtime that serves frank-large on Dankclaw.
+# Build the gufo runtime that serves frank-dragoon on Dankclaw.
 #
 #   bash scripts/build-gufo.sh              # build + install the pinned tag
 #   bash scripts/build-gufo.sh --verify     # only check the installed tree
@@ -93,4 +93,4 @@ cmake --install build/release
 
 echo "== verify =="
 "$PREFIX/bin/gufo" diagnose
-echo "frank-large runtime ready: $PREFIX/bin/gufo ($GUFO_TAG @ $commit)"
+echo "frank-dragoon runtime ready: $PREFIX/bin/gufo ($GUFO_TAG @ $commit)"

scripts/build-rocmfpx.sh

@@ -1,11 +1,11 @@
 #!/usr/bin/env bash
-# Build the ROCmFPX runtime that serves frank-large on Dankclaw.
+# Build the ROCmFPX runtime that serves frank-dragoon on Dankclaw.
 #
 #   bash scripts/build-rocmfpx.sh              # clone/fetch + build the pin
 #   bash scripts/build-rocmfpx.sh --verify     # only check the installed tree
 #
 # Runtime: kingjones30/ROCmFPX — charlie12345/ROCmFPX plus the model-card
-# patches, i.e. the fork that owns the ROCmFPx tensor formats. frank-large's
+# patches, i.e. the fork that owns the ROCmFPx tensor formats. frank-dragoon's
 # payload is ftype 115 (`Q8_0_ROCMFPX_AGENT`): 311 tensors of
 # GGML_TYPE_Q8_0_ROCMFPX (103), a type that exists ONLY in this fork, so
 # stock llama.cpp, gufo and every other loader on the host reject the file.
@@ -30,7 +30,7 @@
 set -euo pipefail
 
 ROCMFPX_REPO="${ROCMFPX_REPO:-https://github.com/kingjones30/ROCmFPX.git}"
-# The commit frank-large was qualified with (measured 2026-10-02).
+# The commit frank-dragoon was qualified with (measured 2026-10-02).
 ROCMFPX_COMMIT="${ROCMFPX_COMMIT:-36e9acd40e10a87cd3c3ef8ec734668757dc8520}"
 SRC_DIR="${ROCMFPX_SRC_DIR:-/home/dank/GitPackages/kingjones-ROCmFPX}"
 BUILD_DIR="${ROCMFPX_BUILD_DIR:-$SRC_DIR/build}"
@@ -86,4 +86,4 @@ cmake --build "$BUILD_DIR" --target llama-server llama-quantize -j "$JOBS"
 
 echo "== verify =="
 "$BUILD_DIR/bin/llama-server" --version | head -1
-echo "frank-large runtime ready: $BUILD_DIR/bin/llama-server ($ROCMFPX_COMMIT)"
+echo "frank-dragoon runtime ready: $BUILD_DIR/bin/llama-server ($ROCMFPX_COMMIT)"

scripts/calib-push.py

@@ -0,0 +1,110 @@
+#!/usr/bin/env python3
+"""calib-push.py — drive a calibration corpus through a radiance scratch
+server's prefill so its tap writes layer Hessians (docs/MOE-W4.md).
+
+Runs ON DANKSERVER next to the scratch server (the one autoresearch- /
+serve-style scratch container booted with RADIANCE_CALIB_DIR set).
+Reads the corpus JSONL produced by make-calib-corpus.py
+({"prompt": "..."} a line), POSTs each prompt to /v1/completions with
+max_tokens=1 (prefill-only cost, one token out), at N-way concurrency
+matching the scratch server's --max-num-seqs budget.
+
+Corpus rounds repeat until the engine prints the tap's completion line
+("calibration wrote layer Hessians") in `podman logs <container>` — that
+is the ground truth that RADIANCE_CALIB_TOKENS was reached. After that
+line, further prompts are pure waste, so the driver exits.
+
+Mechanics notes:
+- requests carry no sampling params that matter (max_tokens=1, greedy).
+- a per-request timeout of 30 min: at ~1k tok/s prefill a 12k-token
+  prompt is a few seconds; the timeout only catches a wedged engine.
+- failures print and continue: the tap pools over tokens, a few lost
+  prompts do not bias the Hessians (the corpus is drawn round-robin over
+  source classes, so loss is class-neutral as long as failures are rare;
+  a systematic 4xx is loud in the log and must be fixed, not ignored).
+
+Usage: calib-push.py [--port 7770] [--parallel 64] [--container arbench]
+       [--corpus /home/dank/corpora/out/calib.jsonl] [--max-rounds 4]
+"""
+import argparse
+import concurrent.futures
+import json
+import subprocess
+import sys
+import time
+import urllib.request
+
+DONE_MARK = "calibration wrote"
+
+
+def tap_done(container):
+    """True if the engine logged the tap's completion line."""
+    try:
+        out = subprocess.run(
+            ["podman", "logs", "--tail", "50", container],
+            capture_output=True, text=True, timeout=30,
+        )
+    except Exception:
+        return False
+    return DONE_MARK in (out.stdout + out.stderr)
+
+
+def push_one(url, prompt):
+    body = json.dumps({
+        "model": "frank-archon",
+        "prompt": prompt,
+        "max_tokens": 1,
+        "temperature": 0,
+        "stream": False,
+    }).encode()
+    req = urllib.request.Request(
+        url, data=body, headers={"Content-Type": "application/json"})
+    try:
+        with urllib.request.urlopen(req, timeout=1800) as r:
+            r.read()
+        return True
+    except Exception as e:
+        print(f"FAIL {str(e)[:120]}", flush=True)
+        return False
+
+
+def main():
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--port", type=int, default=7770)
+    ap.add_argument("--parallel", type=int, default=64)
+    ap.add_argument("--container", default="arbench")
+    ap.add_argument("--corpus", default="/home/dank/corpora/out/calib.jsonl")
+    ap.add_argument("--max-rounds", type=int, default=4)
+    a = ap.parse_args()
+    url = f"http://127.0.0.1:{a.port}/v1/completions"
+
+    prompts = []
+    with open(a.corpus) as f:
+        for line in f:
+            line = line.strip()
+            if line:
+                prompts.append(json.loads(line)["prompt"])
+    print(f"corpus: {len(prompts)} prompts", flush=True)
+
+    for rnd in range(1, a.max_rounds + 1):
+        if tap_done(a.container):
+            break
+        t0 = time.time()
+        ok = 0
+        with concurrent.futures.ThreadPoolExecutor(a.parallel) as ex:
+            for good in ex.map(lambda p: push_one(url, p), prompts):
+                ok += 1 if good else 0
+        dt = time.time() - t0
+        print(f"round {rnd}: {ok}/{len(prompts)} ok in {dt:.0f}s "
+              f"({sum(len(p) for p in prompts)/4/dt:.0f} chars/s est)",
+              flush=True)
+        if tap_done(a.container):
+            break
+    else:
+        print("max rounds exhausted, tap not done", flush=True)
+        sys.exit(1)
+    print("TAP_DONE: calibration wrote layer Hessians", flush=True)
+
+
+if __name__ == "__main__":
+    main()

scripts/convert-swift15-w4dn8.sh

@@ -0,0 +1,73 @@
+#!/usr/bin/env bash
+# convert-swift15-w4dn8.sh — RUNS ON DANKSERVER. The final recipe convert of
+# the Swift 1.5 checkpoint: gate_up experts through GPTQ against the 10M-token
+# calibration Grams, down projections block-fp8, protected experts bf16,
+# trunk int8, PLE fixed-scale fp8 (scripts/recipes/
+# qwen4exp-swift15-w4dn8-i8-hc8m.recipe).
+#
+# The convert engine is 1.0.13 — the SAME pin that will serve the result, so
+# the .rad crosses no version boundary. Only the Gram files cross versions
+# (1.2.0 wrote them; the RADGRAM2 magic, gram.r%d.%s.bin naming and the
+# calib_gram/calib_resolve/calib_stem symbols are byte-identical between the
+# two libquant.so). rad-convert runs on the host backend (no GPU visible in
+# the container) — production can stay up through this script.
+#
+# Prereqs (campaign order): calibration complete (calib-push printed TAP_DONE),
+# the protected-expert cast lines rewritten into the recipe by
+# derive-protected-experts.py, and the 335 GiB bf16 container deleted —
+# the peak-disk arithmetic needs that space (checkpoint 335.3 + output ~132
+# GiB on the volume; --reuse is NOT used, see the recipe header).
+set -euo pipefail
+
+PIN_1013=sha256:4c3f484564bb2872784e46b0a59cbd71becc9c1e746e301a3596ffae253c322e
+IMAGE="stilldeadcode/radiance@$PIN_1013"
+CKPT=/home/dank/models/ukisai/Swift1.5-Qwen3.8-Flash-Next
+RECIPE=/home/dank/serverAppConfigs-swift15/scripts/recipes/qwen4exp-swift15-w4dn8-i8-hc8m.recipe
+CALIB=/home/dank/corpora/calib
+OUT=/home/dank/models/rad/qwen4exp-swift15-w4dn8-i8-hc8m.rad
+LOG=/home/dank/logs/swift15_convert.log
+# gate_up ~37.6 + down ~18.8 + PLE 47.7 + trunk/embeddings/head ~10 GiB (all-w4 expert table;
+# the plugin's one-encoding law dropped the block-fp8 down tier -- see the recipe header).
+MIN_MIB=${FRANK_SWIFT15_RAD_MIN_MIB:-108000}
+
+# Gate 1: inputs. A missing Gram directory converts UNCALIBRATED with a
+# per-tensor stderr note, which is silently worse than failing here.
+[ -d "$CKPT" ] || { echo "no checkpoint at $CKPT" >&2; exit 1; }
+[ -f "$RECIPE" ] || { echo "no recipe at $RECIPE" >&2; exit 1; }
+GRAMS=$(find "$CALIB" -maxdepth 1 -name 'gram.r*.bin' 2>/dev/null | wc -l)
+[ "$GRAMS" -ge 48 ] || { echo "calib dir $CALIB holds $GRAMS gram files (<48)" >&2; exit 1; }
+if [ -e "$OUT" ]; then echo "$OUT already exists; move it to trash first" >&2; exit 1; fi
+if [ -e /home/dank/models/rad/qwen4exp-swift15-bf16.rad ]; then
+    echo "the bf16 container is still on disk; delete it first (peak disk)" >&2; exit 1
+fi
+
+# Gate 2: disk. Output ~132 GiB plus convert staging, 20 GiB of slack.
+FREE_MIB=$(df --output=avail -m /home/dank/models | tail -1 | tr -d ' ')
+[ "$FREE_MIB" -ge $((MIN_MIB + 20480)) ] || {
+    echo "only ${FREE_MIB} MiB free on /home/dank/models" >&2; exit 1; }
+
+# The recipe names $CALIB; rad-convert expands it from the environment
+# (MOE-W4.md:275). The recipe's cast section must name THIS checkpoint's
+# protected experts — derive-protected-experts.py rewrote it.
+echo "convert: $CKPT -> $OUT (gptq calib=$CALIB, $(date -Is))" | tee "$LOG"
+podman run --rm --name swift15-convert \
+    -v /home/dank/models:/models \
+    -v /home/dank/serverAppConfigs-swift15:/campaign:ro \
+    -v "$CALIB:/data/calib:ro" \
+    -e CALIB=/data/calib \
+    --entrypoint /opt/radiance/bin/rad-convert \
+    "$IMAGE" "/models/${CKPT#/home/dank/models/}" \
+    --recipe /campaign/"${RECIPE#/home/dank/serverAppConfigs-swift15/}" \
+    -o /models/rad/"$(basename "$OUT")" 2>&1 | tee -a "$LOG"
+rc=${PIPESTATUS[0]}
+[ "$rc" -eq 0 ] || { echo "rad-convert rc=$rc; log: $LOG" >&2; exit "$rc"; }
+
+# Gate 3: the artifact. rad-info's recipe echo is the receipt that GPTQ ran.
+SIZE_MIB=$(( $(stat -c %s "$OUT") / 1048576 ))
+[ "$SIZE_MIB" -ge "$MIN_MIB" ] || {
+    echo "$OUT is ${SIZE_MIB} MiB < floor ${MIN_MIB}" >&2; exit 1; }
+podman run --rm --entrypoint /opt/radiance/bin/rad-info \
+    -v /home/dank/models:/models:ro "$IMAGE" /models/rad/"$(basename "$OUT")" \
+    2>&1 | tee -a "$LOG" | grep -c 'gptq' >/dev/null \
+    || echo "WARNING: rad-info shows no gptq rule in the recorded recipe" >&2
+echo "CONVERT_DONE ${SIZE_MIB} MiB -> $OUT"

scripts/dankstatus.sh

@@ -57,9 +57,9 @@ else
   echo "  none"
 fi
 
-section "frank-primary unit"
-printf '  active:  %s\n' "$(systemctl is-active frank-primary 2>/dev/null | head -1)"
-printf '  enabled: %s\n' "$(systemctl is-enabled frank-primary 2>/dev/null | head -1)"
+section "frank-archon unit"
+printf '  active:  %s\n' "$(systemctl is-active frank-archon 2>/dev/null | head -1)"
+printf '  enabled: %s\n' "$(systemctl is-enabled frank-archon 2>/dev/null | head -1)"
 
 section "glm serve tail"
 if podman ps -a --format '{{.Names}}' 2>/dev/null | grep -qx "$GLM_CTR"; then

scripts/deep-probe.py

@@ -0,0 +1,55 @@
+#!/usr/bin/env python3
+"""deep-probe.py — one chat completion at ~43.6k prompt tokens, temp 0, 512
+generated, streamed; decode = completion_tokens / (total - ttft)."""
+import json, time, urllib.request
+
+TARGET_BYTES = int(43600 * 3.8)
+
+def build():
+    parts, n = [], 0
+    with open("/home/dank/corpora/out/calib.jsonl") as f:
+        for line in f:
+            p = json.loads(line)["prompt"]
+            parts.append(p)
+            n += len(p.encode())
+            if n >= TARGET_BYTES:
+                break
+    return "".join(parts)
+
+def main(salt):
+    body = json.dumps({
+        "model": "frank-archon",
+        "messages": [{"role": "user", "content": f"[probe {salt}] Continue and summarize this material in English, 400 words.\n\n" + build()}],
+        "temperature": 0.0, "max_tokens": 512,
+        "stream": True, "stream_options": {"include_usage": True},
+    }).encode()
+    req = urllib.request.Request("http://localhost:7770/v1/chat/completions",
+        data=body, headers={"Content-Type": "application/json"})
+    t0 = time.time(); ttft = None; ctok = 0; usage = {}
+    with urllib.request.urlopen(req, timeout=2400) as r:
+        for raw in r:
+            line = raw.decode().strip()
+            if not line.startswith("data:"):
+                continue
+            d = line[5:].strip()
+            if d == "[DONE]":
+                break
+            j = json.loads(d)
+            if j.get("usage"):
+                usage = j["usage"]
+            for ch in j.get("choices", []):
+                delta = (ch.get("delta") or {})
+                piece = delta.get("content") or delta.get("reasoning_content") or ""
+                if piece and ttft is None:
+                    ttft = time.time() - t0
+                ctok += 1
+    total = time.time() - t0
+    gen = usage.get("completion_tokens") or ctok
+    dec = gen / (total - (ttft or 0)) if total > (ttft or 0) else 0
+    print(json.dumps({"salt": salt, "prompt_tokens": usage.get("prompt_tokens"),
+                      "completion_tokens": gen, "ttft_s": round(ttft or 0, 2),
+                      "total_s": round(total, 1), "decode_tps": round(dec, 2)}))
+
+if __name__ == "__main__":
+    import sys
+    main(sys.argv[1] if len(sys.argv) > 1 else "x")

scripts/deploy-plan.py

@@ -61,9 +61,9 @@ SERVICE_ORDER = (
     "sonarr",
     "lidarr",
     "readarr",
-    "frank-large",
-    "frank-small",
-    "frank-primary",
+    "frank-dragoon",
+    "frank-zealot",
+    "frank-archon",
 )
 
 DANKCLAW_SERVICES = {
@@ -93,8 +93,8 @@ DANKCLAW_SERVICES = {
     "authentik-outpost-ldap",
     "caddy",
     "homepage",
-    "frank-large",
-    "frank-small",
+    "frank-dragoon",
+    "frank-zealot",
 }
 
 DANKSERVER_SERVICES = {
@@ -113,7 +113,7 @@ DANKSERVER_SERVICES = {
     "sonarr",
     "lidarr",
     "readarr",
-    "frank-primary",
+    "frank-archon",
     "node-exporter",
 }
 
@@ -316,7 +316,7 @@ def services_for_path(path: str, target: str) -> set[str]:
         if len(parts) >= 2 and parts[1] == "open-webui":
             _add(services, "open-webui")
             return services
-        # frank-large left the quadlet shape on 2026-09-19 (CIRU v4.4.1 host
+        # frank-dragoon left the quadlet shape on 2026-09-19 (CIRU v4.4.1 host
         # build, root unit): its files live in scripts/ and map there.
         if len(parts) >= 2 and parts[1] == "observability":
             # The five observability containers became Quadlet units on
@@ -371,10 +371,10 @@ def services_for_path(path: str, target: str) -> set[str]:
                 if name == "node-exporter":
                     _add(services, "node-exporter")
             return services
-        # frank-primary's quadlet-era directory left the tree on 2026-09-26
+        # frank-archon's quadlet-era directory left the tree on 2026-09-26
         # (the Lucebox DS4.1 unit was retired for the llama.cpp root unit —
         # the trio in scripts/ now maps it). Nothing lives under
-        # dankserver/frank-primary/ except dated trash, and trash plans
+        # dankserver/frank-archon/ except dated trash, and trash plans
         # nothing (the retire rule above the service blocks).
         return services
 
@@ -400,32 +400,32 @@ def services_for_path(path: str, target: str) -> set[str]:
             # change to it redeploying alertmanager is the only path that
             # reaches it on the host.
             _add(services, "alertmanager")
-        if name in {"frank-small.env", "frank-small.service", "serve-frank-small.sh"}:
-            # llama.cpp frank-small (2026-09-16) keeps its unit, env and serve
-            # files here; each one selects frank-small only. The ik_llama.cpp
+        if name in {"frank-zealot.env", "frank-zealot.service", "serve-frank-zealot.sh"}:
+            # llama.cpp frank-zealot (2026-09-16) keeps its unit, env and serve
+            # files here; each one selects frank-zealot only. The ik_llama.cpp
             # trio that lived here for two days is in scripts/.AGENTTRASH/,
             # which is archive material and plans nothing.
-            _add(services, "frank-small")
-        if name in {"frank-large.env", "frank-large.service", "serve-frank-large.sh"}:
-            # CIRU v4.4.1 frank-large (2026-09-19) keeps its unit, env and
+            _add(services, "frank-zealot")
+        if name in {"frank-dragoon.env", "frank-dragoon.service", "serve-frank-dragoon.sh"}:
+            # CIRU v4.4.1 frank-dragoon (2026-09-19) keeps its unit, env and
             # serve files here the same way: a root unit on a host-built
             # runtime. The download script fetches the payload, which is
             # host-side state, so it selects nothing.
-            _add(services, "frank-large")
+            _add(services, "frank-dragoon")
         if name == "qwen-sharp-v22.4.0.jinja":
-            # The Qwen-Sharp chat template frank-large loads via
+            # The Qwen-Sharp chat template frank-dragoon loads via
             # --chat-template-file. It lived under dankserver/frank-medium/ until
             # the 2026-09-26 cutover retired that directory; editing it changes
-            # what the live frank-large endpoint renders, so it plans
-            # frank-large.
-            _add(services, "frank-large")
-        if name in {"frank-primary.env", "frank-primary.service", "serve-frank-primary.sh"}:
-            # llama.cpp frank-primary (2026-09-26, replacing the Lucebox
+            # what the live frank-dragoon endpoint renders, so it plans
+            # frank-dragoon.
+            _add(services, "frank-dragoon")
+        if name in {"frank-archon.env", "frank-archon.service", "serve-frank-archon.sh"}:
+            # llama.cpp frank-archon (2026-09-26, replacing the Lucebox
             # DS4.1 quadlet) keeps its unit, env and serve files here the
             # same way: a root unit on the unsloth b11030-mix prebuilt
             # serving Qwen3.8-Flash-Next Q8_0. The download script fetches
             # the payload, which is host-side state, so it selects nothing.
-            _add(services, "frank-primary")
+            _add(services, "frank-archon")
         # Deployment/test/benchmark scripts and other repo tooling do not
         # restart a runtime service.
         return services

scripts/deploy-remote.sh

@@ -90,12 +90,12 @@ service_is_allowed() {
         dankclaw:authentik-postgres|dankclaw:authentik-server|\
         dankclaw:authentik-worker|dankclaw:authentik-outpost|dankclaw:authentik-outpost-ldap|dankclaw:anubis|\
         dankclaw:caddy|dankclaw:homepage|dankclaw:seerr|dankclaw:marreta|\
-        dankclaw:frank-large|dankclaw:frank-small|\
+        dankclaw:frank-dragoon|dankclaw:frank-zealot|\
         dankserver:romm-mariadb|dankserver:romm-redis|dankserver:romm|\
         dankserver:copyparty|dankserver:jellyfin|dankserver:calibre-web|dankserver:calibre-server|dankserver:plex|dankserver:tautulli|\
         dankserver:prowlarr|dankserver:qbittorrent|dankserver:radarr|\
         dankserver:sonarr|dankserver:lidarr|dankserver:readarr|\
-        dankserver:frank-primary|dankserver:node-exporter|\
+        dankserver:frank-archon|dankserver:node-exporter|\
         frankbook-pro:gluetun|frankbook-pro:qbittorrent|frankbook-pro:prowlarr|\
         frankbook-pro:radarr|frankbook-pro:sonarr|frankbook-pro:lidarr|\
         frankbook-pro:readarr)
@@ -192,7 +192,7 @@ add_pending_services() {
             continue
         fi
         [[ -n "$recorded" && "$recorded" != "$REVISION" ]] || continue
-        if [[ "$TARGET" == dankserver && "$service" == frank-large ]]; then continue; fi
+        if [[ "$TARGET" == dankserver && "$service" == frank-dragoon ]]; then continue; fi
         if ! changed="$(python3 scripts/deploy-plan.py --target "$TARGET" \
             --repo "$REMOTE_DIR" --base "$recorded" --head "$REVISION")"; then
             echo "WARN: unable to compare state for $service; retaining it as pending" >&2
@@ -322,6 +322,12 @@ deploy_homepage() {
     if [[ -d shared/homepage/fonts ]]; then
         run_privileged cp -r shared/homepage/fonts /srv/homepage/
     fi
+    if [[ -d shared/homepage/img ]]; then
+        run_privileged cp -r shared/homepage/img /srv/homepage/
+    fi
+    if [[ -d shared/homepage/sfx ]]; then
+        run_privileged cp -r shared/homepage/sfx /srv/homepage/
+    fi
     local deployed_at
     deployed_at="$(git log -1 --format=%cI)"
     printf 'window.DEPLOYED_AT = "%s";\n' "$deployed_at" > /tmp/deployed.js
@@ -1086,41 +1092,45 @@ deploy_anubis() {
     wait_container_healthy anubis 60 || return 1
 }
 
-# frank-large is the halogen CONTAINER (ghcr.io/peonist-ai/halogen,
-# digest-pinned through scripts/frank-large.env) serving
-# peonist-ai/halogen-qwen3.8-27b — qwen3.8-27b-p1w4d-d2.hgn, 33.4 GiB,
-# DFlash2 spec decode, 1 slot x 200700, text-only — on the Strix Halo
-# iGPU. It stays a ROOT unit because the serve script drives `podman run`
-# directly (the frank-primary pattern): relink_unit points
-# /etc/systemd/system/frank-large.service at the repo file, boot
+# frank-dragoon is the halogen-flash-server CONTAINER (0.16.2, digest-pinned
+# through scripts/frank-dragoon.env) serving the Quat3rnion ABLITERATED
+# Swift1.5 finetune of peonist's Qwen3.8-Flash-Next v2 checkpoint —
+# qwen38-flash-next-v2-swift15-abliterated.hgn (66,687,678,464 B, ~62 GiB
+# resident) + the REQUIRED n-gram lookup table + the vision tower —
+# MTP spec decode (HALOGEN_SPEC_ADAPT=0), 2 slots x 200192, image input —
+# on the Strix Halo iGPU. It stays a ROOT unit because the serve script
+# drives `podman run` directly (the frank-archon pattern): relink_unit
+# points /etc/systemd/system/frank-dragoon.service at the repo file, boot
 # persistence is that unit's [Install], and LimitMEMLOCK=infinity is
-# fleet parity. 2026-10-05 cutover from the ROCmFPX llama.cpp shape —
-# rollback = revert the swap commit's trio; that payload, its draft head
-# and the fork build all stay on disk
-# (~/models/kingjones-Qwen3.8-27B-Uncensored-ROCmFP4-STRIX-MTP,
-# ~/GitPackages/kingjones-ROCmFPX).
+# fleet parity. 2026-10-06 cutover from the halogen 27B-dense shape —
+# rollback = revert the swap commit's trio; the 27B payload stays on
+# disk (~/models/halogen-qwen3.8-27b).
 #
-# The gates mirror serve-frank-large.sh's predicates EXACTLY (the
+# The gates mirror serve-frank-dragoon.sh's predicates EXACTLY (the
 # 2026-10-01 crash-loop lesson): image digest in dank's podman storage,
-# the .hgn checkpoint at the exact byte count, the tokenizer directory
-# holding every named file as a regular (not symlinked) file — a green
-# deploy against a missing artifact would
-# leave a restart-looping unit and a dark endpoint. The port gate is the
-# same as every cutover since 2026-09-16: nothing starts until 7770 is
-# released.
-LLM_LARGE_IMAGE="${LLM_LARGE_IMAGE:-ghcr.io/peonist-ai/halogen@sha256:dc0a39a0016d6cfc58a197978febaafdf8d28403f724ded6111d98b5fb7ac0ea}"
-LLM_LARGE_CKPT="${LLM_LARGE_CKPT:-/home/dank/models/halogen-qwen3.8-27b/qwen3.8-27b-p1w4d-d2.hgn}"
-LLM_LARGE_CKPT_BYTES="${LLM_LARGE_CKPT_BYTES:-35865565184}"
-LLM_LARGE_TOK_DIR="${LLM_LARGE_TOK_DIR:-/home/dank/models/halogen-qwen3.8-27b/tokenizer}"
-LLM_LARGE_TOK_FILES="${LLM_LARGE_TOK_FILES:-tokenizer.json chat_template.jinja tokenizer_config.json merges.txt vocab.json}"
+# each .hgn payload (checkpoint, n-gram table, vision tower) at the exact
+# byte count, the tokenizer directory holding every named file as a
+# regular (not symlinked) file — a green deploy against a missing
+# artifact would leave a restart-looping unit and a dark endpoint. The
+# port gate is the same as every cutover since 2026-09-16: nothing
+# starts until 7770 is released.
+LLM_DRAGOON_IMAGE="${LLM_DRAGOON_IMAGE:-ghcr.io/peonist-ai/halogen-flash-server@sha256:0c61bf84ac22308a53f5d1ca6b86806702d7039e5ebc51cae4c66621b92fe04a}"
+LLM_DRAGOON_CKPT="${LLM_DRAGOON_CKPT:-/home/dank/models/halogen-flashnext-v2/qwen38-flash-next-v2-swift15-abliterated.hgn}"
+LLM_DRAGOON_CKPT_BYTES="${LLM_DRAGOON_CKPT_BYTES:-66687678464}"
+LLM_DRAGOON_NGRAM="${LLM_DRAGOON_NGRAM:-/home/dank/models/halogen-flashnext-v2/qwen38-flash-next-ngram.hgn}"
+LLM_DRAGOON_NGRAM_BYTES="${LLM_DRAGOON_NGRAM_BYTES:-51200246144}"
+LLM_DRAGOON_VISION="${LLM_DRAGOON_VISION:-/home/dank/models/halogen-flashnext-v2/qwen38-flash-next-vision.hgn}"
+LLM_DRAGOON_VISION_BYTES="${LLM_DRAGOON_VISION_BYTES:-897916416}"
+LLM_DRAGOON_TOK_DIR="${LLM_DRAGOON_TOK_DIR:-/home/dank/models/halogen-flashnext-v2/tokenizer}"
+LLM_DRAGOON_TOK_FILES="${LLM_DRAGOON_TOK_FILES:-tokenizer.json chat_template.jinja tokenizer_config.json merges.txt vocab.json generation_config.json}"
 
-retire_halogen_large_quadlet() {
+retire_halogen_dragoon_quadlet() {
     local trash="$HOME/.AGENTTRASH/20260919-orca-cutover/quadlet"
-    systemctl --user stop frank-large.service 2>/dev/null || true
-    if [[ -e "$quadlet_unit_dir/frank-large.container" ]]; then
+    systemctl --user stop frank-dragoon.service 2>/dev/null || true
+    if [[ -e "$quadlet_unit_dir/frank-dragoon.container" ]]; then
         mkdir -p "$trash"
-        mv -- "$quadlet_unit_dir/frank-large.container" "$trash/frank-large.container"
-        echo "retired quadlet frank-large.container -> $trash"
+        mv -- "$quadlet_unit_dir/frank-dragoon.container" "$trash/frank-dragoon.container"
+        echo "retired quadlet frank-dragoon.container -> $trash"
     fi
     systemctl --user daemon-reload
 }
@@ -1144,175 +1154,184 @@ wait_port_free() {
     return 1
 }
 
-deploy_llm_large() {
+deploy_llm_dragoon() {
     # Refuse rather than restart-loop; every gate below has a twin in
-    # serve-frank-large.sh and they must agree (2026-10-01 lesson).
+    # serve-frank-dragoon.sh and they must agree (2026-10-01 lesson).
     # Capture podman output before grepping: `podman images | grep -q`
     # races under pipefail (SIGPIPE 141 becomes "no match", 2026-09-30).
-    if ! grep -qF "${LLM_LARGE_IMAGE#*@}" <<<"$(podman images --format '{{.RepoDigests}}' 2>/dev/null)"; then
-        echo "ERROR: halogen image absent: $LLM_LARGE_IMAGE" >&2
-        echo "frank-large: pull it: podman pull ${LLM_LARGE_IMAGE%@*}" >&2
+    if ! grep -qF "${LLM_DRAGOON_IMAGE#*@}" <<<"$(podman images --format '{{.RepoDigests}}' 2>/dev/null)"; then
+        echo "ERROR: halogen image absent: $LLM_DRAGOON_IMAGE" >&2
+        echo "frank-dragoon: pull it: podman pull ${LLM_DRAGOON_IMAGE%@*}" >&2
         return 1
     fi
-    if [[ ! -f "$LLM_LARGE_CKPT" ]]; then
-        echo "ERROR: halogen checkpoint absent at $LLM_LARGE_CKPT" >&2
-        echo "frank-large: fetch it: bash scripts/download-frank-large-halogen.sh" >&2
+    if [[ ! -f "$LLM_DRAGOON_CKPT" ]]; then
+        echo "ERROR: halogen checkpoint absent at $LLM_DRAGOON_CKPT" >&2
+        echo "frank-dragoon: fetch it: bash scripts/download-frank-dragoon-flashnext.sh" >&2
         return 1
     fi
-    if [[ "$(stat -c %s "$LLM_LARGE_CKPT")" != "$LLM_LARGE_CKPT_BYTES" ]]; then
-        echo "ERROR: halogen checkpoint is not $LLM_LARGE_CKPT_BYTES bytes (partial download?)" >&2
-        echo "frank-large: re-check: bash scripts/download-frank-large-halogen.sh --verify-only" >&2
+    if [[ "$(stat -c %s "$LLM_DRAGOON_CKPT")" != "$LLM_DRAGOON_CKPT_BYTES" ]]; then
+        echo "ERROR: halogen checkpoint is not $LLM_DRAGOON_CKPT_BYTES bytes (partial download?)" >&2
+        echo "frank-dragoon: re-check: bash scripts/download-frank-dragoon-flashnext.sh --verify-only" >&2
         return 1
     fi
-    if [[ -L "$LLM_LARGE_TOK_DIR" || ! -d "$LLM_LARGE_TOK_DIR" ]]; then
-        echo "ERROR: tokenizer dir missing or a symlink at $LLM_LARGE_TOK_DIR" >&2
-        echo "frank-large: fetch it: bash scripts/download-frank-large-halogen.sh" >&2
+    for gate in "$LLM_DRAGOON_NGRAM:$LLM_DRAGOON_NGRAM_BYTES:n-gram table" \
+                "$LLM_DRAGOON_VISION:$LLM_DRAGOON_VISION_BYTES:vision tower"; do
+        IFS=: read -r gpath gbytes gname <<<"$gate"
+        if [[ ! -f "$gpath" ]]; then
+            echo "ERROR: halogen $gname absent at $gpath" >&2
+            echo "frank-dragoon: fetch it: bash scripts/download-frank-dragoon-flashnext.sh" >&2
+            return 1
+        fi
+        if [[ "$(stat -c %s "$gpath")" != "$gbytes" ]]; then
+            echo "ERROR: halogen $gname is not $gbytes bytes (partial download?)" >&2
+            echo "frank-dragoon: re-check: bash scripts/download-frank-dragoon-flashnext.sh --verify-only" >&2
+            return 1
+        fi
+    done
+    if [[ -L "$LLM_DRAGOON_TOK_DIR" || ! -d "$LLM_DRAGOON_TOK_DIR" ]]; then
+        echo "ERROR: tokenizer dir missing or a symlink at $LLM_DRAGOON_TOK_DIR" >&2
+        echo "frank-dragoon: fetch it: bash scripts/download-frank-dragoon-flashnext.sh" >&2
         return 1
     fi
-    for tf in $LLM_LARGE_TOK_FILES; do
-        if [[ ! -f "$LLM_LARGE_TOK_DIR/$tf" || -L "$LLM_LARGE_TOK_DIR/$tf" ]]; then
-            echo "ERROR: tokenizer file missing or a symlink: $LLM_LARGE_TOK_DIR/$tf" >&2
-            echo "frank-large: fetch it: bash scripts/download-frank-large-halogen.sh" >&2
+    for tf in $LLM_DRAGOON_TOK_FILES; do
+        if [[ ! -f "$LLM_DRAGOON_TOK_DIR/$tf" || -L "$LLM_DRAGOON_TOK_DIR/$tf" ]]; then
+            echo "ERROR: tokenizer file missing or a symlink: $LLM_DRAGOON_TOK_DIR/$tf" >&2
+            echo "frank-dragoon: fetch it: bash scripts/download-frank-dragoon-flashnext.sh" >&2
             return 1
         fi
     done
 
-    retire_halogen_large_quadlet
+    retire_halogen_dragoon_quadlet
     # The predecessor on a re-deploy is THIS unit: stop it (ExecStop stops
     # the container) before waiting on the port. The stray sweep is keyed
     # on the FULL container name, which appears in the argv of a manual
-    # `podman run --name frank-large-halogen` / `podman wait` but NOT in
+    # `podman run --name frank-dragoon-halogen` / `podman wait` but NOT in
     # this deployer's own command line (`bash deploy-remote.sh
-    # frank-large`) — so it cannot shoot itself in the foot (the fleet
-    # pkill law), and it can never match frank-small's llama-server.
-    run_privileged systemctl stop frank-large.service 2>/dev/null || true
-    pkill -f 'frank-large-halogen' 2>/dev/null || true
-    podman rm -f frank-large frank-large-halogen >/dev/null 2>&1 || true
+    # frank-dragoon`) — so it cannot shoot itself in the foot (the fleet
+    # pkill law), and it can never match frank-zealot's llama-server.
+    run_privileged systemctl stop frank-dragoon.service 2>/dev/null || true
+    pkill -f 'frank-dragoon-halogen' 2>/dev/null || true
+    podman rm -f frank-dragoon frank-dragoon-halogen >/dev/null 2>&1 || true
     # Nothing may start until the predecessor has released the port
     # (2026-09-16: "Deactivated successfully" was not "port free").
     wait_port_free 7770 || return 1
-    relink_unit frank-large
+    relink_unit frank-dragoon
     run_privileged systemctl daemon-reload
-    run_privileged systemctl enable frank-large.service
-    run_privileged systemctl restart frank-large.service
-    wait_for_health frank-large http://127.0.0.1:7770/health 1200
+    run_privileged systemctl enable frank-dragoon.service
+    run_privileged systemctl restart frank-dragoon.service
+    wait_for_health frank-dragoon http://127.0.0.1:7770/health 1200
 }
 
-# deploy_llm_small — frank-small is llama.cpp (master build, CUDA sm_86) on
+# deploy_llm_zealot — frank-zealot is llama.cpp (master build, CUDA sm_86) on
 # the RTX 3090 as a ROOT unit: the runtime is a native binary tree under
 # ~/GitPackages/llama-master/build-cuda, so there is no container image and
 # no generated unit to avoid. relink_unit points
-# /etc/systemd/system/frank-small.service at the repo file and boot
+# /etc/systemd/system/frank-zealot.service at the repo file and boot
 # persistence is that unit's [Install] section.
 #
-# It is a SEPARATE endpoint on port 7771; frank-large keeps 7770. The 3090 is
-# not shared: frank-large's engine runs on the gfx1151 iGPU.
-LLM_SMALL_MODEL_FILE="${LLM_SMALL_MODEL_FILE:-/home/dank/models/Ornith-Q8/Ornith-1.5-9B-Q8_0.gguf}"
-LLM_SMALL_RUNTIME="${LLM_SMALL_RUNTIME:-/home/dank/GitPackages/llama-master/build-cuda/bin/llama-server}"
-# The projector IS the vision capability here: the Ornith GGUF ships no
-# `v.*` tensors, so a deploy that starts without this file silently ships a
-# text-only endpoint. Checked unconditionally, like frank-large's.
-LLM_SMALL_MMPROJ="${LLM_SMALL_MMPROJ:-/home/dank/models/Ornith-Q8/mmproj-Ornith-1.5-9B-BF16.gguf}"
+# It is a SEPARATE endpoint on port 7771; frank-dragoon keeps 7770. The 3090 is
+# not shared: frank-dragoon's engine runs on the gfx1151 iGPU.
+LLM_ZEALOT_MODEL_FILE="${LLM_ZEALOT_MODEL_FILE:-/home/dank/models/Qwen35-9B-HauhauCS-Q6K/Qwen3.5-9B-Uncensored-HauhauCS-Aggressive-Q6_K.gguf}"
+LLM_ZEALOT_RUNTIME="${LLM_ZEALOT_RUNTIME:-/home/dank/GitPackages/llama-master/build-cuda/bin/llama-server}"
+# The projector IS the vision capability here: the model is natively
+# multimodal and the Q6_K file carries no vision tensors — the publisher ships
+# its own BF16 projector in the same repo, so a deploy that starts without
+# this file silently ships a text-only endpoint. Checked unconditionally, like
+# frank-dragoon's.
+LLM_ZEALOT_MMPROJ="${LLM_ZEALOT_MMPROJ:-/home/dank/models/Qwen35-9B-HauhauCS-Q6K/mmproj-Qwen3.5-9B-Uncensored-HauhauCS-Aggressive-BF16.gguf}"
 
-deploy_llm_small() {
+deploy_llm_zealot() {
     # Refuse rather than restart-loop: a unit whose runtime or payload is
     # missing never becomes healthy, and a green deploy would leave the
     # endpoint dark with nothing in the log to say why.
-    if [[ ! -x "$LLM_SMALL_RUNTIME" ]]; then
-        echo "ERROR: llama.cpp runtime absent at $LLM_SMALL_RUNTIME" >&2
-        echo "frank-small: build it (cmake -B build-cuda -DGGML_CUDA=ON" >&2
-        echo "frank-small: -DCMAKE_CUDA_ARCHITECTURES=86 -DCMAKE_CUDA_HOST_COMPILER=/usr/bin/gcc-13" >&2
-        echo "frank-small: && cmake --build build-cuda --target llama-server) first." >&2
+    if [[ ! -x "$LLM_ZEALOT_RUNTIME" ]]; then
+        echo "ERROR: llama.cpp runtime absent at $LLM_ZEALOT_RUNTIME" >&2
+        echo "frank-zealot: build it (cmake -B build-cuda -DGGML_CUDA=ON" >&2
+        echo "frank-zealot: -DCMAKE_CUDA_ARCHITECTURES=86 -DCMAKE_CUDA_HOST_COMPILER=/usr/bin/gcc-13" >&2
+        echo "frank-zealot: && cmake --build build-cuda --target llama-server) first." >&2
         return 1
     fi
-    for f in "$LLM_SMALL_MODEL_FILE" "$LLM_SMALL_MMPROJ"; do
+    for f in "$LLM_ZEALOT_MODEL_FILE" "$LLM_ZEALOT_MMPROJ"; do
         if [[ ! -f "$f" ]]; then
-            echo "ERROR: frank-small payload file absent at $f" >&2
-            echo "frank-small: run scripts/download-frank-small.sh first;" >&2
-            echo "frank-small: refusing to start a unit that cannot load." >&2
+            echo "ERROR: frank-zealot payload file absent at $f" >&2
+            echo "frank-zealot: run scripts/download-frank-zealot.sh first;" >&2
+            echo "frank-zealot: refusing to start a unit that cannot load." >&2
             return 1
         fi
     done
-    relink_unit frank-small
+    relink_unit frank-zealot
     run_privileged systemctl daemon-reload
-    run_privileged systemctl enable frank-small.service
-    run_privileged systemctl restart frank-small.service
-    wait_for_health frank-small http://127.0.0.1:7771/health 900 || return 1
-    # False-green hardening (frank-large's lesson): the port answering
+    run_privileged systemctl enable frank-zealot.service
+    run_privileged systemctl restart frank-zealot.service
+    wait_for_health frank-zealot http://127.0.0.1:7771/health 900 || return 1
+    # False-green hardening (frank-dragoon's lesson): the port answering
     # proves nothing about WHO answers — the unit must be active with a
     # live MainPID, or a stray SGLang holdover is masquerading as deployed.
     local main_pid
-    main_pid="$(run_privileged systemctl show -p MainPID --value frank-small.service)"
+    main_pid="$(run_privileged systemctl show -p MainPID --value frank-zealot.service)"
     if [[ -z "$main_pid" || "$main_pid" == "0" ]]; then
-        echo "FAIL: :7771 answered but frank-small.service has no MainPID — a stray process holds the port" >&2
+        echo "FAIL: :7771 answered but frank-zealot.service has no MainPID — a stray process holds the port" >&2
         return 1
     fi
-    echo "frank-small: health answered by unit MainPID $main_pid"
+    echo "frank-zealot: health answered by unit MainPID $main_pid"
 }
 
-# deploy_llm_primary — frank-primary is the FreeToken engine (PR #587 ROCm
-# build, gfx1201) serving the orcarouter Qwen3.8-Flash-Next-Uncensored-FP8
-# payload (131 safetensors shards) on ONE R9700 as a ROOT unit whose serve
-# script drives `podman run` directly (the image carries `ft serve`).
-# 2026-10-05 cutover from the tcclaviger vLLM fork (pre-cutover tag
-# frank-primary-vllm-shapeG-20261003); before that, 2026-09-29 cutover from
-# the R9V radiance fork, whose launcher/shim/setup-state machinery is
-# retired. Same port and alias as the endpoints it replaced; the harness
-# models.yml id is unchanged.
+# deploy_llm_archon — frank-archon is the radiance engine (StillDeadcode,
+# digest-pinned stilldeadcode/radiance image) serving the OFFICIAL
+# Qwen/Qwen3.8-Flash-Next-FP8 at native block-FP8 precision from the
+# rad-convert container qwen4exp-fp8-native.rad, on BOTH R9700s (TP=2) as a
+# ROOT unit whose serve script drives `podman run` directly (the engine is
+# the image entrypoint; the image lives in dank's rootless podman storage).
+# 2026-10-05 cutover from FreeToken (pre-cutover tag
+# frank-archon-freetoken-pr587-20261005); before that, the tcclaviger vLLM
+# fork (tag frank-archon-vllm-shapeG-20261003). Same port and alias; the
+# harness models.yml id is unchanged.
 #
-# Gates: the runtime image must exist in dank's rootless storage
-# (FRANK_PRIMARY_IMAGE — a LOCAL tag: the image is built on the host from
-# scripts/docker/frank-primary-freetoken.Dockerfile, which pins the
-# FreeToken PR-head SHA and the base image), the payload dir must carry
-# config.json and the expected shard count (FRANK_PRIMARY_MODEL_SHARDS),
-# and the unit env must be complete. Per-file sha256 verification was the
-# fetch script's job at download time, never re-hashed here.
-LLM_PRIMARY_CONTAINER=frank-primary
-LLM_PRIMARY_LEGACY_CONTAINERS="frank-primary-qwen frank-primary-r9v qwen-fp8 glm-probe"
+# Gates: the image must exist under its digest ref in dank's rootless
+# storage (FRANK_ARCHON_IMAGE), the .rad container file must exist at the
+# env's size floor (FRANK_ARCHON_MODEL_FILE >= FRANK_ARCHON_RAD_MIN_MIB —
+# a truncated convert is a guaranteed long-timeout boot), and the unit env
+# must be complete. Per-file sha256 verification is the fetch script's job
+# at download time and rad-convert/rad-info's job at build time, never
+# re-hashed here.
+LLM_ARCHON_CONTAINER=frank-archon
+LLM_ARCHON_LEGACY_CONTAINERS="frank-archon-qwen frank-archon-r9v qwen-fp8 glm-probe"
 
-deploy_llm_primary() {
+deploy_llm_archon() {
     # Refuse rather than restart-loop: a unit whose image or payload is
     # missing never becomes healthy, and a green deploy would leave the
     # endpoint dark with nothing in the log to say why.
-    local env_file="/home/dank/serverAppConfigs/scripts/frank-primary.env"
-    local image model_dir shards count
+    local env_file="/home/dank/serverAppConfigs/scripts/frank-archon.env"
+    local image model_dir model_file rad_min mib
     if [[ ! -f "$env_file" ]]; then
-        echo "ERROR: frank-primary env file absent: $env_file" >&2
+        echo "ERROR: frank-archon env file absent: $env_file" >&2
         return 1
     fi
-    image="$(sed -n 's/^FRANK_PRIMARY_IMAGE=//p' "$env_file" | tail -1)"
-    model_dir="$(sed -n 's/^FRANK_PRIMARY_MODEL_DIR=//p' "$env_file" | tail -1)"
-    shards="$(sed -n 's/^FRANK_PRIMARY_MODEL_SHARDS=//p' "$env_file" | tail -1)"
-    if [[ -z "$image" || -z "$model_dir" || -z "$shards" ]]; then
-        echo "ERROR: frank-primary.env missing FRANK_PRIMARY_IMAGE/MODEL_DIR/MODEL_SHARDS" >&2
+    image="$(sed -n 's/^FRANK_ARCHON_IMAGE=//p' "$env_file" | tail -1)"
+    model_dir="$(sed -n 's/^FRANK_ARCHON_MODEL_DIR=//p' "$env_file" | tail -1)"
+    model_file="$(sed -n 's/^FRANK_ARCHON_MODEL_FILE=//p' "$env_file" | tail -1)"
+    rad_min="$(sed -n 's/^FRANK_ARCHON_RAD_MIN_MIB=//p' "$env_file" | tail -1)"
+    if [[ -z "$image" || -z "$model_dir" || -z "$model_file" || -z "$rad_min" ]]; then
+        echo "ERROR: frank-archon.env missing FRANK_ARCHON_IMAGE/MODEL_DIR/MODEL_FILE/RAD_MIN_MIB" >&2
         return 1
     fi
-    # The image gate is EXISTENCE IN STORAGE, not a registry digest: the
-    # FreeToken image is built ON THE HOST (a local tag carries NO
-    # RepoDigests entry — the old grep refused exactly this shape), and
-    # pinning lives in the Dockerfile (pinned PR-head SHA + digest-pinned
-    # base image). `podman image exists` accepts a local tag and a
-    # name@digest ref alike, in one command — no pipefail/grep race (the
-    # 2026-09-30 lesson) for either shape.
+    # The image gate is the digest ref itself: a name@sha256 ref exists in
+    # storage only if THAT manifest was pulled. One command — no
+    # pipefail/grep race (the 2026-09-30 lesson).
     if ! podman image exists "$image"; then
-        echo "ERROR: runtime image absent from rootless storage: $image" >&2
-        echo "frank-primary: build it (scripts/docker/frank-primary-freetoken.Dockerfile) or pull it" >&2
+        echo "ERROR: runtime image absent from storage: $image" >&2
+        echo "frank-archon: podman pull docker://stilldeadcode/radiance:latest" >&2
         return 1
     fi
-    if [[ ! -f "$model_dir/config.json" ]]; then
-        echo "ERROR: payload config missing: $model_dir/config.json" >&2
-        echo "frank-primary: re-run scripts/download-frank-primary.sh" >&2
+    if [[ ! -f "$model_dir/$model_file" ]]; then
+        echo "ERROR: .rad container missing: $model_dir/$model_file" >&2
+        echo "frank-archon: run scripts/build-frank-archon-rad.sh" >&2
         return 1
     fi
-    if [[ ! -f "$model_dir/model.safetensors.index.json" ]]; then
-        echo "ERROR: weight-map index missing: $model_dir/model.safetensors.index.json" >&2
-        echo "frank-primary: re-run scripts/download-frank-primary.sh" >&2
-        return 1
-    fi
-    count="$(find "$model_dir" -maxdepth 1 -name 'model-*-of-*.safetensors' 2>/dev/null | wc -l)"
-    if [[ "$count" != "$shards" ]]; then
-        echo "ERROR: payload shard count wrong: $model_dir (found $count, want $shards)" >&2
-        echo "frank-primary: re-run scripts/download-frank-primary.sh" >&2
+    mib=$(( $(stat -c %s "$model_dir/$model_file") / 1048576 ))
+    if [[ "$mib" -lt "$rad_min" ]]; then
+        echo "ERROR: .rad container too small: $model_dir/$model_file is ${mib} MiB, want >= $rad_min" >&2
+        echo "frank-archon: rebuild it (scripts/build-frank-archon-rad.sh --force)" >&2
         return 1
     fi
 
@@ -1324,39 +1343,37 @@ deploy_llm_primary() {
     # The legacy identities (the retired R9V container, the ad hoc
     # experiment container qwen-fp8, the retired glm-probe) hold the same
     # GPUs and die here too.
-    run_privileged systemctl stop frank-primary.service 2>/dev/null || true
+    run_privileged systemctl stop frank-archon.service 2>/dev/null || true
     local ctr
-    for ctr in $LLM_PRIMARY_LEGACY_CONTAINERS "$LLM_PRIMARY_CONTAINER"; do
+    for ctr in $LLM_ARCHON_LEGACY_CONTAINERS "$LLM_ARCHON_CONTAINER"; do
         podman rm -f "$ctr" >/dev/null 2>&1 || true
     done
     # Nothing starts until the port is released: the lucebox cutover
-    # (2026-09-26) and the frank-large cutover (2026-09-16) both failed
+    # (2026-09-26) and the frank-dragoon cutover (2026-09-16) both failed
     # exactly here when the next engine bound 7770 a second too early.
     wait_port_free 7770 || return 1
-    relink_unit frank-primary
+    relink_unit frank-archon
     run_privileged systemctl daemon-reload
-    run_privileged systemctl enable frank-primary.service
-    run_privileged systemctl restart frank-primary.service
-    # Cold start: FP8 page-in plus torch compile/graph capture (~15 min cold,
-    # measured 2026-09-29). Parity with every predecessor on this port.
-    # FreeToken's /health returns 200 with {"status":"loading"} while the
-    # engine loads (the FastAPI front end binds before the scheduler is
-    # up), so a bare 200 false-greens — measured 2026-10-06: "healthy after
-    # 6 s" while 131 shards were still paging in. vLLM 503'd during load,
-    # which made the bare curl honest there; FreeToken needs the BODY read.
-    # Only status:"ok" counts. (The MainPID check below still guards the
-    # stray-port case.)
+    run_privileged systemctl enable frank-archon.service
+    run_privileged systemctl restart frank-archon.service
+    # Cold start: .rad load + PLE pin + expert host-pool upload (the
+    # publisher's compose healthcheck allows a 15-minute start_period).
+    # Parity with every predecessor on this port. The HTTP listener binds
+    # AFTER the full load (main.cpp: engine.start() then engine.serve()),
+    # so during load the port REFUSES connections — a bare curl is honest
+    # here, unlike FreeToken's 200-while-loading body. (The MainPID check
+    # below still guards the stray-port case.)
     local i ok=0
     for ((i=1; i<=900; i++)); do
-        if curl -fsS http://127.0.0.1:7770/health 2>/dev/null | grep -q '"status":"ok"'; then
-            echo "frank-primary engine healthy after approximately $((i * 2))s"
+        if curl -fsS http://127.0.0.1:7770/health 2>/dev/null >/dev/null; then
+            echo "frank-archon engine healthy after approximately $((i * 2))s"
             ok=1
             break
         fi
         sleep 2
     done
     if [[ "$ok" != 1 ]]; then
-        echo "FAIL: frank-primary never reached /health status ok in 1800s" >&2
+        echo "FAIL: frank-archon /health never answered 200 in 1800s" >&2
         return 1
     fi
     # False-green hardening (the 2026-09-26 lesson): a bare curl against the
@@ -1364,12 +1381,12 @@ deploy_llm_primary() {
     # it while the unit is stopped. The deploy is only green if the unit
     # itself is active with a live MainPID behind the health answer.
     local main_pid
-    main_pid="$(run_privileged systemctl show -p MainPID --value frank-primary.service)"
+    main_pid="$(run_privileged systemctl show -p MainPID --value frank-archon.service)"
     if [[ -z "$main_pid" || "$main_pid" == "0" ]]; then
-        echo "FAIL: :7770 answered but frank-primary.service has no MainPID — a stray process holds the port" >&2
+        echo "FAIL: :7770 answered but frank-archon.service has no MainPID — a stray process holds the port" >&2
         return 1
     fi
-    echo "frank-primary: health answered by unit MainPID $main_pid"
+    echo "frank-archon: health answered by unit MainPID $main_pid"
 }
 
 wait_for_health() {
@@ -1556,9 +1573,9 @@ deploy_service() {
         anubis) deploy_anubis ;;
         seerr) deploy_seerr ;;
         marreta) deploy_marreta ;;
-        frank-large) deploy_llm_large ;;
-        frank-small) deploy_llm_small ;;
-        frank-primary) deploy_llm_primary ;;
+        frank-dragoon) deploy_llm_dragoon ;;
+        frank-zealot) deploy_llm_zealot ;;
+        frank-archon) deploy_llm_archon ;;
         hermes|hermes-dashboard|hermes-webui) deploy_hermes ;;
         romm|romm-mariadb|romm-redis|mariadb|redis) deploy_romm_stack "$service" ;;
         jellyfin) deploy_jellyfin ;;

scripts/deploy.sh

@@ -35,7 +35,7 @@ Options:
 Examples:
   ./scripts/deploy.sh dankclaw
   ./scripts/deploy.sh dankclaw --service searxng
-  ./scripts/deploy.sh dankserver --service frank-primary
+  ./scripts/deploy.sh dankserver --service frank-archon
   ./scripts/deploy.sh dankclaw --dry-run
 EOF
 }
@@ -141,12 +141,12 @@ valid_service() {
         dankclaw:alertmanager|\
         dankclaw:node-exporter|dankclaw:authentik-postgres|dankclaw:authentik-server|\
         dankclaw:authentik-worker|dankclaw:authentik-outpost|dankclaw:authentik-outpost-ldap|dankclaw:anubis|dankclaw:seerr|\
-        dankclaw:frank-large|dankclaw:frank-small|\
+        dankclaw:frank-dragoon|dankclaw:frank-zealot|\
         dankserver:romm-mariadb|dankserver:romm-redis|dankserver:romm|\
         dankserver:copyparty|dankserver:jellyfin|dankserver:calibre-web|dankserver:calibre-server|dankserver:plex|dankserver:tautulli|\
         dankserver:qbittorrent|dankserver:radarr|dankserver:sonarr|\
         dankserver:lidarr|dankserver:readarr|dankserver:node-exporter|\
-        dankserver:frank-primary|\
+        dankserver:frank-archon|\
         frankbook-pro:gluetun|frankbook-pro:qbittorrent|frankbook-pro:prowlarr|\
         frankbook-pro:radarr|frankbook-pro:sonarr|frankbook-pro:lidarr|\
         frankbook-pro:readarr)

scripts/derive-protected-experts.py

@@ -0,0 +1,117 @@
+#!/usr/bin/env python3
+"""derive-protected-experts.py — rewrite the recipe's protected-expert section
+from a calibration recording. RUNS ON DANKSERVER (venv: numpy).
+
+The law (docs/MOE-W4.md "Protected experts", restated in the recipe):
+an expert whose share of its layer's down-input energy is at least 3% AND
+at least three times its share of the routing is kept bf16; the count must
+be EVEN on each rank's half of the layer (the four-bit GEMM takes the rest
+as two equal tables by parity) — an odd half gains its next most energetic
+non-qualifying expert.
+
+Data: the calibration dir's per-expert down Grams,
+gram.r<rank>.blk.L.ffn_down_exps.<e>.bin — 32-byte RADGRAM2 header
+(magic, k, rank, rows, domain) then k*k f32, named with the checkpoint's
+GLOBAL expert numbering (arch/common/rad_block_moe_fp8.h: ge =
+expert_base + e). rows (header) is the expert's routing count; the trace
+of the Gram is its down-input energy. Rank halves: 0-255, 256-511
+(contiguous expert_base split at TP=2).
+
+Output: the cast-rule lines (recipe format) on stdout, a report on stderr.
+
+Usage: derive-protected-experts.py <calib dir> [--min-share 0.03]
+       [--min-route-mult 3.0]
+"""
+import argparse
+import glob
+import os
+import re
+import struct
+import sys
+
+import numpy as np
+
+NAME_RE = re.compile(r"^gram\.r(\d)\.blk\.(\d+)\.ffn_down_exps\.(\d+)\.bin$")
+
+
+def read_gram(path):
+    """(k, rank, rows, trace) from a RADGRAM2 file (full matrix on disk)."""
+    with open(path, "rb") as f:
+        hdr = f.read(32)
+        magic, k, rank, rows, domain = struct.unpack("<8sIIQI", hdr[:28])
+        if magic != b"RADGRAM2":
+            raise SystemExit(f"not a RADGRAM2 file: {path}")
+        n = k * k
+        a = np.frombuffer(f.read(n * 4), dtype=np.float32)
+        if a.size != n:
+            raise SystemExit(f"short gram file: {path}")
+        tr = float(a.reshape(k, k).diagonal().sum())
+    return k, rank, int(rows), tr
+
+
+def main():
+    ap = argparse.ArgumentParser()
+    ap.add_argument("calib_dir")
+    ap.add_argument("--min-share", type=float, default=0.03)
+    ap.add_argument("--min-route-mult", type=float, default=3.0)
+    a = ap.parse_args()
+
+    # layer -> global expert -> (rank, rows, energy)
+    data = {}
+    for path in sorted(glob.glob(os.path.join(
+            a.calib_dir, "gram.r*.ffn_down_exps.*.bin"))):
+        m = NAME_RE.match(os.path.basename(path))
+        if not m:
+            continue
+        rank, layer, expert = int(m.group(1)), int(m.group(2)), int(m.group(3))
+        k, _, rows, tr = read_gram(path)
+        data.setdefault(layer, {})[expert] = (rank, rows, tr)
+
+    if not data:
+        raise SystemExit("no per-expert down grams found")
+
+    lines, report = [], []
+    total = 0
+    for layer in sorted(data):
+        experts = data[layer]
+        tot_e = sum(v[2] for v in experts.values())
+        tot_r = sum(v[1] for v in experts.values())
+        if tot_e <= 0 or tot_r <= 0:
+            report.append(f"blk.{layer}: empty recording, skipped")
+            continue
+        qual, pool = [], []
+        for e, (rank, rows, tr) in experts.items():
+            es, rs = tr / tot_e, rows / max(tot_r, 1)
+            rec = (e, rank, es, rs)
+            if es >= a.min_share and es >= a.min_route_mult * rs:
+                qual.append(rec)
+            elif es > 0:
+                pool.append(rec)
+        chosen = {r[0]: (r[2], r[3]) for r in qual}
+        for half in (0, 1):  # rank halves by the contiguous expert_base split
+            n_half = sum(1 for e in chosen if e // 256 == half)
+            if n_half % 2:
+                pool.sort(key=lambda r: -r[2])
+                for cand in pool:
+                    if cand[1] == half and cand[0] not in chosen:
+                        chosen[cand[0]] = (cand[2], cand[3])
+                        report.append(
+                            f"blk.{layer}: half {half} odd -> added e{cand[0]} "
+                            f"(energy {cand[2]*100:.2f}%)")
+                        break
+        for e in sorted(chosen):
+            es, rs = chosen[e]
+            lines.append(f"blk.{layer}.ffn_*_exps.{e}.weight"
+                         f"         cast dtype=bf16")
+            report.append(f"blk.{layer} e{e:3d} (rank {e // 256}): "
+                          f"energy {es*100:5.2f}%, routing {rs*100:5.3f}%, "
+                          f"ratio {es/max(rs,1e-12):6.1f}")
+        total += len(chosen)
+
+    print("\n".join(lines))
+    print("\n".join(report), file=sys.stderr)
+    print(f"total protected: {total}", file=sys.stderr)
+
+
+if __name__ == "__main__":
+    main()

scripts/docker/frank-primary-freetoken.Dockerfile

@@ -1,63 +0,0 @@
-# frank-primary-freetoken.Dockerfile — FreeToken (PR #587 ROCm) serving image
-# for the frank-primary endpoint (dankserver :7770, 1x R9700 gfx1201).
-#
-# Built on dankserver with rootless podman (dank user), same storage the
-# service's `podman run` reads:
-#   podman build -t frank-primary-freetoken:pr587-77a7201 \
-#     -f scripts/docker/frank-primary-freetoken.Dockerfile scripts/docker/
-#
-# Base: the PR's own docs/install_amd.md names this exact image as the
-# known-good ROCm 7.14 stack for gfx1201 (torch 2.11.0+rocm7.14, triton-rocm
-# 3.7 — the original pin; FreeToken main+PR587 accepts torch>=2.11,<2.16 and
-# triton>=3.6,<3.9). There is no rocm7.14+torch2.14 image on Docker Hub (the
-# 2.14 images are rocm10.1.0 — an untested pair for this PR), so the PR doc's
-# verbatim recommendation is the deployed stack.
-#
-# FreeToken source: FlashML-org/FreeToken PR #587 at pinned head
-# 77a7201f98f00d93f618c6cf8b81ffe8360e0899 (branch rocm714_torch214, base
-# main 581fdca3). The PR is ROCm-gated end to end; the NVIDIA/CUDA path is
-# byte-identical to main.
-#
-# Build law from docs/install_amd.md:
-#   - `pip install --no-build-isolation --no-deps -e .` — the image's ROCm
-#     torch is preserved and used to compile the C++/HIP extensions.
-#   - NEVER a plain `pip install -e .` on ROCm: the dependency set is
-#     authored for NVIDIA (flashlib pulls numba + nvidia-cutlass-dsl; torch
-#     metadata pulls cuda-bindings) and the resolve can REPLACE the ROCm
-#     torch with a CUDA build.
-#   - Runtime deps installed explicitly, curated by the same doc. flashinfer
-#     / sgl_kernel / nvidia-cutlass-dsl have no ROCm builds and are
-#     intentionally absent — FreeToken gates them off and falls back to its
-#     Triton kernels on ROCm.
-#
-# Base is digest-pinned (2026-10-05): sha256:a223aee1… is the manifest this
-# build was qualified against; a re-pushed tag cannot change the stack. The
-# readable tag rides along for humans (podman verifies the digest matches).
-FROM rocm/pytorch:rocm7.14_ubuntu24.04_py3.12_pytorch_release_2.11.0@sha256:a223aee17aef5d21c3b9f63436dd19d27d1c665ec8b2f40011c9546cabae2a80
-
-# Pin the PR head, not the branch: a future push to rocm714_torch214 would
-# otherwise silently change the deployed engine.
-# The pip-ROCm torch in this image ships libhiprtc as the VERSIONED
-# libhiprtc.so.7 only; the PR's `_cpu_moe` extension links `-lhiprtc`, and
-# ld looks for the unversioned dev symlink in the ALREADY-LINKED
-# _rocm_sdk_core/lib dir. Create it there (first build failure 2026-10-05:
-# `ld: cannot find -lhiprtc`).
-RUN ln -s libhiprtc.so.7 /opt/venv/lib/python3.12/site-packages/_rocm_sdk_core/lib/libhiprtc.so
-RUN git clone https://github.com/FlashML-org/FreeToken.git /opt/FreeToken \
- && cd /opt/FreeToken \
- && git fetch origin pull/587/head \
- && git checkout 77a7201f98f00d93f618c6cf8b81ffe8360e0899
-
-WORKDIR /opt/FreeToken
-RUN python -m pip install --no-build-isolation --no-deps -e .
-
-# Curated runtime dependencies (docs/install_amd.md). transformers is pinned
-# to the pyproject window (>=5.16,<5.17); the rest are the doc's portable set.
-# torch / torchvision / triton-rocm come from the base image, 1:1 aligned.
-RUN python -m pip install \
-      "transformers>=5.16,<5.17" tokenizers safetensors huggingface_hub \
-      fastapi uvicorn pydantic openai httpx anyio \
-      einops gguf msgpack pyzmq typer rich apache-tvm-ffi \
-      partial-json-parser \
- && python -m pip install --no-deps flashlib==0.3.0 \
- && python -m pip install ninja

scripts/download-frank-archon-swift15.sh

@@ -0,0 +1,113 @@
+#!/usr/bin/env bash
+# download-frank-archon-swift15.sh — payload fetch/verify for the planned
+# frank-archon swap to the Swift 1.5 finetune: ukisai/Swift1.5-Qwen3.8-Flash-Next
+# (BF16 source, 149 files, 360,037,355,038 bytes = 335.3 GiB: 131 safetensors
+# shards + weight-map index + tokenizer + vision preprocessing configs + chat
+# template + licenses). Key set verified identical to the official
+# Qwen/Qwen3.8-Flash-Next base (0 added / 0 missing), so the qwen4exp recipes
+# apply verbatim; the checkpoint ships BF16 with NO quantization_config.
+# Repo is UNGATED — no token needed (never put one on the command line).
+#
+#   bash scripts/download-frank-archon-swift15.sh --fetch         resume/complete
+#   bash scripts/download-frank-archon-swift15.sh                 verify only
+#
+# Fetch uses the vendored scripts/hfget.sh (StillDeadcode's Apache-2.0
+# listing/resume downloader, curl+jq only): per-file size checks against
+# the Hub listing, `-C -` resume, pickle-format duplicates skipped.
+# Verify (default) is the AGENTS.md law in three parts: every listed file
+# present with the listed size, the shard count matches the weight-map
+# index, and every shard's sha256 equals the Hub's LFS oid. Verify needs
+# only the public API.
+set -euo pipefail
+
+REPO="ukisai/Swift1.5-Qwen3.8-Flash-Next"
+DEST="/home/dank/models/ukisai/Swift1.5-Qwen3.8-Flash-Next"
+EXPECTED_SHARDS=131
+
+mode="verify"
+[[ "${1:-}" == "--fetch" ]] && mode="fetch"
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+
+if [[ "$mode" == "fetch" ]]; then
+    # HFGET_JOBS=4 is hfget's default (a few streams saturate the link).
+    bash "$SCRIPT_DIR/hfget.sh" "$REPO" "$DEST" main
+fi
+
+echo "verifying local payload: $DEST"
+fail=0
+
+INDEX="$DEST/model.safetensors.index.json"
+if [[ ! -f "$INDEX" ]]; then
+    echo "  BAD  weight-map index missing: $INDEX" >&2
+    exit 1
+fi
+
+python3 - "$REPO" "$DEST" <<'PY' || fail=1
+import hashlib, json, os, sys, urllib.request
+
+repo, dest = sys.argv[1], sys.argv[2]
+
+def listing():
+    """The tree API, following the Link cursor exactly like hfget.sh."""
+    out, api, pages = [], (
+        f"https://huggingface.co/api/models/{repo}/tree/main"
+        "?recursive=true&expand=true"), 0
+    while api:
+        with urllib.request.urlopen(api) as r:
+            out += json.load(r)
+            api = None
+            link = r.headers.get("Link", "")
+            for part in link.split(","):
+                if 'rel="next"' in part:
+                    api = part[part.find("<") + 1:part.find(">")]
+        pages += 1
+        if pages > 200:
+            raise SystemExit("listing did not terminate")
+    return out
+
+files = [e for e in listing() if e.get("type") == "file"]
+sizes = {e["path"]: e.get("size", 0) for e in files}
+lfs = {e["path"]: e["lfs"]["oid"] for e in files if e.get("lfs")}
+
+bad = 0
+for path, want in sorted(sizes.items()):
+    p = os.path.join(dest, path)
+    if not os.path.isfile(p):
+        print(f"  BAD  {path}: missing")
+        bad += 1
+    elif os.path.getsize(p) != want:
+        print(f"  BAD  {path}: {os.path.getsize(p)} bytes, listing says {want}")
+        bad += 1
+print(f"  {'OK' if bad == 0 else 'FAIL'}: {len(sizes) - bad}/{len(sizes)} files present at listed size")
+if bad:
+    raise SystemExit(1)
+
+# Shard set against the weight-map index.
+wm = json.load(open(os.path.join(dest, "model.safetensors.index.json")))["weight_map"]
+shards = sorted(set(wm.values()))
+print(f"  index maps {len(wm)} tensors across {len(shards)} shards")
+if len(shards) != 131:
+    print(f"  BAD  shard count {len(shards)}, want 131")
+    raise SystemExit(1)
+
+# Content: every LFS-tracked file hashed against the Hub oid. The safetensors
+# shards dominate the bytes; tokenizer/config files ride the same check when
+# the Hub tracks them in LFS (they are plain blobs here, already size-checked).
+todo = [p for p in shards if p in lfs]
+for i, path in enumerate(todo):
+    h = hashlib.sha256()
+    with open(os.path.join(dest, path), "rb") as f:
+        for chunk in iter(lambda: f.read(1 << 24), b""):
+            h.update(chunk)
+    if h.hexdigest() != lfs[path]:
+        print(f"  BAD  {path}: sha256 mismatch (want {lfs[path]})")
+        bad += 1
+    if (i + 1) % 16 == 0:
+        print(f"  ...hashed {i + 1}/{len(todo)}")
+print(f"  {'OK' if bad == 0 else 'FAIL'}: {len(todo) - bad}/{len(todo)} shards sha256-match the Hub")
+if bad:
+    raise SystemExit(1)
+PY
+
+[[ "$fail" -eq 0 ]] || exit 1
+echo "payload verified: 131 shards + index + tokenizer + configs, sizes and sha256 checked"

scripts/download-frank-archon.sh

@@ -0,0 +1,111 @@
+#!/usr/bin/env bash
+# download-frank-archon.sh — payload fetch/verify for frank-archon:
+# the OFFICIAL Qwen/Qwen3.8-Flash-Next-FP8 checkpoint (131 safetensors
+# shards + weight-map index + tokenizer + vision preprocessing configs,
+# ~172.8 GB). 2026-10-05: replaces the orcarouter uncensored payload of the
+# FreeToken era (that script lived here; its repo was gated and needed
+# HF_TOKEN — this one is UNGATED and needs no token at all).
+#
+#   bash scripts/download-frank-archon.sh --fetch         resume/complete
+#   bash scripts/download-frank-archon.sh                 verify only
+#
+# Fetch uses the vendored scripts/hfget.sh (StillDeadcode's Apache-2.0
+# listing/resume downloader, curl+jq only): per-file size checks against
+# the Hub listing, `-C -` resume, pickle-format duplicates skipped.
+# Verify (default) is the AGENTS.md law in three parts: every listed file
+# present with the listed size, the shard count matches the weight-map
+# index, and every shard's sha256 equals the Hub's LFS oid. Verify needs
+# only the public API.
+set -euo pipefail
+
+REPO="Qwen/Qwen3.8-Flash-Next-FP8"
+DEST="/home/dank/models/Qwen/Qwen3.8-Flash-Next-FP8"
+EXPECTED_SHARDS=131
+
+mode="verify"
+[[ "${1:-}" == "--fetch" ]] && mode="fetch"
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+
+if [[ "$mode" == "fetch" ]]; then
+    # HFGET_JOBS=4 is hfget's default (a few streams saturate the link).
+    bash "$SCRIPT_DIR/hfget.sh" "$REPO" "$DEST" main
+fi
+
+echo "verifying local payload: $DEST"
+fail=0
+
+INDEX="$DEST/model.safetensors.index.json"
+if [[ ! -f "$INDEX" ]]; then
+    echo "  BAD  weight-map index missing: $INDEX" >&2
+    exit 1
+fi
+
+python3 - "$REPO" "$DEST" <<'PY' || fail=1
+import hashlib, json, os, sys, urllib.request
+
+repo, dest = sys.argv[1], sys.argv[2]
+
+def listing():
+    """The tree API, following the Link cursor exactly like hfget.sh."""
+    out, api, pages = [], (
+        f"https://huggingface.co/api/models/{repo}/tree/main"
+        "?recursive=true&expand=true"), 0
+    while api:
+        with urllib.request.urlopen(api) as r:
+            out += json.load(r)
+            api = None
+            link = r.headers.get("Link", "")
+            for part in link.split(","):
+                if 'rel="next"' in part:
+                    api = part[part.find("<") + 1:part.find(">")]
+        pages += 1
+        if pages > 200:
+            raise SystemExit("listing did not terminate")
+    return out
+
+files = [e for e in listing() if e.get("type") == "file"]
+sizes = {e["path"]: e.get("size", 0) for e in files}
+lfs = {e["path"]: e["lfs"]["oid"] for e in files if e.get("lfs")}
+
+bad = 0
+for path, want in sorted(sizes.items()):
+    p = os.path.join(dest, path)
+    if not os.path.isfile(p):
+        print(f"  BAD  {path}: missing")
+        bad += 1
+    elif os.path.getsize(p) != want:
+        print(f"  BAD  {path}: {os.path.getsize(p)} bytes, listing says {want}")
+        bad += 1
+print(f"  {'OK' if bad == 0 else 'FAIL'}: {len(sizes) - bad}/{len(sizes)} files present at listed size")
+if bad:
+    raise SystemExit(1)
+
+# Shard set against the weight-map index.
+wm = json.load(open(os.path.join(dest, "model.safetensors.index.json")))["weight_map"]
+shards = sorted(set(wm.values()))
+print(f"  index maps {len(wm)} tensors across {len(shards)} shards")
+if len(shards) != 131:
+    print(f"  BAD  shard count {len(shards)}, want 131")
+    raise SystemExit(1)
+
+# Content: every LFS-tracked file hashed against the Hub oid. The safetensors
+# shards dominate the bytes; tokenizer/config files ride the same check when
+# the Hub tracks them in LFS (they are plain blobs here, already size-checked).
+todo = [p for p in shards if p in lfs]
+for i, path in enumerate(todo):
+    h = hashlib.sha256()
+    with open(os.path.join(dest, path), "rb") as f:
+        for chunk in iter(lambda: f.read(1 << 24), b""):
+            h.update(chunk)
+    if h.hexdigest() != lfs[path]:
+        print(f"  BAD  {path}: sha256 mismatch (want {lfs[path]})")
+        bad += 1
+    if (i + 1) % 16 == 0:
+        print(f"  ...hashed {i + 1}/{len(todo)}")
+print(f"  {'OK' if bad == 0 else 'FAIL'}: {len(todo) - bad}/{len(todo)} shards sha256-match the Hub")
+if bad:
+    raise SystemExit(1)
+PY
+
+[[ "$fail" -eq 0 ]] || exit 1
+echo "payload verified: 131 shards + index + tokenizer + configs, sizes and sha256 checked"

scripts/download-frank-dragoon-flashnext.sh

@@ -0,0 +1,119 @@
+#!/usr/bin/env bash
+# download-frank-dragoon-flashnext.sh — fetch frank-dragoon's flash-server v2
+# payload: the Quat3rnion abliterated Swift1.5 checkpoint of peonist's v2
+# .hgn, the REQUIRED lookup table and the optional vision tower from
+# peonist-ai/halogen-qwen3.8-flash-next (both at the revisions the model
+# card pins), and the flat tokenizer the two repos share. All public, no
+# token — and per the fleet secret law, none would ever touch argv.
+#
+# The fetch law, same as every sibling script: curl -f (an access error
+# must not become a "successful" 153-byte artifact), exact byte count from
+# the Hub tree API, LFS sha256 verification, --verify-only to re-check an
+# existing payload without downloading.
+#
+# File manifest (verified against the Hub tree API on 2026-10-06):
+#   qwen38-flash-next-v2-swift15-abliterated.hgn  66,687,678,464 B  sha256
+#     9c880b8ba48deabfa06172eff1e7572e4fe465e09e97faec6e50c3f6fdcac037
+#     (Quat3rnion main; compacted r2 of the card's 89,775,868,032 B
+#     append-only original — byte-identical live tensors, dropped padding)
+#   qwen38-flash-next-ngram.hgn  51,200,246,144 B  sha256
+#     3450acada94e19aabad88bd49b45eb70304820949c2240fc178067b20ae5dffe
+#     (peonist @5cc17cea; REQUIRED — the engine reads it beside the
+#     checkpoint)
+#   qwen38-flash-next-vision.hgn  897,916,416 B  sha256
+#     d62e0ae553fe88afd3833733d4a4c669f34d20fd8dfce4b9610525bed2134b10
+#     (peonist @e053f488; optional, enables image input)
+#   tokenizer/* @e053f488 — byte-identical to the 27B-era tokenizer
+#     already on disk (tokenizer.json LFS
+#     0997f410c57a1f4e53b09e4be8f4a172d90edd9564368fb0847030937229b9f3);
+#     fetched fresh rather than symlinked, per the no-symlink law.
+set -euo pipefail
+
+DEST="${FRANK_DRAGOON_MODEL_DIR:-$HOME/models/halogen-flashnext-v2}"
+ABLIT="https://huggingface.co/Quat3rnion/halogen-swift1.5-qwen3.8-flash-next-v2-abliterated/resolve/main"
+PEONIST="https://huggingface.co/peonist-ai/halogen-qwen3.8-flash-next/resolve"
+NGRAM_REV="5cc17cea1a10b502b4a5db41d8d2b1a0f22dba26"
+TOK_REV="e053f488b120b99ed2525e6ac99f68c51b3b6179"
+
+FILES=(qwen38-flash-next-v2-swift15-abliterated.hgn
+       qwen38-flash-next-ngram.hgn
+       qwen38-flash-next-vision.hgn
+       tokenizer/tokenizer.json
+       tokenizer/chat_template.jinja
+       tokenizer/generation_config.json
+       tokenizer/merges.txt
+       tokenizer/vocab.json
+       tokenizer/tokenizer_config.json)
+SIZES=(66687678464
+       51200246144
+       897916416
+       12809320
+       8952
+       202
+       3353259
+       6722759
+       17928)
+SHAS=(9c880b8ba48deabfa06172eff1e7572e4fe465e09e97faec6e50c3f6fdcac037
+      3450acada94e19aabad88bd49b45eb70304820949c2240fc178067b20ae5dffe
+      d62e0ae553fe88afd3833733d4a4c669f34d20fd8dfce4b9610525bed2134b10
+      0997f410c57a1f4e53b09e4be8f4a172d90edd9564368fb0847030937229b9f3
+      - - - - - -)
+
+# Fetch source per file: repo base + revision (empty = ABLIT @main).
+SRCS=("$ABLIT"
+      "$PEONIST/$NGRAM_REV"
+      "$PEONIST/$TOK_REV"
+      "$PEONIST/$TOK_REV"
+      "$PEONIST/$TOK_REV"
+      "$PEONIST/$TOK_REV"
+      "$PEONIST/$TOK_REV"
+      "$PEONIST/$TOK_REV"
+      "$PEONIST/$TOK_REV")
+
+VERIFY_ONLY=0
+[ "${1:-}" = "--verify-only" ] && VERIFY_ONLY=1
+
+mkdir -p "$DEST"
+
+for i in "${!FILES[@]}"; do
+    f="${FILES[$i]}"; want="${SIZES[$i]}"; sha="${SHAS[$i]}"; base="${SRCS[$i]}"
+    path="$DEST/$f"
+    mkdir -p "$(dirname "$path")"
+    if [ "$VERIFY_ONLY" -eq 0 ]; then
+        # A file already at the published size skips the fetch entirely:
+        # resuming it would ask the CDN for a range past EOF (416 -> curl
+        # error under set -e), and re-pulling 62 GiB to prove a point is
+        # not what --verify-only is for. sha256 below still decides.
+        if [ -f "$path" ] && [ "$(stat -c %s "$path")" = "$want" ]; then
+            echo "HAVE  $f ($want bytes) — skipping fetch"
+        else
+            echo "FETCH $f -> $path"
+            # HF answers /resolve/ with a 302 to the Xet CDN and curl DROPS
+            # the Range header across redirects — a naive -C - then
+            # "resumes" by pulling the ~1 KB redirect body (measured
+            # 2026-10-05 on the 27B fetch: file frozen 14 MiB short, curl
+            # exit 0). Resolve the effective URL first, then resume
+            # against the CDN, which honors Range.
+            url=$(curl -sfIL -o /dev/null -w '%{url_effective}' "$base/$f") \
+                || { echo "cannot resolve $base/$f" >&2; exit 1; }
+            curl -fL --retry 5 -C - -o "$path" "$url"
+        fi
+    fi
+    [ -f "$path" ] || { echo "MISSING $path (run without --verify-only)" >&2; exit 1; }
+    got="$(stat -c %s "$path")"
+    [ "$got" = "$want" ] || { echo "SIZE $path: $got != $want" >&2; exit 1; }
+    echo "OK   $f ($got bytes)"
+done
+
+echo "byte counts match; verifying sha256 where the Hub publishes an LFS oid..."
+for i in "${!FILES[@]}"; do
+    f="${FILES[$i]}"; sha="${SHAS[$i]}"
+    if [ "$sha" = "-" ]; then
+        echo "OK   $f (plain git blob, size-checked)"
+        continue
+    fi
+    got="$(sha256sum "$DEST/$f" | cut -d' ' -f1)"
+    [ "$got" = "$sha" ] || { echo "SHA256 $f: $got != $sha" >&2; exit 1; }
+    echo "OK   $f sha256"
+done
+echo "DOWNLOAD_DONE $DEST"

scripts/download-frank-dragoon-halogen.sh

@@ -1,5 +1,5 @@
 #!/usr/bin/env bash
-# download-frank-large-halogen.sh — fetch frank-large's halogen payload:
+# download-frank-dragoon-halogen.sh — fetch frank-dragoon's halogen payload:
 # the qwen3.8-27b .hgn checkpoint and the export tokenizer, from the
 # PUBLIC peonist-ai/halogen-qwen3.8-27b repo (no token — and per the fleet
 # secret law, none would ever touch argv).
@@ -10,7 +10,7 @@
 # existing payload without downloading.
 set -euo pipefail
 
-DEST="${FRANK_LARGE_MODEL_DIR:-$HOME/models/halogen-qwen3.8-27b}"
+DEST="${FRANK_DRAGOON_MODEL_DIR:-$HOME/models/halogen-qwen3.8-27b}"
 BASE="https://huggingface.co/peonist-ai/halogen-qwen3.8-27b/resolve/main"
 
 FILES=(qwen3.8-27b-p1w4d-d2.hgn

scripts/download-frank-dragoon-kingjones-uncensored.sh

@@ -1,6 +1,6 @@
 #!/usr/bin/env bash
 # Download kingjones777/Qwen3.8-27B-Uncensored-ROCmFP4-STRIX-MTP-GGUF for
-# frank-large (Dankclaw iGPU). Public repo — no auth header, and never a token
+# frank-dragoon (Dankclaw iGPU). Public repo — no auth header, and never a token
 # on the command line (it is world-readable in /proc/<pid>/cmdline).
 #
 # The payload is the repo's Q6 AGENT rung:
@@ -10,7 +10,7 @@
 #     names for MTP serving ("Take Q6 AGENT (114) if you want protected
 #     heads"). Like every ROCmFPX file it loads on nothing but the fork.
 #
-# The other two files frank-large needs are NOT re-downloaded:
+# The other two files frank-dragoon needs are NOT re-downloaded:
 #   * mtp-Qwen3.8-27B-Q4_0.gguf — the uncensored repo redistributes the
 #     ALIGNED repo's draft head byte for byte (identical Hub LFS oid
 #     051a1764…), so it is hardlinked out of the aligned payload dir when that
@@ -25,7 +25,7 @@
 # byte count and the Hub LFS sha256. Idempotent: complete files are skipped.
 #
 # Usage:
-#   scripts/download-frank-large-kingjones-uncensored.sh [DEST_DIR] [--verify-only]
+#   scripts/download-frank-dragoon-kingjones-uncensored.sh [DEST_DIR] [--verify-only]
 set -euo pipefail
 
 REPO="kingjones777/Qwen3.8-27B-Uncensored-ROCmFP4-STRIX-MTP-GGUF"

scripts/download-frank-dragoon-kingjones.sh

@@ -1,5 +1,5 @@
 #!/usr/bin/env bash
-# Download kingjones777/Qwen3.8-27B-ROCmFP4-STRIX-MTP-GGUF for frank-large
+# Download kingjones777/Qwen3.8-27B-ROCmFP4-STRIX-MTP-GGUF for frank-dragoon
 # (Dankclaw iGPU). Public repo — no auth header, and never a token on the
 # command line (it is world-readable in /proc/<pid>/cmdline).
 #
@@ -24,7 +24,7 @@
 # come from the Hub LFS oids (api/models/<repo>/tree/main).
 #
 # Usage:
-#   scripts/download-frank-large-kingjones.sh [DEST_DIR] [--verify-only]
+#   scripts/download-frank-dragoon-kingjones.sh [DEST_DIR] [--verify-only]
 set -euo pipefail
 
 REPO="kingjones777/Qwen3.8-27B-ROCmFP4-STRIX-MTP-GGUF"

scripts/download-frank-dragoon-orca.sh

@@ -1,9 +1,9 @@
 #!/usr/bin/env bash
-# Download and assemble jcbtc/Qwen3.8-Flash-CIRU-STRIX-Orca (the frank-large
+# Download and assemble jcbtc/Qwen3.8-Flash-CIRU-STRIX-Orca (the frank-dragoon
 # model) on Dankclaw.
 #
-#   bash scripts/download-frank-large-orca.sh
-#   bash scripts/download-frank-large-orca.sh --verify-only
+#   bash scripts/download-frank-dragoon-orca.sh
+#   bash scripts/download-frank-dragoon-orca.sh --verify-only
 #
 # The package is 136 GB of Hub-sized transport parts (HF caps new uploads at
 # 50 GB, so the 79 GB main GGUF, the 52 GB PLE payload and the 4 GB MTP head
@@ -105,4 +105,4 @@ fi
 echo "verifying assembled files against SHA256SUMS"
 (cd "$MODEL_DIR" && sha256sum -c SHA256SUMS)
 (cd "$MODEL_DIR/vision" && sha256sum -c SHA256SUMS)
-echo "frank-large payload complete: $MODEL_DIR"
+echo "frank-dragoon payload complete: $MODEL_DIR"

scripts/download-frank-dragoon-q4.sh

@@ -1,9 +1,9 @@
 #!/usr/bin/env bash
-# Download the Q4_K_XL frank-large payload on Dankclaw:
+# Download the Q4_K_XL frank-dragoon payload on Dankclaw:
 #   unsloth/Qwen3.8-27B-GGUF  ->  Qwen3.8-27B-UD-Q4_K_XL.gguf
 #
-#   bash scripts/download-frank-large-q4.sh
-#   bash scripts/download-frank-large-q4.sh --verify-only
+#   bash scripts/download-frank-dragoon-q4.sh
+#   bash scripts/download-frank-dragoon-q4.sh --verify-only
 #
 # Integrity: the file is checked against its declared byte count and sha256
 # (the LFS oid from the Hub tree API, 2026-10-01). NO AUTH HEADER IS USED:
@@ -21,12 +21,12 @@
 # x 2 (K,V) x 2 B), so 4 sessions x 163840 ctx = 640,000 tokens = 39.06 GiB.
 #
 # The speculative drafter is UNCHANGED and still fetched by its own script
-# (scripts/download-frank-large.sh, z-lab's Hub repo). That name must not
-# appear here at all — the frank-large seam greps THIS file for it to prove
+# (scripts/download-frank-dragoon.sh, z-lab's Hub repo). That name must not
+# appear here at all — the frank-dragoon seam greps THIS file for it to prove
 # the drafter was not folded into the payload fetch.
 #
 # NOTE ON MTP: this payload has no baked-in MTP head (the Hub repo ships one
-# separately as MTP/mtp-Qwen3.8-27B-Q4_0.gguf). frank-large does not need it —
+# separately as MTP/mtp-Qwen3.8-27B-Q4_0.gguf). frank-dragoon does not need it —
 # spec decode here is the block-diffusion drafter, not MTP.
 set -euo pipefail
 

scripts/download-frank-dragoon-swift.sh

@@ -1,10 +1,10 @@
 #!/usr/bin/env bash
-# Download the Swift-1.5 frank-large candidate on Dankclaw:
+# Download the Swift-1.5 frank-dragoon candidate on Dankclaw:
 #   ajgazin/Swift-1.5-Qwen3.8-27B-Uncensored-Dynamic-MTP-GGUF
 #     Swift-1.5-Qwen3.8-27B-Uncensored-Dynamic-MTP-UD-Q8_K_XL.gguf
 #
-#   bash scripts/download-frank-large-swift.sh
-#   bash scripts/download-frank-large-swift.sh --verify-only
+#   bash scripts/download-frank-dragoon-swift.sh
+#   bash scripts/download-frank-dragoon-swift.sh --verify-only
 #
 # Integrity: the file is checked against its declared byte count and sha256
 # (the LFS oid from the Hub, 2026-09-28). NO AUTH HEADER IS USED: the repo is
@@ -15,9 +15,9 @@
 # Layout after a successful run (MODEL_DIR):
 #   Swift-1.5-Qwen3.8-27B-Uncensored-Dynamic-MTP-UD-Q8_K_XL.gguf  31457990272
 #
-# This is the CANDIDATE payload, not the deployed one. frank-large still
-# serves scripts/download-frank-large.sh's output; do not repoint
-# frank-large.env at MODEL_DIR until the gufo load test passes.
+# This is the CANDIDATE payload, not the deployed one. frank-dragoon still
+# serves scripts/download-frank-dragoon.sh's output; do not repoint
+# frank-dragoon.env at MODEL_DIR until the gufo load test passes.
 set -euo pipefail
 
 MODEL_DIR="/home/dank/models/Swift-1.5-Qwen3.8-27B-Uncensored-MTP-UD-Q8_K_XL"

scripts/download-frank-dragoon-unsloth.sh

@@ -1,9 +1,9 @@
 #!/usr/bin/env bash
 # Download unsloth/Qwen3.8-Flash-Next-GGUF:UD-IQ4_XS (the
-# frank-large model) on Dankclaw.
+# frank-dragoon model) on Dankclaw.
 #
-#   bash scripts/download-frank-large-unsloth.sh
-#   bash scripts/download-frank-large-unsloth.sh --verify-only
+#   bash scripts/download-frank-dragoon-unsloth.sh
+#   bash scripts/download-frank-dragoon-unsloth.sh --verify-only
 #
 # The UD-IQ4_XS GGUF ships as three llama.cpp split parts (HF caps uploads at
 # 50 GB). The parts ARE the canonical payload: the serve script points -m at
@@ -112,4 +112,4 @@ if [[ "$mode" == "download" ]]; then
     [[ -e "$MODEL_DIR/vision/mmproj-F16.gguf" ]] || mv "$MODEL_DIR/mmproj-F16.gguf" "$MODEL_DIR/vision/"
 fi
 
-echo "frank-large payload complete: $MODEL_DIR"
+echo "frank-dragoon payload complete: $MODEL_DIR"

scripts/download-frank-dragoon.sh

@@ -1,10 +1,10 @@
 #!/usr/bin/env bash
-# Download the frank-large payload on Dankclaw:
+# Download the frank-dragoon payload on Dankclaw:
 #   - unsloth/Qwen3.8-27B-GGUF:UD-Q8_K_XL (the 27B dense main GGUF)
 #   - z-lab/Qwen3.8-27B-DFlash2-GGUF:Q4_K_M (the DFlash2 drafter)
 #
-#   bash scripts/download-frank-large.sh
-#   bash scripts/download-frank-large.sh --verify-only
+#   bash scripts/download-frank-dragoon.sh
+#   bash scripts/download-frank-dragoon.sh --verify-only
 #
 # Integrity: every file is checked against its declared byte count and sha256
 # (the values below are the LFS oids from the Hub, 2026-09-21). An HF token
@@ -86,4 +86,4 @@ if [[ "$mode" == "download" ]]; then
     done
 fi
 
-echo "frank-large payload complete: $MODEL_DIR"
+echo "frank-dragoon payload complete: $MODEL_DIR"

scripts/download-frank-primary.sh

@@ -1,88 +0,0 @@
-#!/usr/bin/env bash
-# Payload inventory/verification for frank-primary:
-# orcarouter/Qwen3.8-Flash-Next-Uncensored-FP8 (compressed-tensors FP8, 131
-# shards + weight-map index, ~172.8 GiB) — the tcclaviger-stack payload that
-# became frank-primary on 2026-09-29.
-#
-#   bash scripts/download-frank-primary.sh --verify-only   (the ONLY mode)
-#   bash scripts/download-frank-primary.sh --fetch
-#
-# THIS REPO IS GATED (401 anonymous — measured 2026-09-29): anonymous fetch
-# is impossible and the tree API masks LFS hashes, so a byte-exact upstream
-# manifest cannot be built without the authed endpoint. The payload on
-# /home/dank/models was fetched with the operator's HF token (out of band:
-# HF_TOKEN in the environment, never in argv) at bring-up time.
-#
-# Modes:
-#   --fetch       resume any missing/truncated shard via `hf download` with
-#                 HF_TOKEN from the environment (NEVER passed on the command
-#                 line — a -H auth header is world-readable in
-#                 /proc/<pid>/cmdline, the 2026-09-16 leak).
-#   --verify-only default: local integrity check — shard count vs the
-#                 weight-map index, every file nonzero and its size equal to
-#                 the index's declared total, plus sha256 of every shard
-#                 (slow, ~10 min for 173 GiB).
-set -euo pipefail
-
-REPO="orcarouter/Qwen3.8-Flash-Next-Uncensored-FP8"
-DEST="/home/dank/models/Qwen3.8-Flash-Next-Uncensored-FP8"
-EXPECTED_SHARDS=131
-
-mode="verify"
-[[ "${1:-}" == "--fetch" ]] && mode="fetch"
-
-if [[ "$mode" == "fetch" ]]; then
-    : "${HF_TOKEN:?--fetch needs HF_TOKEN in the environment (never argv)}"
-    export HF_TOKEN
-    mkdir -p "$DEST"
-    hf download "$REPO" --local-dir "$DEST"
-fi
-
-echo "verifying local payload: $DEST"
-fail=0
-
-# The weight-map index is the source of truth for the shard set.
-INDEX="$DEST/model.safetensors.index.json"
-if [[ ! -f "$INDEX" ]]; then
-    echo "  BAD  weight-map index missing: $INDEX" >&2
-    exit 1
-fi
-
-# Every index entry must exist, nonzero, and sized equal to the map's total.
-python3 - "$INDEX" "$DEST" <<'PY' || fail=1
-import json, os, sys
-index, dest = sys.argv[1], sys.argv[2]
-wm = json.load(open(index))["weight_map"]
-files = sorted(set(wm.values()))
-print(f"  index maps {len(wm)} tensors across {len(files)} files")
-bad = 0
-total = 0
-for f in files:
-    p = os.path.join(dest, f)
-    if not os.path.isfile(p) or os.path.getsize(p) == 0:
-        print(f"  BAD  {f}: missing or zero bytes" )
-        bad += 1
-    else:
-        total += os.path.getsize(p)
-print(f"  {'OK' if bad == 0 else 'FAIL'}: {len(files) - bad}/{len(files)} files present, {total/2**30:.1f} GiB total")
-raise SystemExit(1 if bad else 0)
-PY
-
-# Shard count gate (what the serve script and deployer check).
-n="$(find "$DEST" -maxdepth 1 -name 'model-*-of-*.safetensors' | wc -l)"
-if [[ "$n" != "$EXPECTED_SHARDS" ]]; then
-    echo "  BAD  shard count: found $n, want $EXPECTED_SHARDS" >&2
-    fail=1
-else
-    echo "  OK   shard count $n"
-fi
-
-if [[ "${2:-}" == "--hash" || "${VERIFY_HASH:-0}" == "1" ]]; then
-    echo "hashing every shard (slow)..."
-    cd "$DEST"
-    sha256sum -c --quiet model.safetensors.index.json 2>/dev/null || \
-    sha256sum model-*-of-00131.safetensors > /dev/null  # presence check; content hash list printed on demand
-fi
-
-[[ "$fail" -eq 0 ]] || exit 1
-echo "payload inventory OK: $EXPECTED_SHARDS shards + index present"

scripts/download-frank-small.sh

@@ -1,87 +0,0 @@
-#!/usr/bin/env bash
-# Download the frank-small payload for llama.cpp on the RTX 3090:
-# ornith-ai/Ornith-1.5-9B-GGUF:Q8_0 plus its vision projector
-# (the GGUF carries no `v.*` tensors — the tower lives only in the mmproj, so
-# without this file the endpoint is text-only by construction). Public repo —
-# no auth header, and never a token on the command line (it is world-readable
-# in /proc/<pid>/cmdline).
-#
-# Fresh downloads, no resume (`curl -C -` once produced a 213 MB oversized file
-# on a 31 GiB payload); -f/--fail-with-body so an HTTP 401 is not a success,
-# then byte count and the Hub LFS sha256. Idempotent: complete files are
-# skipped.
-#
-# 2026-10-05 (Frank): the rung is Ornith-1.5-9B Q8_0. The payload moved off
-# MiMo-V2.6 (Q6_K) to Ornith because it is the fleet's own model and it is the
-# only one the harness's own prompt recipes were written against; Q8_0 was the
-# rung chosen so the quant does not cost the throughput this endpoint already
-# runs at. The Q5_K_M file this script served from 2026-10-02 stays on disk at
-# /home/dank/models/MiMo-Q5KM/ (6876124704 B, LFS oid
-# 04cf46f2b5584ef922697d6c063f94879434fb86c467f1a09e52daf0cddaf35f) as the
-# rollback target; re-fetch it from the same repo with the same recipe.
-#
-# Usage:
-#   scripts/download-frank-small.sh [DEST_DIR] [--verify-only]
-set -euo pipefail
-
-REPO="ornith-ai/Ornith-1.5-9B-GGUF"
-BASE="https://huggingface.co/${REPO}/resolve/main"
-
-DEST=""
-VERIFY_ONLY=0
-for arg in "$@"; do
-    case "$arg" in
-        --verify-only) VERIFY_ONLY=1 ;;
-        *) DEST="$arg" ;;
-    esac
-done
-DEST="${DEST:-/home/dank/models/Ornith-Q8}"
-
-# name bytes sha256 (the sha256 is the LFS oid in the repo's pointer file)
-FILES=(
-  "Ornith-1.5-9B-Q8_0.gguf 9786060384 22086870b009dbe9815ee752c48a82de930118a7c5ce5599590892ae03b8b010"
-  "mmproj-Ornith-1.5-9B-BF16.gguf 921704672 626f9f90627402a6bf4a999111d0fbd69b5fcca7aa8ba089d69e5f10e8858e1d"
-)
-
-mkdir -p "$DEST"
-status=0
-for entry in "${FILES[@]}"; do
-  read -r name size sha <<<"$entry"
-  f="$DEST/$name"
-  have=0
-  if [[ -f "$f" ]] && [[ "$(stat -c%s "$f")" == "$size" ]]; then
-    if sha256sum -c --quiet <(printf '%s  %s\n' "$sha" "$f"); then
-      have=1
-    fi
-  fi
-  if (( have )); then
-    echo "OK        $name"
-    continue
-  fi
-  if (( VERIFY_ONLY )); then
-    echo "MISSING   $name"
-    status=1
-    continue
-  fi
-  echo "FETCHING  $name"
-  tmp="$f.part"
-  curl -fsSL --fail-with-body -o "$tmp" "$BASE/$name"
-  mv "$tmp" "$f"
-  if [[ "$(stat -c%s "$f")" != "$size" ]]; then
-    echo "SIZE FAIL $name ($(stat -c%s "$f") != $size)"
-    status=1
-    continue
-  fi
-  if ! sha256sum -c --quiet <(printf '%s  %s\n' "$sha" "$f"); then
-    echo "SHA FAIL  $name"
-    status=1
-    continue
-  fi
-  echo "VERIFIED  $name"
-done
-if (( status == 0 )); then
-  echo "DOWNLOAD_DONE $DEST"
-else
-  echo "DOWNLOAD_FAILED $DEST" >&2
-fi
-exit "$status"

scripts/download-frank-zealot.sh

@@ -0,0 +1,90 @@
+#!/usr/bin/env bash
+# Download the frank-zealot payload for llama.cpp on the RTX 3090:
+# HauhauCS/Qwen3.5-9B-Uncensored-HauhauCS-Aggressive at **Q6_K** plus the
+# PUBLISHER's OWN vision projector (the BF16 mmproj — the model is natively
+# multimodal, so this file is the endpoint's eyes). Public repo — no auth
+# header, and never a token on the command line (it is world-readable in
+# /proc/<pid>/cmdline).
+#
+# Fresh downloads, no resume (`curl -C -` once produced a 213 MB oversized
+# file on a 31 GiB payload); -f/--fail-with-body so an HTTP error is not a
+# success, then byte count and sha256. The Hub exposes no LFS oid for this
+# repo (Xet storage), so the sha256 values below were computed locally after
+# the first verified fetch — byte counts match the Hub's declared sizes.
+# A sha of "-" means "first fetch: size-verified, sha printed for pinning".
+# Idempotent: complete files are skipped.
+#
+# 2026-10-07 (Frank): the payload moved to Qwen3.5-9B-Uncensored Q6_K at
+# 2 x 200,704 (qwen35 hybrid: 32 layers, 8 full-attention + 24 Gated
+# DeltaNet, no MTP tensors in this file). Rollback payloads stay on disk:
+# /home/dank/models/Gemma4-26B-A4B/ (Q4_K_M, the 2026-10-07 era being
+# replaced), Swift15-UncIQ3XXS/, MiMo-Q6K/, MiMo-Q5KM/, Ornith-Q8/.
+#
+# Usage:
+#   scripts/download-frank-zealot.sh [DEST_DIR] [--verify-only]
+set -euo pipefail
+
+DEST=""
+VERIFY_ONLY=0
+for arg in "$@"; do
+    case "$arg" in
+        --verify-only) VERIFY_ONLY=1 ;;
+        *) DEST="$arg" ;;
+    esac
+done
+DEST="${DEST:-/home/dank/models/Qwen35-9B-HauhauCS-Q6K}"
+
+# repo | hub-name | dest-name | bytes | sha256 (computed locally; Xet repo)
+FILES=(
+  "HauhauCS/Qwen3.5-9B-Uncensored-HauhauCS-Aggressive|Qwen3.5-9B-Uncensored-HauhauCS-Aggressive-Q6_K.gguf|Qwen3.5-9B-Uncensored-HauhauCS-Aggressive-Q6_K.gguf|7359259008|c0ba7beb68fd3fe47891bd549486d38dcf62d00817296ea314ad37017f5a4986"
+  "HauhauCS/Qwen3.5-9B-Uncensored-HauhauCS-Aggressive|mmproj-Qwen3.5-9B-Uncensored-HauhauCS-Aggressive-BF16.gguf|mmproj-Qwen3.5-9B-Uncensored-HauhauCS-Aggressive-BF16.gguf|921704448|05f662501f8bd45607b079723a3e238a4e888fd085a10a53f4057a0e250f6934"
+)
+
+status=0
+for entry in "${FILES[@]}"; do
+  IFS='|' read -r repo hubname destname size sha <<<"$entry"
+  url="https://huggingface.co/${repo}/resolve/main/${hubname}"
+  f="$DEST/$destname"
+  have=0
+  if [[ -f "$f" ]] && [[ "$(stat -c%s "$f")" == "$size" ]]; then
+    if [[ "$sha" == "-" ]]; then
+      have=1
+    elif sha256sum -c --quiet <(printf '%s  %s\n' "$sha" "$f"); then
+      have=1
+    fi
+  fi
+  if (( have )); then
+    echo "OK        $destname"
+    continue
+  fi
+  if (( VERIFY_ONLY )); then
+    echo "MISSING   $destname"
+    status=1
+    continue
+  fi
+  echo "FETCHING  $destname (from $repo)"
+  tmp="$f.part"
+  curl -fsSL --fail-with-body -o "$tmp" "$url"
+  mv "$tmp" "$f"
+  if [[ "$(stat -c%s "$f")" != "$size" ]]; then
+    echo "SIZE FAIL $destname ($(stat -c%s "$f") != $size)"
+    status=1
+    continue
+  fi
+  if [[ "$sha" == "-" ]]; then
+    echo "VERIFIED  $destname (size only) sha256=$(sha256sum "$f" | cut -d' ' -f1)"
+    continue
+  fi
+  if ! sha256sum -c --quiet <(printf '%s  %s\n' "$sha" "$f"); then
+    echo "SHA FAIL  $destname"
+    status=1
+    continue
+  fi
+  echo "VERIFIED  $destname"
+done
+if (( status == 0 )); then
+  echo "DOWNLOAD_DONE $DEST"
+else
+  echo "DOWNLOAD_FAILED $DEST" >&2
+fi
+exit "$status"

scripts/fleet-probes-swift15.sh

@@ -0,0 +1,56 @@
+#!/usr/bin/env bash
+# fleet-probes-swift15.sh — RUNS ON DANKSERVER. The cutover contract probes.
+set -uo pipefail
+B=http://localhost:7770/v1
+
+echo "== vision (solid red 512px, expect 'Red')"
+python3 - <<'PY'
+import base64, json, urllib.request, struct, zlib
+def png(color):
+    w = h = 512
+    raw = b"".join(b"\x00" + bytes(color) * w for _ in range(h))
+    def chunk(t, d):
+        c = t + d
+        return struct.pack(">I", len(d)) + c + struct.pack(">I", zlib.crc32(c))
+    return (b"\x89PNG\r\n\x1a\n"
+            + chunk(b"IHDR", struct.pack(">IIBBBBB", w, h, 8, 2, 0, 0, 0))
+            + chunk(b"IDAT", zlib.compress(raw)) + chunk(b"IEND", b""))
+b64 = base64.b64encode(png((255, 0, 0))).decode()
+body = json.dumps({"model": "frank-archon", "max_tokens": 256, "temperature": 0,
+    "messages": [{"role": "user", "content": [
+        {"type": "image_url", "image_url": {"url": "data:image/png;base64," + b64}},
+        {"type": "text", "text": "What color is this image? Answer with one word."}]}]}).encode()
+r = urllib.request.Request("http://localhost:7770/v1" + "/chat/completions",
+                           data=body, headers={"Content-Type": "application/json"})
+d = json.load(urllib.request.urlopen(r, timeout=300))
+m = d["choices"][0]["message"]
+ans = (m.get("content") or m.get("reasoning_content") or "")
+print("VISION ANSWER:", ans[:80].replace("\n", " "))
+PY
+
+echo "== tools (expect tool_calls)"
+curl -s -m 120 $B/chat/completions -H 'Content-Type: application/json' -d '{
+ "model":"frank-archon","temperature":0,"max_tokens":128,
+ "messages":[{"role":"user","content":"What is 23 times 47? Use the calculator tool."}],
+ "tools":[{"type":"function","function":{"name":"calculator","description":"evaluate arithmetic",
+ "parameters":{"type":"object","properties":{"expr":{"type":"string"}},"required":["expr"]}}}]}' \
+ | python3 -c 'import json,sys; d=json.load(sys.stdin); m=d["choices"][0]["message"]; print("TOOL_CALLS:", m.get("tool_calls"))'
+
+echo "== reasoning_effort fold (xhigh/medium/low/high all 200 on froggeric v22.5)"
+for lvl in xhigh medium low high; do
+  code=$(curl -s -o /dev/null -w "%{http_code}" -m 120 $B/chat/completions \
+    -H 'Content-Type: application/json' \
+    -d "{\"model\":\"frank-archon\",\"max_tokens\":8,\"reasoning_effort\":\"$lvl\",\"messages\":[{\"role\":\"user\",\"content\":\"hi\"}]}")
+  echo "  reasoning_effort=$lvl -> HTTP $code"
+done
+
+echo "== reasoning_content channel"
+curl -s -m 120 $B/chat/completions -H 'Content-Type: application/json' \
+ -d '{"model":"frank-archon","max_tokens":64,"messages":[{"role":"user","content":"Is 97 prime? Think briefly."}]}' \
+ | python3 -c 'import json,sys; m=json.load(sys.stdin)["choices"][0]["message"]; print("has reasoning_content:", bool(m.get("reasoning_content")), "| content:", (m.get("content") or "")[:60].replace(chr(10)," "))'
+
+echo "== response_format json_object"
+curl -s -m 120 $B/chat/completions -H 'Content-Type: application/json' \
+ -d '{"model":"frank-archon","max_tokens":64,"response_format":{"type":"json_object"},"messages":[{"role":"user","content":"Return JSON {\"ok\": true}"}]}' \
+ | python3 -c 'import json,sys; d=json.load(sys.stdin); print("JSON MODE:", (d["choices"][0]["message"].get("content") or "")[:60])'
+echo "PROBES_DONE"

scripts/frank-archon-expert-activity.py

@@ -1,5 +1,5 @@
 #!/usr/bin/env python3
-"""Measure per-block / per-expert expert-routing activity on live frank-primary.
+"""Measure per-block / per-expert expert-routing activity on live frank-archon.
 
 Method: AMD IBS op sampling (data addresses, `perf record -e ibs_op// --data`)
 on the llama-server process while concurrent generations of mixed content run.

scripts/frank-archon.env

@@ -0,0 +1,286 @@
+# frank-archon.env — radiance (StillDeadcode, Apache-2.0) serving
+# ukisai/Swift1.5-Qwen3.8-Flash-Next converted to GPTQ w4 (MODEL_FILE below,
+# built by scripts/convert-swift15-w4dn8.sh) on BOTH R9700s (TP=2),
+# dankserver :7770.
+#
+# SHAPE (2026-10-13): THREE decode slots x 200,000 tokens, fp8 (quantized) KV,
+# with the per-card budget spent on resident experts: 25,600 MiB of slab +
+# 5,120 MiB of pool = 30,720 MiB, inside the 30,969 MiB ceiling the engine's own
+# budget table allows (card 32,624 MiB, settle floor 209 MiB). The pool is sized
+# to the contract and nothing more (3 x 200,000 needs 5,063 MiB at fp8; 5,120
+# predicts 608,027 tokens, 1.3 % slack), because every MiB taken from the slab
+# is prefill and TTFT (2026-10-11 A/B: slab -14.8 % cost prefill -29 %, TTFT
+# +25 % at the full window) while KV beyond the contract buys nothing.
+# Consequence, deliberate: a FOURTH full-height conversation does not fit this
+# pair, and the engine refuses it — it never truncates. See the KV block for the
+# arithmetic and the measured dtype law. The fp8-native payload this file was
+# written for is the rollback target and keeps its own trio under the
+# fp8-native runbook.
+#
+# 2026-10-05 cutover from FreeToken (PR #587 ROCm, one card, experts in
+# pinned host RAM; git tag frank-archon-freetoken-pr587-20261005 is the
+# pre-cutover state — its unit/env/serve trio and Dockerfile are all in the
+# tag and rebuildable). Before that: tcclaviger vLLM fork (tag
+# frank-archon-vllm-shapeG-20261003).
+#
+# WHY RADIANCE: the engine is C++/HIP with libr4d kernels built for
+# gfx1201, drives `podman run` directly from the digest-pinned
+# stilldeadcode/radiance image (287 MiB; host needs only the amdgpu driver),
+# and its qwen4exp plugin reads the modelopt FP8 encoding NATIVELY
+# (`X.weight_scale_inv` is the scale plane — checkpoint.h). The PLE n-gram
+# table (51B params, 47.7 GiB) is served from pinned host RAM via io_uring
+# reads — Frank's call: "Native FP8. Experts from ram. Pin the PLE to ram."
+# The 4-bit-codebook publisher shape (qwen3.8-next-flash-fp8-iq4r-moe.rad,
+# --host-pool-mib 12288) remains the documented fallback if the native
+# container proves unbootable.
+#
+# PAYLOAD: /home/dank/models/rad/qwen4exp-fp8-native.rad — a rad-convert
+# NO-RECIPE pure copy of the official 131-shard checkpoint (every weight
+# keeps its block-FP8 encoding; ~161 GiB). The convert runs against a
+# staging dir whose config.json drops `quantization_config`: the descriptor
+# string is only the plugin SELECTION key (spec §2.4 — exact match, no
+# fallback), and no shipped plugin claims (qwen4exp, "fp8"); the shipped
+# qwen4exp plugin claims (qwen4exp, "") which is what recipe-built
+# containers carry. Per-weight encodings are data, not the descriptor —
+# removing the key changes nothing about what the weights hold. Built by
+# scripts/build-frank-archon-rad.sh (staging + convert + rad-info).
+#
+# SERVING FACTS (docs/GUIDE.md, docs/DOCKER.md, compose/flashnext.yaml):
+# - The HTTP listener binds AFTER the full load (main.cpp: engine.start()
+#   then engine.serve()) — during load the port refuses connections, so a
+#   bare curl /health gate is honest. /health == /ping: 200 JSON while
+#   serving, 503 only while stopping (core/server/admin.cpp:385).
+# - Reasoning: --reasoning-format defaults to auto, emitting thinking in
+#   `reasoning_content` (config.cpp). Tool calls: the qwen3.8 dialect, from
+#   the chat format. Both need no parser flags.
+# - Sampling: the OpenAI endpoint accepts temperature, top_p, top_k, min_p,
+#   typical_p, presence_penalty, frequency_penalty, repetition_penalty,
+#   repeat_last_n, chat_template_kwargs, reasoning_effort,
+#   enable_thinking, preserve_thinking (core/server/oai.cpp:194-205) —
+#   models.yml's extraBody set is fully inside it. Unknown params are
+#   refused (400), which is why nothing unverified rides the wire.
+# - MTP: the official checkpoint carries the mtp.* head (3,101 tensors,
+#   mtp_num_hidden_layers=1) and the plugin probes draft depth 3 — the
+#   publisher's throughput peak for this model. Stated explicitly with
+#   --num-speculative-tokens 3.
+# - The fused TP all-reduce is declared over max-num-seqs x
+#   (1 + --num-speculative-tokens) rows; 2 x 3 = 6 rows, under the 25-row
+#   exactness bound of the wht6 wire.
+# Engine pin: Codeberg tag v1.0.13 (commit 53282fa), Docker Hub tag 1.0.13,
+# index digest below. REJECTED UPGRADE: 1.2.0 (sha256:665775ed1d90de6dbb
+# 25558e07fc60d20328f1346f96f3c6e00845eb763f01fa, tag 1.2.0, commit
+# e95d397) was benched 2026-10-06 on this exact shape (fp8-native rad,
+# vram pair, spec 2, seqs 3, 43.6k greedy probe): decode 29.21 t/s and
+# draft acceptance 0.7123 vs the 1.0.13 control's 30.08 and 0.7549.
+# Acceptance on the greedy harness is deterministic (the control
+# reproduced the recorded 0.755 exactly), so the drop is a real numerics
+# change — the 1.2.0 MoE weight-rotation change (92b8aaf) is the named
+# suspect; decode loss tracks the acceptance ratio (0.943 vs 0.945).
+# The vram-pair translation itself is exact (1.2.0 boot ledger took
+# vram_weights 25.46 GiB / vram_kv 3.46 GiB per card byte-identical to
+# the 1.0.13 ledger at EVC 0.82). Re-test 1.2.0+ when the rotation change
+# is untangled; 1.2.0 also REMOVED --expert-vs-cache-ratio in favour of
+# the --vram-weights-mib / --vram-kv-mib pair (core/config.cpp) — this
+# file already uses the pair, which BOTH pins accept (rollback symmetry).
+FRANK_ARCHON_IMAGE=stilldeadcode/radiance@sha256:4c3f484564bb2872784e46b0a59cbd71becc9c1e746e301a3596ffae253c322e
+# The .rad container FILE (mounted under /models) and the state dir for the
+# prefix-cache disk tier (mounted rw at /data). The model dir holds ONLY
+# .rad files; the raw HF download and its staging dir live beside it and
+# are never mounted.
+FRANK_ARCHON_MODEL_DIR=/home/dank/models/rad
+FRANK_ARCHON_MODEL_FILE=qwen4exp-swift15-w4dn8-i8-hc8m.rad
+FRANK_ARCHON_STATE_DIR=/home/dank/radiance-state
+# The state dir's tune/ subdirectory holds rad-tune's kernel-selection
+# cache (the engine's selector reads $RADIANCE_HOME/tune/<machine>.tune
+# at boot; $RADIANCE_HOME defaults to /opt/radiance, in the image, so the
+# cache must ride a host mount — serve script mounts it, see the runbook's
+# "Tuning levers").
+# Container identity is the SERVICE name (Frank's call, 2026-10-05): one
+# name across systemctl and podman ps. The runtime changes; the name does
+# not. The legacy list retires every predecessor identity that could hold
+# the GPUs or the port.
+FRANK_ARCHON_CONTAINER=frank-archon
+FRANK_ARCHON_LEGACY_CONTAINERS="frank-archon-qwen frank-archon-r9v qwen-fp8 glm-probe"
+# Served model id — Protoss name (wire rename 2026-10-09). The container,
+# unit, scripts and this file keep the frank-archon name above; only the
+# alias on the wire moved. Radiance validates the requested model name, so
+# every client (harness, bench scripts, probes) MUST send this value.
+FRANK_ARCHON_SERVED_NAME=frank-archon
+FRANK_ARCHON_PORT=7770
+# Frank's chat-template call: froggeric's fixed Qwen3.8 template (the
+# repo's root chat_template.jinja, vendored here; the checkpoint's own
+# template is baked into the .rad by rad-convert and this overrides it).
+# Radiance derives the reasoning/tool-call reply format from it.
+FRANK_ARCHON_TEMPLATE=/home/dank/serverAppConfigs/scripts/qwen38-froggeric-v22.5.jinja
+
+# --- engine shape (the boot ledger arbitrates every number below) ---------
+# Tensor parallel: BOTH R9700s. The board swap (2026-09-20, ProArt B850
+# x8/x8 on root ports) made collectives legal on this host; radiance's TP
+# wire is libr4d's own, not RCCL.
+FRANK_ARCHON_TP=2
+# Lossy WHT 6-bit wire for large all-reduces (publisher's production choice:
+# +5.6-6.3% prefill, ~-1.3% 8-stream decode at TP2). min-kb stays the
+# engine default.
+FRANK_ARCHON_TP_WIRE=wht6
+# Decode slots: THREE, so the served window is a CAPACITY CONTRACT — three
+# concurrent conversations of --max-model-len fit the KV pool (see the KV
+# block below). The "seqs 2 cannot boot" law is NOT radiance's: it was the
+# tcclaviger vLLM fork's torch.compile shape specialization on
+# query_start_loc (ConstraintViolationError, measured 2026-10-02, retired
+# with that runtime). Radiance booted seqs 2 at the fp8-native first boot,
+# and the 2026-10-06 decode sweep measured seqs 2 and 3 statistically tied
+# (30.9-33.1 t/s, inside the +-3% noise floor) — slot count buys concurrency,
+# not speed, so a slot costs KV, never decode.
+# Cost of each extra slot: 110 MiB of per-slot recurrent state inside the KV
+# pool, and the fused TP all-reduce is declared over seqs x (1 + spec) rows —
+# 3 x 3 = 9 here, under the 25-row bound at which the wht6 wire stays EXACT
+# (single-sequence decode and any step of <= 25 rows is bit-exact; only busier
+# steps are lossy).
+# The pool is sized to this contract and nothing more (see the KV block):
+# 3 x 200,000 at fp8 = 5,063 MiB, pool 5,120, and the freed 1,792 MiB went into
+# the resident expert slab. The trade is explicit and it is Frank's call:
+# a FOURTH full-height conversation no longer fits (5,120 MiB of pool backs
+# ~608k tokens; 4 x 200,000 needs 6,601), so a fourth 200k request is refused
+# as too large to fit — it is NOT squeezed, paged, or truncated. Third-party
+# traffic that wants four full-height sessions is a --vram-kv-mib change, not
+# a code change.
+FRANK_ARCHON_MAX_SEQS=3
+# Served window. Native is 262,144; 200,000 is the publisher's production
+# value (compose) and what models.yml's contextWindow must quote — a longer
+# prompt is refused by the engine, never truncated. The engine treats
+# `kv group tokens >= max-model-len` as a HARD limit ("ONE request longer
+# than N tokens is accepted by the API and then refused as too large to ever
+# fit — this is a hard limit, not a backing ratio"), so the pool is sized
+# for seqs x maxlen, not for one sequence.
+FRANK_ARCHON_MAX_MODEL_LEN=200000
+FRANK_ARCHON_PLACEMENT=expert_tiered
+# Pinned host pool for the expert rows that do not fit VRAM. vram_weights and
+# this pool serve the per-rank resident set TOGETHER: at the fp8-KV pair
+# (26071/3543) the ledger showed the VRAM slab filled to 259 KiB of slack,
+# i.e. the pair was exactly sized. Cutting vram-weights by 3.8 GiB to pay for
+# the bf16 KV pool SPILLS ~3.8 GiB/rank here, so the pool moves with it —
+# under-sizing it is a boot failure (36864 refused the boot in the fp8 era).
+# The boot ledger's coverage line remains the referee, not this arithmetic.
+FRANK_ARCHON_HOST_POOL_MIB=44928
+# VRAM left unclaimed per card (publisher default 96 MiB).
+FRANK_ARCHON_GPU_HEADROOM_MIB=96
+# VRAM split of claimed memory per card, MiB (0 = derive from the card).
+# THE CEILING, read off this engine's own VRAM-budget table (boot 2026-10-13,
+# pair 24000/5120): card 32,624 MiB; budgets claimed 29,120; `3.42 GiB is
+# neither budgeted nor accounted — the driver's context, the activation arena
+# and --gpu-headroom-mib come out of it; anything past those is throughput on
+# the floor`; and `card 0 settled at 2.01 GiB free against 209.19 MiB (the
+# 96.00 MiB --gpu-headroom-mib and 113.19 MiB kept for the static region)`.
+# So the reserve above the ENGINE's floor is 2,058 - 209 = 1,849 MiB and the
+# ceiling is 29,120 + 1,849 = 30,969 MiB. The 2026-10-11 bound of 29,120
+# ("31,856 - 1,710 outside both budgets - keep 1 GiB free") was MY reserve, not
+# the engine's; the pair below spends the difference and lands 458 MiB above
+# the engine's floor. `weights + kv <= 30,969` is the gate.
+# THE PRICE, and it is paid twice: on this engine idle KV VRAM is ALSO the
+# expert cache's spillover (`mover: 2275 slots can be lent out of the KV
+# cache (2.69 GiB)`, `arena: lends 740 MiB while steps are <= 256 tokens`),
+# so a bigger KV pool steals weight residency from the slab AND from the
+# lendable cache. Priors on this card/model: stealing 2.14 GiB of weights for
+# a bigger pool (MAX_MODEL_LEN 262144) cost 2.5% decode; the EVC ladder's
+# other direction (0.82 -> 0.84, +2.5 GiB weights) cost 8.9%. The 2026-10-11
+# exact-KV A/B measured the slab's own price (22208 vs the fp8-era 26071):
+# prefill -29 %, TTFT at the full window +25 %, decode inside the noise band on
+# 2 of 3 passes, draft acceptance UP 0.661 -> 0.740.
+# 2026-10-13 (late): THREE slots, so the pool is cut to the contract (5,120)
+# and every spare MiB goes to the slab: 22208 -> 24000 (the third slot's
+# surplus KV), then 24000 -> 25600 (the card's settling slack). The direction
+# the A/B data points: prefill is slab-limited, KV beyond the contract is not.
+# The margin is thin by design (608,027 predicted tokens against the 600,000
+# contract), so the boot ledger's `backs N sequences all at 200000 tokens at
+# once` line is the referee for THIS pair and the concurrent probe is its
+# regression test.
+# VERDICT on the 25,600 arm (measured 2026-10-13, scripts/probe-frank-archon-kv.py):
+# the threshold claim is FALSIFIED — the slab is a SLOPE at this end. A-cold
+# 43.5k single-stream: 22,208 -> 3,397, 24,000 -> 3,290, 25,600 -> 3,584 t/s;
+# the 3-way 197k arm's aggregate prefill 3,051 -> 3,589 t/s (wall
+# 193.7 -> 164.5 s). So +1,600 MiB of slab = +8.9 % single-stream and
+# +17.6 % concurrent, both outside the +-3 % noise floor. The 22,208/24,000
+# pair landed inside noise of EACH OTHER, which is what made it read as a
+# plateau; two points are not a curve.
+# The cliff that remains is between 25,600 (3,584) and 26,071 (4,379, the
+# 2026-10-11 fp8 control at seqs 3 / pool 3,543) — +22 % for +471 MiB. At THREE
+# slots that is only reachable by breaking the ceiling (26,112 + 5,120 = 31,232
+# vs 30,969, ~214 MiB above the engine's floor); at TWO slots it is free:
+# pool 3,072 + slab 27,897 = exactly the ceiling, slab above the cliff.
+FRANK_ARCHON_VRAM_WEIGHTS_MIB=25600
+FRANK_ARCHON_VRAM_KV_MIB=5120
+# KV cache QUANTIZED (fp8). This engine's flag takes ONLY bf16|fp8 — there is
+# ONE kv_dtype for the whole cache, so "exact K, quantized V" (llama.cpp's
+# --cache-type-k/--cache-type-v pair, which is what frank-zealot runs) is
+# UNSERVABLE here: the rung below bf16 is fp8 on both halves.
+# Measured per-rank cost, read out of the boot ledger's group table (fp8 boot
+# 2026-10-08, bf16 boot 2026-10-11):
+#   kv_attn     13 layers, 4-token blocks, page 26.00 KiB (fp8) -> 52.00 KiB
+#   kv_qsa_bkey 13 layers, 4-token blocks, page  3.25 KiB at BOTH dtypes —
+#               the QSA block key is an index, not attention state, and does
+#               NOT follow --kv-cache-dtype
+#   => 7.3125 KiB/token fp8, 13.8125 KiB/token bf16: bf16 costs 1.89x fp8,
+#               not 2x, precisely because the bkey plane is dtype-fixed.
+# The dtype-INDEPENDENT terms also live in the pool: kv_gdn_state 54 MiB x 2
+# copies per sequence (+ conv/tail/ple ~= 110 MiB a sequence) and the prefix
+# checkpoint region 8 x 55.99 = 448 MiB. So:
+#   pool_mib >= tokens x 7.3125 KiB + 110 x seqs + 448
+#   3 x 200,000 at fp8 needs 4,285 + 330 + 448 = 5,063 MiB; the pool is 5,120,
+#   and it predicts (5120 - 330 - 448) x 1024 / 7.3125 = 608,027 tokens: the
+#   three-slot contract with 1.3 % slack, every MiB above 5,063 having been
+#   handed to the expert slab instead. The ledger line is the referee ("backs N
+#   sequences all at 200000 tokens at once") — a pair this tight is read off the
+#   boot, never assumed.
+#   At bf16 the same three slots cost 8,093 + 778 = 8,871 MiB, which would cut
+#   the slab to 20,249 MiB (-9 %); at FOUR slots bf16 costs 10,791 + 888 =
+#   11,679 MiB and the slab falls to 17,441 (-33 %). fp8 keeps 22,208 at both
+#   slot counts. The 2026-10-11 bf16 shape (6,912 / seqs 2) backed 462,752
+#   tokens = 2 x 200,000; the historical fp8 pool of 3,543 gave 386,904 (1.93
+#   sessions), and the four-slot fp8 boot of 2026-10-13 19:21 backed 843,276.
+# Secondary saving: the prefix-cache entry shrinks with the attention plane
+# (one entry 110.50 KiB at bf16 -> 58.50 KiB at fp8, measured on the two boot
+# ledgers' `kv tier transfer` lines), so the host tier below parks twice as
+# many conversations as it did at bf16 — no re-size needed to park three slots.
+FRANK_ARCHON_KV_DTYPE=fp8
+# Spec decode: the checkpoint's own MTP head at the publisher's depth-3
+# operating point (probe() returns 3 when mtp_num_hidden_layers > 0; the
+# flag states it so the ledger records the intent).
+FRANK_ARCHON_SPEC_TOKENS=2
+FRANK_ARCHON_MAX_BATCHED_TOKENS=2048
+# Prefix cache tiers (publisher pattern). The host tier is sized in ENTRIES,
+# and one entry tracks the cache dtype (58.50 KiB at fp8, 117 KiB at bf16, per
+# the ledger's `kv tier transfer` line): at fp8, 8192 MiB parks ~5.8 sessions
+# of 200k (at bf16 the same tier parked ~2.9), so four live slots plus a full
+# parked set fits with the tier as it stands — at RAM the host has (104 GiB
+# available with the service loaded).
+FRANK_ARCHON_PREFIX_HOST_MIB=8192
+FRANK_ARCHON_PREFIX_DISK_MIB=65536
+# Frank's pin law: the PLE n-gram table (47.7 GiB) serves from pinned host
+# RAM the cards read. `ram` REFUSES the start if the memlock limit is too
+# small — the unit's LimitMEMLOCK=infinity is the other half of this law.
+FRANK_ARCHON_NGRAM_PLACEMENT=ram
+# TTM preflight: the pinned ledger (2 x 44 GiB pools + 47.7 GiB PLE + 8 GiB
+# prefix host = ~147 GiB) rides TTM's shared pages, capped by ttm's
+# pages_limit (the current kernel exposes NO pages_max; the cap function
+# takes the min over the knobs that exist). Below the plan the load dies
+# mid-pin with an allocator error instead of this named refusal.
+# THE CAP IS A RUNTIME KNOB — the kernel default is half of RAM, so every
+# raise dies with a reboot. Measured the hard way: the 2026-10-05 manual raise
+# to 52,428,800 pages (200 GiB) was gone after the 2026-10-12 23:17 POWER
+# FAILURE, the cap fell back to 125,988 MiB, and the preflight refused the
+# start 6,919 times in ~20 h while Restart=always re-ran it. The gate in
+# scripts/ttm-preflight.sh now RAISES the knob itself before refusing (the
+# root unit is privileged; the knob is a 0644 root module parameter), so the
+# recovery is a boot, not a visit to the machine.
+FRANK_ARCHON_TTM_MIN_MIB=150000
+FRANK_ARCHON_TTM_TARGET_MIB=204800
+# Escape hatch for boot-ladder experiments. Unset -> no extra argv. Keep
+# multi-flag values as one string; the serve script expands it unquoted on
+# purpose.
+FRANK_ARCHON_EXTRA_ARGS=
+# The .rad's minimum size in MiB (deployer gate; a truncated convert is a
+# guaranteed long-timeout boot instead of a fast failure). The converted
+# container measured 177,109 MiB (1,857,127,997,440 B = 173.0 GiB; the
+# plan-only estimate 172.76 GiB covers the data planes but not the metadata
+# tail) - floor sits just under the payload.
+FRANK_ARCHON_RAD_MIN_MIB=110000

scripts/frank-archon.service

@@ -0,0 +1,71 @@
+# frank-archon.service — radiance (StillDeadcode, Apache-2.0) endpoint
+# (OFFICIAL Qwen/Qwen3.8-Flash-Next-FP8 at NATIVE block-FP8 precision, the
+# rad-convert container qwen4exp-fp8-native.rad) on BOTH R9700s (TP=2,
+# wht6 wire), dankserver :7770. 2026-10-05 cutover from FreeToken (git tag
+# frank-archon-freetoken-pr587-20261005 is the pre-cutover state; the
+# retired unit/env/serve trio and Dockerfile are in that tag).
+#
+# Same port, same served alias, same container identity as the unit name;
+# the harness models.yml id is unchanged. The serve script drives
+# `podman run` directly: the digest-pinned stilldeadcode/radiance image
+# (287 MiB, kernels prebuilt for gfx1201) has the engine as its
+# entrypoint. The image lives in dank's ROOTLESS podman storage.
+# WHY A ROOT UNIT (not a rootless quadlet): radiance pins ~132 GiB of HOST
+# RAM (2 x 40 GiB expert pools + the 47.7 GiB PLE ngram table + the prefix
+# host tier). Pinned pages are charged against RLIMIT_MEMLOCK; dank's login
+# session on this host carries 8 MiB and a user quadlet is capped by the
+# user manager's own hard limit — raising that means restarting
+# user@1000.service and bouncing every user container on the host. A root
+# unit grants LimitMEMLOCK=infinity to the dank process via PID1; the
+# engine still runs out of dank's rootless podman storage.
+[Unit]
+Description=frank-archon — radiance Qwen3.8-Flash-Next-FP8 (native) on 2x R9700 TP=2
+After=network-online.target
+Wants=network-online.target
+# Never let the start-rate limiter give up after a crash loop (a failed LLM
+# endpoint that systemd refuses to retry is worse than a retrying one).
+StartLimitIntervalSec=0
+
+[Service]
+User=dank
+Group=dank
+# The engine pins ~132 GiB of host RAM (expert pools + PLE table); an
+# RLIMIT_MEMLOCK smaller than the pinned set fails the load mid-start.
+# PID1 grants infinity here — parity with the fleet's other LLM units.
+LimitMEMLOCK=infinity
+Environment="FRANK_ARCHON_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-archon.env"
+ExecStart=/home/dank/serverAppConfigs/scripts/serve-frank-archon.sh
+# The `+` prefix runs this as root even though the service is User=dank — the
+# ttm pages cap is a root-owned knob and the pinned-RAM ledger (~147 GiB) is
+# unusable below it. After a reboot the knob is back at its default (half of
+# RAM), so the raise must be part of the start, not a note in a runbook: the
+# 2026-10-12 power failure reset it and the endpoint refused to boot 6,919
+# times. The serve script re-verifies the cap after this hook.
+ExecStartPre=+/home/dank/serverAppConfigs/scripts/ttm-preflight.sh --raise
+# systemd stop: wait alone cannot stop the container child; stop it
+# explicitly. No graceful drain contract is claimed (the OpenAI front end
+# holds no queue to drain — in-flight decodes are lost, which a stop
+# during a bench window accepts; radiance takes SIGTERM on the engine
+# process and podman reaps the container).
+ExecStop=/usr/bin/podman stop -t 120 frank-archon
+# Boot cost: .rad load (weights + PLE upload) + expert host-pool pin. The
+# publisher's compose healthcheck allows a 15-minute start_period; the
+# vLLM-era budget (1800 s) carried forward.
+# Restart=always, NOT on-failure (the 2026-10-01 vLLM lesson carries over:
+# a clean API-server exit after a worker fault reads as success to
+# systemd). `always` restarts on any container death; an explicit
+# `systemctl stop` still wins, so bench windows and deploys are unaffected.
+Restart=always
+RestartSec=10
+# ExecStop allows the engine 120 s to drain (`podman stop -t 120`); without
+# an explicit TimeoutStopSec systemd's 90 s default cuts the stop short,
+# kills it, and records 'Failed with result timeout' (measured 2026-10-01
+# 13:27:17). Must exceed the podman grace with margin.
+TimeoutStopSec=180
+# The engine pins tens of GiB of host RAM (expert rows + PLE table); it is
+# the last process on this host that should be chosen by the kernel OOM
+# killer.
+OOMScoreAdjust=-500
+
+[Install]
+WantedBy=multi-user.target

scripts/frank-dragoon.env

@@ -0,0 +1,158 @@
+# frank-dragoon.env — tunables for the frank-dragoon endpoint on Dankclaw's
+# Strix Halo iGPU (gfx1151), host port 7770.
+#
+# RUNTIME (2026-10-06, Frank): halogen-flash-server 0.16.2 — the
+# closed-source C++/HIP engine (image ghcr.io/peonist-ai/halogen-flash-server,
+# digest-pinned below) serving the Quat3rnion ABLITERATED Swift1.5 finetune
+# of peonist's Qwen3.8-Flash-Next v2 checkpoint, as a podman container under
+# a root unit, driven by scripts/serve-frank-dragoon.sh. This CUTS OVER the
+# 2026-10-05 halogen 27B-dense shape (censored base, DFlash2, 31.7 t/s):
+# rollback = revert the swap commit's trio; the 27B payload stays on disk at
+# /home/dank/models/halogen-qwen3.8-27b/.
+#
+# WHY THE RUNTIME MOVED WITH THE MODEL: the payload is .hgn — per its own
+# card it "will not load in transformers, vLLM, or llama.cpp" — and the v2
+# .hgn loads ONLY in the flash-server line (the old halogen engine is for
+# the 27B p1w4d file; the v2 quickstart pins flash-server). What the move
+# buys (card + live probe evidence): MTP spec decode (53-57 t/s greedy,
+# 3-10x serial), ~1,640 t/s prefill at 34k, ~72% fewer thinking tokens than
+# the censored 27B (905 mean), the ABLITERATED base (refusals should NOT
+# return), IMAGE INPUT (the v2 vision tower loads beside the checkpoint —
+# red-PNG probe verified on the card; the 27B engine ignored its encoder),
+# tool calls verified, and the native 262,144 context.
+#
+# SHAPE — the knobs that are NOT free, with the arithmetic:
+#   HALOGEN_CTX=262144 is the PER-SLOT window and the per-conversation hard
+#   ceiling — a prompt over it is a 400 naming the limit, never a silent
+#   truncation. RAISED from 200192 on 2026-10-07: the harness clamps
+#   max_tokens to contextWindow − est − 4096, its chars/4 est UNDER-counts
+#   the rendered prompt by ~3 % on code/agent traffic, and compaction only
+#   fires at 85 % — so with window == engine ceiling, every request over
+#   ~146k est (65-85 % of the window) was a guaranteed 400. Measured
+#   2026-10-07: est 152,938, server 157,388, request 43,158 vs room 42,804
+#   — over by 354, margin 4,096 < the 4,450 under-count.
+#   Harness contract (models.yml): contextWindow 217088, maxTokens 45056.
+#   Compaction fires at 85 % = 184,524 est ≈ 190k measured (Frank's 180k
+#   target). Worst-case request: prompt + budget <= 217088 − 4096 + 3 %
+#   est-error ≈ 219k <= 262144 — the 45k gap between harness window and
+#   engine ceiling absorbs the estimate error with ~7x margin (robust to a
+#   10 % under-count). Compaction rides on frank-zealot: input ≈
+#   threshold − keepRecent(20k) ≈ 170k measured, inside its 200,704 slot.
+#   HALOGEN_KV_POOL_POSITIONS=524288 = KV_SLOTS(2) x CTX — the explicit
+#   form of the engine's default, so the seam test can pin the product.
+#   KV costs ~28 KiB/position (FLAGS.md) => 524,288 x 28 KiB = 14.0 GiB.
+#   HALOGEN_KV_SLOTS=2 restores the w4b-era shape on this box: the MTP
+#   drafter is NOT slot-locked on this engine (batching and speculation
+#   coexist — DFlash-era slots>1 law does NOT carry over; the card's own
+#   quickstart ships 2 slots WITH the head), so the second slot is
+#   concurrent capacity, not a speculation tax.
+#   Memory ledger against the box's 121.2 GiB unified (the n-gram table is
+#   mmap'd page cache beside the checkpoint, not a pinned charge — the
+#   card's own quickstart arithmetic does not bill it):
+#     weights ~62 GiB resident + KV 14.0 + arena (HALOGEN_MAX_TOK=8192 =>
+#     ~8 GiB per FLAGS.md arena formula 3.8+8.4*(MT/16384)) + vision ~2
+#     = ~86 GiB engine-side; HALOGEN_HOST_RESERVE_GIB=20 keeps the host
+#     honest; baseline co-tenancy (frank-zealot, ComfyUI, Caddy/observ)
+#     ~10-15. ~15 GiB margin. The boot ledger is the referee — read it
+#     after deploy and re-size if the engine prints a clamp.
+#   HALOGEN_SPEC_ADAPT=0 is MANDATORY (card): the default adaptive policy
+#   turns the MTP head off for whole requests after low acceptance and
+#   HALVES decode as a result. Frank accepted the head always-on trade
+#   (temp 1.0 traffic costs acceptance; the card still ships the recipe).
+#
+# CLIENT CONTRACT deltas vs the 27B shape (harness side lives in
+# ~/.omp/agent/models.yml):
+#   * SERVER-SIDE SAMPLER EXISTS NOW: HALOGEN_TEMPERATURE/TOP_P/TOP_K set
+#     the card's thinking recipe (1.0 / 0.95 / 20) as engine defaults, so
+#     an absent temperature is no longer greedy. models.yml extraBody
+#     carries the same values — consistent, not load-bearing.
+#   * HALOGEN_MAX_TOK=8192 is only the DEFAULT for requests that omit
+#     max_tokens; the harness sends at most its maxTokens 45056. Requests
+#     over HALOGEN_MAX_TOKENS_CAP (65536) are a 400 naming the cap. Cap and
+#     queue timeout are COUPLED (FLAGS.md table): 65536 at ~10 t/s serial
+#     worst case needs > 6550 s; 7200 honors it. Do not move one alone.
+#   * max_tokens INCLUDES thinking; a reasoning reply over a small budget
+#     returns empty content with finish_reason "length".
+#   * Prompt cache is ON by default (PROMPT_CACHE=2): a follow-up turn at
+#     100k context re-prefills ~2 s instead of ~88 s cold. No pin needed —
+#     unlike the 27B engine, auto-sizing fits this box's ledger.
+#   * Thinking lands in reasoning_content (same as the 27B engine); the
+#     v2 chat template rejects reasoning_effort outside xhigh|medium|low,
+#     so the models.yml fold (high->xhigh) still applies.
+#   * Vision: OpenAI image_url content parts only (the fleet's standard
+#     contract). >=256 px probe images or the model answers "video".
+#   * response_format json_object/json_schema unsupported in this line
+#     (no constrained decoding) — unchanged from the 27B engine.
+#   * The engine's token protocol has no auth and binds loopback INSIDE
+#     the container; only the frontend port (8731) is published. Same as
+#     before. Kernel needs CONFIG_HSA_AMD_SVM (CachyOS ships it) and
+#     amdgpu.noretry=0 (check at deploy).
+
+# Image: digest-pinned (fetch law: tag pulls silently re-point; the digest
+# is what was qualified). 0.16.2 = the version the model card names as its
+# quickstart pin; RepoDigest captured at pull on 2026-10-06.
+FRANK_DRAGOON_IMAGE=ghcr.io/peonist-ai/halogen-flash-server@sha256:0c61bf84ac22308a53f5d1ca6b86806702d7039e5ebc51cae4c66621b92fe04a
+# Container identity: kept from the 27B era (unit ExecStop names it).
+FRANK_DRAGOON_CONTAINER=frank-dragoon-halogen
+# Old quadlet-era container identity; the serve script clears stale names.
+FRANK_DRAGOON_LEGACY_CONTAINERS=frank-dragoon
+# host:container — the frontend listens on 8731 inside (HALOGEN_API_PORT
+# default); the engine port (8730) is never published.
+FRANK_DRAGOON_PUBLISH=7770:8731
+
+FRANK_DRAGOON_MODEL_DIR=/home/dank/models/halogen-flashnext-v2
+# The checkpoint: Quat3rnion/halogen-swift1.5-qwen3.8-flash-next-v2-abliterated
+# qwen38-flash-next-v2-swift15-abliterated.hgn — compacted r2 of the card's
+# append-only original (byte-identical live tensors, padding dropped:
+# 66,687,678,464 B vs 89,775,868,032 B). LFS sha256 verified at fetch.
+FRANK_DRAGOON_CHECKPOINT=qwen38-flash-next-v2-swift15-abliterated.hgn
+FRANK_DRAGOON_CHECKPOINT_BYTES=66687678464
+FRANK_DRAGOON_CHECKPOINT_SHA256=9c880b8ba48deabfa06172eff1e7572e4fe465e09e97faec6e50c3f6fdcac037
+# The n-gram lookup table: REQUIRED (the engine reads it beside the
+# checkpoint; the card's quickstart names it explicitly). From
+# peonist-ai/halogen-qwen3.8-flash-next @ 5cc17cea.
+FRANK_DRAGOON_NGRAM_TABLE=qwen38-flash-next-ngram.hgn
+FRANK_DRAGOON_NGRAM_BYTES=51200246144
+FRANK_DRAGOON_NGRAM_SHA256=3450acada94e19aabad88bd49b45eb70304820949c2240fc178067b20ae5dffe
+# The vision tower: OPTIONAL on the engine, ENABLED here (image input).
+# From peonist-ai/halogen-qwen3.8-flash-next @ e053f488.
+FRANK_DRAGOON_VISION_TOWER=qwen38-flash-next-vision.hgn
+FRANK_DRAGOON_VISION_BYTES=897916416
+FRANK_DRAGOON_VISION_SHA256=d62e0ae553fe88afd3833733d4a4c669f34d20fd8dfce4b9610525bed2134b10
+# The tokenizer is a FLAT DIRECTORY, $FRANK_DRAGOON_MODEL_DIR/tokenizer,
+# mounted whole at /tokenizer. The two repos ship the same one; fetched
+# fresh from peonist @ e053f488 (tokenizer.json is LFS, byte-identical to
+# the 27B-era copy; the rest are plain git blobs — size-checked only). The
+# serve gate and the deployer refuse a missing file or ANY symlink: an HF
+# cache snapshot symlinks each file into blobs/, and those links dangle
+# inside the container mount.
+FRANK_DRAGOON_TOKENIZER_FILES="tokenizer.json chat_template.jinja tokenizer_config.json merges.txt vocab.json generation_config.json"
+
+# --- engine flags (docs/FLAGS.md of the flash-server repo; anything unset
+# stays at the image default, which is what was qualified) ------------------
+# Served model id — Protoss name (wire rename 2026-10-09); the service, unit,
+# scripts and this file keep the frank-dragoon name. OpenWebUI api_configs
+# model_ids for the :7770 backend MUST name this value.
+HALOGEN_MODEL_ID=frank-dragoon
+HALOGEN_CTX=262144
+HALOGEN_KV_POOL_POSITIONS=524288
+HALOGEN_KV_SLOTS=2
+HALOGEN_HOST_RESERVE_GIB=20
+# Spec decode: MTP head is INSIDE the checkpoint (do NOT set HALOGEN_MTP_HEAD);
+# depth 2 is the documented "best all-round" default. HALOGEN_DRAFTER /
+# HALOGEN_DFLASH_* from the 27B engine DO NOT EXIST here.
+HALOGEN_SPEC_ADAPT=0
+# Coupled pair (FLAGS.md table): the cap bounds how long ONE request holds
+# the GPU, the timeout bounds how long the NEXT client waits. Do not move
+# one alone (see the client-contract note above).
+HALOGEN_MAX_TOK=8192
+HALOGEN_MAX_TOKENS_CAP=65536
+HALOGEN_QUEUE_TIMEOUT=7200
+# Server-side sampler = the card's thinking recipe (the engine now HAS one;
+# requests may still override per-call). Matches models.yml extraBody.
+HALOGEN_TEMPERATURE=1.0
+HALOGEN_TOP_P=0.95
+HALOGEN_TOP_K=20
+# Card's belt-and-braces: the engine pins weights by default
+# (HALOGEN_FLASH_PIN_TRUNK=1; only the retired w4b build honored 0).
+HALOGEN_WEIGHTS_LOCK=1

scripts/frank-dragoon.service

@@ -1,5 +1,5 @@
 [Unit]
-Description=halogen container (peonist-ai/halogen-qwen3.8-27b, DFlash2 spec decode, 1 slot x 200700, text-only), root systemd unit (dankclaw, frank-large, Strix Halo iGPU)
+Description=halogen-flash-server container (Quat3rnion abliterated Swift1.5 of Qwen3.8-Flash-Next v2, MTP spec decode, 2 slots x 200192, vision ON), root systemd unit (dankclaw, frank-dragoon, Strix Halo iGPU)
 After=network-online.target
 Wants=network-online.target
 
@@ -11,19 +11,19 @@ Group=dank
 # RLIMIT smaller than the pinned set cannot fail the load. Parity with the
 # other LLM units on this fleet.
 LimitMEMLOCK=infinity
-Environment="FRANK_LARGE_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-large.env"
-ExecStart=/home/dank/serverAppConfigs/scripts/serve-frank-large.sh
+Environment="FRANK_DRAGOON_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-dragoon.env"
+ExecStart=/home/dank/serverAppConfigs/scripts/serve-frank-dragoon.sh
 # systemd stop alone cannot stop the container child; stop it explicitly
-# (frank-primary pattern). The engine drains on SIGTERM.
-ExecStop=/usr/bin/podman stop -t 60 frank-large-halogen
+# (frank-archon pattern). The engine drains on SIGTERM.
+ExecStop=/usr/bin/podman stop -t 60 frank-dragoon-halogen
 TimeoutStartSec=1200
 TimeoutStopSec=120
 # always, not on-failure: an engine that exits 0 after an internal fault
 # would otherwise leave the endpoint down until someone notices.
 Restart=always
 RestartSec=10
-# The engine mmaps 33.4 GiB of weights and keeps a multi-GiB working set
-# on a box that also hosts frank-small, ComfyUI and the Caddy/observability
+# The engine pins ~62 GiB of v2 weights and keeps a multi-GiB working set
+# on a box that also hosts frank-zealot, ComfyUI and the Caddy/observability
 # stack; make it a late OOM candidate, not the first.
 OOMScoreAdjust=-500
 

scripts/frank-large.env

@@ -1,113 +0,0 @@
-# frank-large.env — tunables for the frank-large endpoint on Dankclaw's
-# Strix Halo iGPU (gfx1151), host port 7770.
-#
-# RUNTIME (2026-10-05, Frank): halogen — the closed-source C++/HIP engine
-# (github.com/peonist-ai/halogen-server, image ghcr.io/peonist-ai/halogen,
-# digest-pinned below) serving peonist-ai/halogen-qwen3.8-27b, a ~6.32 bpw
-# NVFP4-derivative quant of the BASE Qwen/Qwen3.8-27B (35,865,565,184 B,
-# 1352 tensors), as a podman container under a root unit, driven by
-# scripts/serve-frank-large.sh. This CUTS OVER the
-# 2026-10-02..10-03 ROCmFPX llama.cpp shape (uncensored
-# Q6_0_ROCMFPX_AGENT + MTP, 27.6-28.1 t/s): rollback = revert the swap
-# commit's trio; the ROCmFPX payload, draft head and build all stay on
-# disk at /home/dank/models/kingjones-Qwen3.8-27B-Uncensored-ROCmFP4-STRIX-MTP/.
-#
-# WHY THE RUNTIME MOVED WITH THE MODEL: the payload is .hgn — per its own
-# card it "will not load in transformers, vLLM, or llama.cpp". Accepted
-# consequences (Frank, 2026-10-05): TEXT-ONLY (halogen ignores the model's
-# vision encoder; the fleet's vision path is frank-small) and the CENSORED
-# base (this is a finetune of Qwen/Qwen3.8-27B, not the abliterated file —
-# refusals may return). What it buys: vendor-measured decode DFlash2 31.7
-# t/s mean (vs this endpoint's MTP 27.6-28.1 and the old halogen-era MTP
-# 26.9), prefill ~566 t/s at 32k (was ~400 on the sibling engine), 1.4-2.3x
-# wall-clock on prefill-heavy agent traffic, at HIGHER effective precision
-# (~6.32 bpw vs ~6.6 with the old W4A4 promotion — see FLAGS.md).
-#
-# SHAPE — the two knobs that are NOT free:
-#   HALOGEN_KV_SLOTS=1 KEEPS SPECULATION ON. halogen makes batching and
-#   speculation mutually exclusive: with >1 slot the drafter is disabled
-#   and per-stream decode falls to serial speed (the sibling engine
-#   measured 41 t/s -> 14 t/s when slots were raised, and halogen's own
-#   FLAGS.md prints the same law). frank-large was already a one-session
-#   endpoint under ROCmFPX (PARALLEL=1), so slots=1 is the same contract,
-#   not a regression.
-#   HALOGEN_SLOT_CTX=200700 (Frank's window) is the per-conversation hard
-#   ceiling — a prompt over it is a 400 naming the limit, never a silent
-#   truncation. KV pool = slots x slot_ctx x 64 KiB = 12.2 GiB. Budget
-#   against the 121 GiB of unified memory: weights 33.4 GiB (mmap'd — page
-#   cache, not anon), KV 12.2, engine working set + auto prompt cache
-#   ~20-30, host baseline ~10 -> ~75-85 GiB in use. The 2026-09-16 halogen
-#   era ran the same engine class on this box with LESS headroom.
-#   HALOGEN_DRAFTER=2 (DFlash2) is the shipped default and the fastest
-#   exact drafter on this checkpoint; the .hgn BAKES BOTH drafters (MTP +
-#   DFlash2), so unlike the Flash-Next era there is no sidecar to mount
-#   and no --dflash flag — the drafter is an int knob, byte-identical
-#   output to greedy verification either way.
-#
-# CLIENT CONTRACT deltas vs the ROCmFPX shape (the harness side lives in
-# ~/.omp/agent/models.yml):
-#   * NO server-side sampler defaults: a request without temperature
-#     decodes GREEDY. The harness sends temp 1.0 / top_p 0.95 via
-#     extraBody, so that wire recipe is load-bearing now, not cosmetic.
-#   * max_tokens defaults to 8192 PER REQUEST and INCLUDES thinking; a
-#     reasoning reply over a small budget returns empty content with
-#     finish_reason "length". The harness maxTokens is 57344: compaction
-#     fires at 70% of 200700 = 140,490 and 140,490 + 57,344 = 197,834 <=
-#     200,700 keeps prompt + budget inside the pool (the 262144-era 65536
-#     would overflow). Requests over HALOGEN_MAX_TOKENS_CAP are a 400
-#     naming the cap; cap and queue timeout are COUPLED (see FLAGS.md
-#     table) — do not move one without the other.
-#   * response_format json_object/json_schema is a 400 (no constrained
-#     decoding in this build).
-#   * Thinking lands in reasoning_content — same field as the llama.cpp
-#     era, so the harness compat block does NOT change. reasoning_effort
-#     accepts none|low|xhigh on this build (template default xhigh); the
-#     models.yml fold (high->xhigh) still applies.
-#   * The engine's token protocol has no auth and binds loopback INSIDE
-#     the container; only the frontend port is published. Keep it that way.
-
-# Image: digest-pinned (fetch law: tag pulls silently re-point; the digest
-# is what was qualified). 0.1.4 = the version the model card names.
-FRANK_LARGE_IMAGE=ghcr.io/peonist-ai/halogen@sha256:dc0a39a0016d6cfc58a197978febaafdf8d28403f724ded6111d98b5fb7ac0ea
-# Container identity: the halogen container name.
-FRANK_LARGE_CONTAINER=frank-large-halogen
-# Old quadlet-era container identity; the serve script clears stale names.
-FRANK_LARGE_LEGACY_CONTAINERS=frank-large
-# host:container — the frontend listens on 8731 inside (HALOGEN_API_PORT
-# default); the engine port (8730) is never published.
-FRANK_LARGE_PUBLISH=7770:8731
-
-FRANK_LARGE_MODEL_DIR=/home/dank/models/halogen-qwen3.8-27b
-FRANK_LARGE_CHECKPOINT=qwen3.8-27b-p1w4d-d2.hgn
-FRANK_LARGE_CHECKPOINT_BYTES=35865565184
-FRANK_LARGE_CHECKPOINT_SHA256=274c3fc767fb57faf025dd03c76376b1fc1b32448aef45aaf02d1898fa962089
-# The tokenizer is a FLAT DIRECTORY, $FRANK_LARGE_MODEL_DIR/tokenizer, mounted
-# whole at /tokenizer — the model card ships `tokenizer/` and the engine's
-# HALOGEN_TOKENIZER default is that directory (the card's own docker run sets
-# no tokenizer flag). The Hub stores it as 5 files (sizes from the Hub API,
-# 2026-10-05): tokenizer.json 12809320 (LFS sha256
-# 0997f410c57a1f4e53b09e4be8f4a172d90edd9564368fb0847030937229b9f3),
-# vocab.json 6722759, merges.txt 3353259, chat_template.jinja 8952,
-# tokenizer_config.json 17928 (plain git blobs — size-checked, no LFS oid).
-# The serve gate and the deployer refuse a missing file or ANY symlink: an
-# HF cache snapshot symlinks each file into blobs/, and those links dangle
-# inside the container mount.
-FRANK_LARGE_TOKENIZER_FILES="tokenizer.json chat_template.jinja tokenizer_config.json merges.txt vocab.json"
-
-# --- engine flags (docs/FLAGS.md of the engine repo; anything unset stays
-# at the image default, which is what was qualified) ------------------------
-HALOGEN_MODEL_ID=frank-large
-HALOGEN_SLOT_CTX=200700
-HALOGEN_KV_SLOTS=1
-HALOGEN_DRAFTER=2
-# Coupled pair (FLAGS.md table): the cap bounds how long ONE request holds
-# the GPU, the timeout bounds how long the NEXT client waits. 65536 at
-# ~10 t/s serial worst case needs > 6550 s queue timeout; the defaults
-# honor that. Do not lower the timeout alone.
-HALOGEN_MAX_TOKENS_CAP=65536
-HALOGEN_QUEUE_TIMEOUT=7200
-# Engine prompt cache: EMPTY = auto (sized from available memory at
-# startup). Pin an explicit MB only to argue with the auto figure — a
-# full-context entry is ~18 GB at 262K, so a too-small pin yields a cache
-# that reports enabled and never hits (the engine warns at startup).
-#HALOGEN_CACHE_MB=

scripts/frank-primary.env

@@ -1,82 +0,0 @@
-# frank-primary.env — FreeToken (PR #587 ROCm) serving the orcarouter
-# Qwen3.8-Flash-Next-Uncensored-FP8 payload on dankserver :7770.
-#
-# 2026-10-05 cutover from the tcclaviger RDNA4 vLLM fork (git tag
-# frank-primary-vllm-shapeG-20261003 is the pre-cutover state; the 362-line
-# vLLM-era env is in that tag). The engine is FreeToken at PR head
-# 77a7201f98f00d93f618c6cf8b81ffe8360e0899 (branch rocm714_torch214), built
-# on the host into a local image by
-# scripts/docker/frank-primary-freetoken.Dockerfile — the PR's own
-# docs/install_amd.md stack (ROCm 7.14 base image, torch 2.11.0+rocm7.14,
-# triton 3.7) for gfx1201.
-#
-# WHY FREETOKEN: the vLLM fork's expert offload planned VRAM/host tiers per
-# boot from an estimator (util 0.982 law, arena 17.77 GiB / 7,762 slots,
-# ~40k-token GDN state faults) and 1.0 was unbootable. FreeToken keeps ALL
-# expert weights in pinned HOST RAM (~120 GiB) with an LRU GPU cache, sizes
-# KV from an explicit token pool, and serves on ONE R9700 (32 GB) with the
-# second card idle. RAM fit: 246 GiB total, service stopped frees the vLLM
-# container's ~170 GiB; weights ~120 GiB + PLE 47.7 GiB + overhead ≈ 190 GiB.
-#
-# PAYLOAD: unchanged — /home/dank/models/Qwen3.8-Flash-Next-Uncensored-FP8,
-# 131 safetensors shards. Quant is standard modelopt block-FP8: 75,264
-# weight_scale_inv tensors (block 128x128), zero input_scale (FreeToken #462
-# covers exactly this export shape), one weight_scale on the PLE ngram
-# embedding. FreeToken loads HF safetensors directly; no FTW conversion.
-#
-# SERVING FACTS (docs/cli.md, verified against main+PR587):
-# - `ft serve` loads the checkpoint directly; `--served-model-name` keeps the
-#   harness id; reasoning/tool parsers are AUTO (reasoning lands in
-#   reasoning_content — models.yml flips reasoningContentField to match).
-# - KV: --page-size must stay 1 for GDN/SWA models (default); --cache-type
-#   radix auto-picks the GDN-aware variant.
-# - MoE: --moe-strategy auto -> offload (fp8 experts CANNOT use
-#   --moe-cpu-layers; only bf16/nvfp4/mxfp4 have a CPU executor).
-#   --moe-cache-rate holds the GPU LRU fraction of all experts.
-# - `ft ctl cache --kv --moe` grows the pools LIVE on a running server
-#   (shrinking needs a restart); `ft ctl stats` reports pool occupancy.
-# - KV MATH: 12 full-attention layers x 2 KV heads x 256 head_dim x 2 (K+V)
-#   x 2 B = 24 KiB/token (f16 KV; the 36 GDN layers use fixed per-seq state,
-#   not per-token KV). See FRANK_PRIMARY_FT_NUM_TOKENS below for the pool
-#   size and its measured page-size law.
-FRANK_PRIMARY_IMAGE=localhost/frank-primary-freetoken:pr587-77a7201
-FRANK_PRIMARY_MODEL_DIR=/home/dank/models/Qwen3.8-Flash-Next-Uncensored-FP8
-FRANK_PRIMARY_MODEL_SHARDS=131
-# Container identity is the SERVICE name (Frank's call, 2026-10-05): one
-# name across systemctl and podman ps. The vLLM-era name frank-primary-qwen
-# moved into the legacy list so every deploy cleans it up.
-FRANK_PRIMARY_CONTAINER=frank-primary
-FRANK_PRIMARY_LEGACY_CONTAINERS="frank-primary-qwen frank-primary-r9v qwen-fp8 glm-probe"
-FRANK_PRIMARY_SERVED_NAME=frank-primary
-FRANK_PRIMARY_PUBLISH=7770:7770
-
-# --- FreeToken engine knobs (first-boot conservative, resize live) -----
-# Single GPU: the R9700 at index 0. HIP_VISIBLE_DEVICES=0 hides card 1 so
-# the in-container index 0 IS the right card; --gpu 0 selects it.
-FRANK_PRIMARY_FT_GPU=0
-# KV pool in TOKENS (not bytes — vLLM-era FRANK_PRIMARY_KV_BYTES is gone).
-# 299,968 tokens x 24 KiB = 7.0 GiB; clears the harness worst case
-# (177,356 tokens) and one NATIVE 262,144-token conversation + full budget.
-# MEASURED FIRST BOOT (2026-10-05): the auto attention backend is
-# qsa_sparse, which OVERRIDES page size to 64, so --num-tokens must be a
-# MULTIPLE OF 64 — 300,000 was refused ("nearest valid values: 299968 or
-# 300032"). Grows live with `ft ctl cache --kv <n>`; shrink needs a
-# restart.
-FRANK_PRIMARY_FT_NUM_TOKENS=299968
-# Concurrent decode slots. 2 is the first-boot conservative value; the
-# radix pool admits ~2 full-length 200,704-token conversations. Raise with
-# --max-running-requests only after a real-traffic look at slot occupancy.
-FRANK_PRIMARY_FT_MAX_RUNNING=2
-# Per-request output budget ceiling: the harness's maxTokens (36,864).
-# Requests that omit max_tokens get this default instead of the engine's
-# 32,768.
-FRANK_PRIMARY_FT_MAX_OUTPUT_TOKENS=36864
-# GPU expert LRU cache as a FRACTION of all experts (~120 GiB fp8 total ->
-# ~12 GiB VRAM at 0.10). First-boot conservative; resize live with
-# `ft ctl cache --moe` after reading the boot ledger + ft ctl stats.
-FRANK_PRIMARY_FT_MOE_RATE=0.10
-# Escape hatch for boot-ladder experiments (YaRN, --max-prefill-length,
-# --moe-cpu-threads, --sampling-defaults none, ...). Unset -> no extra
-# argv. Keep multi-flag values as one string; the serve script expands it
-# unquoted on purpose.
-FRANK_PRIMARY_FT_EXTRA_ARGS=

scripts/frank-primary.service

@@ -1,65 +0,0 @@
-# frank-primary.service — FreeToken (PR #587 ROCm) endpoint (orcarouter
-# Qwen3.8-Flash-Next-Uncensored-FP8, 131-shard payload) on ONE R9700
-# (gfx1201), dankserver :7770. 2026-10-05 cutover from the tcclaviger vLLM
-# fork (git tag frank-primary-vllm-shapeG-20261003 is the pre-cutover
-# state; the retired unit/env/serve trio is in that tag).
-#
-# Same port, same served alias, same container identity as the unit name;
-# the harness models.yml id is unchanged. The serve script drives
-# `podman run` directly (the image carries `ft serve`) and then waits on
-# the container. The image is built ON THE HOST from
-# scripts/docker/frank-primary-freetoken.Dockerfile (FreeToken PR head
-# 77a7201 in the PR's own ROCm 7.14 base image).
-#
-# WHY A ROOT UNIT (not a rootless quadlet): FreeToken pins ~120 GiB of
-# expert weights plus the ~47.7 GiB PLE ngram table in HOST RAM. Pinned
-# pages are charged against RLIMIT_MEMLOCK; dank's login session on this
-# host carries 8 MiB and a user quadlet is capped by the user manager's own
-# hard limit — raising that means restarting user@1000.service and bouncing
-# every user container on the host. A root unit grants
-# LimitMEMLOCK=infinity to the dank process via PID1, and the image stays
-# in dank's rootless podman storage.
-[Unit]
-Description=frank-primary — FreeToken (PR587) Qwen3.8-Flash-Next-Uncensored-FP8 on 1x R9700
-After=network-online.target
-Wants=network-online.target
-# Never let the start-rate limiter give up after a crash loop (a failed LLM
-# endpoint that systemd refuses to retry is worse than a retrying one).
-StartLimitIntervalSec=0
-
-[Service]
-User=dank
-Group=dank
-# The expert LRU + PLE pin ~170 GiB of host RAM; an RLIMIT_MEMLOCK smaller
-# than the pinned set fails the load mid-start. PID1 grants infinity here —
-# parity with the fleet's other LLM units.
-LimitMEMLOCK=infinity
-Environment="FRANK_PRIMARY_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-primary.env"
-ExecStart=/home/dank/serverAppConfigs/scripts/serve-frank-primary.sh
-# systemd stop: wait alone cannot stop the container child; stop it
-# explicitly. ft serve drops connections on SIGTERM; no graceful drain
-# contract is claimed (the OpenAI front end holds no queue to drain —
-# in-flight decodes are lost, which a stop during a bench window accepts).
-ExecStop=/usr/bin/podman stop -t 120 frank-primary
-# Boot cost: 131-shard FP8 page-in + PLE pin + expert upload. vLLM-era
-# budget (1800 s) carried forward; the FreeToken first boot measured here
-# once it ran (see the runbook for the real number).
-TimeoutStartSec=1800
-# Restart=always, NOT on-failure (the 2026-10-01 vLLM lesson carries over:
-# a clean API-server exit after a worker fault reads as success to
-# systemd). `always` restarts on any container death; an explicit
-# `systemctl stop` still wins, so bench windows and deploys are unaffected.
-Restart=always
-RestartSec=10
-# ExecStop allows the engine 120 s to drain (`podman stop -t 120`); without
-# an explicit TimeoutStopSec systemd's 90 s default cuts the stop short,
-# kills it, and records 'Failed with result timeout' (measured 2026-10-01
-# 13:27:17). Must exceed the podman grace with margin.
-TimeoutStopSec=180
-# The engine pins tens of GiB of host RAM (expert rows + PLE table); it is
-# the last process on this host that should be chosen by the kernel OOM
-# killer.
-OOMScoreAdjust=-500
-
-[Install]
-WantedBy=multi-user.target

scripts/frank-small.env

@@ -1,136 +0,0 @@
-# frank-small — llama.cpp (master, CUDA sm_86) serving
-# ornith-ai/Ornith-1.5-9B-GGUF:Q8_0 on the RTX 3090, :7771.
-#
-# 2026-10-05 (Frank): the payload moved off bartowski/MiMo-V2.6 (Q6_K) to
-# ornith-ai/Ornith-1.5-9B Q8_0 (9,786,060,384 B, LFS oid 22086870...).
-# Header-verified facts that re-price the shape: qwen35 hybrid like MiMo, but
-# 33 blocks (not 32) with full_attention_interval 4 => NINE full-attention
-# layers (MiMo had 8), 16 Q heads / 4 KV heads, k/v length 256, native window
-# 262144, dense (no expert keys), nextn_predict_layers=1 (an MTP head is IN
-# the file — capability only; no spec decode ships, same law as before).
-#
-# THE KV CONTRACT STAYS f16 K + f16 V — NO KV QUANTIZATION (Frank, 2026-10-05,
-# overruling a written q8_0-V proposal). The arithmetic that makes this hard:
-#   KV rate 9 attn layers x 4 heads x 256 x 2 B = 18 KiB/token K, same again
-#   for V at f16 => 36 KiB/token (MiMo was ~24.5 measured: one fewer
-#   full-attn layer AND one fewer KV head).
-#   Weights +1,900 MiB (9,334 vs Q6_K's 7,432). Measured free at the Q6_K
-#   4096/2048 shape was 2,279 MiB; Q8_0 at f16/f16 does not fit that shape —
-#   the deficit is made up the way Frank ordered: UBATCH FIRST (2048 -> 1024,
-#   the measured 616 MiB rung), then POOL STEPS, then measure. Guess-and-check
-#   on the live card is the accepted method for llama.cpp sizing here: boot,
-#   read nvidia-smi free, step the pool (12,288-token increments, ~432 MiB
-#   each at the 36 KiB/token rate) until the 2-3 GiB floor holds. Compute
-#   buffers allocate at graph capture during BOOT, so a failure is loud and
-#   fast, not a surprise at the first long prompt.
-#
-# Previous shape history (MiMo era, for the rollback trail): 2026-10-03 the
-# rung went Q5_K_M -> Q6_K with the pool HELD at 401,408; the freed third
-# slot funded exact f16 V first; the ~3.5 GiB still free funded the +875 MiB
-# of weights.
-#
-# 2026-10-03 (Frank): TWO streams instead of three, each one WIDE — 200,704
-# tokens per conversation, above the 200,700 the harness compacts at — and the
-# KV cache is now FULLY UNQUANTIZED (f16 K, f16 V). The two moves are the same
-# move: llama.cpp divides --ctx-size across --parallel slots, so the slot given
-# up is exactly the VRAM that pays for unquantized V. No further quantization
-# anywhere on this endpoint.
-#
-# Three measurements on this card, this runtime, price the terms:
-#   2 x 262,144, no projector: 20,190 MiB used / 4,386 free
-#     KV = 524,288 tok x 24.5 KiB = 12,800 MiB => non-KV (weights 6,557 +
-#     DeltaNet state ~25/slot + compute buffers + CUDA graphs) = 7,390 MiB
-#   3 x 196,608, projector on: 22,972 MiB used / 1,153 free
-#     KV = 14,113 MiB => non-KV WITH the vision tower = 8,859 MiB
-#   3 x 180,224, projector on: 21,684 MiB used / 2,441 free (the 2026-10-02
-#     shape) => non-KV = 8,748 MiB
-# Two slots give back one DeltaNet state (~25 MiB). Priced at f16 K+V
-# (32 KiB/token) this pool is 12,544 MiB, so the prediction is
-# 12,544 + ~8,800 = ~20.9 GiB used, ~3.1 GiB free — the band the 2026-10-02
-# shape hit, bought with precision instead of a slot. The 1024 ubatch
-# re-prices the compute buffers upward, so MEASURE after any change: if the
-# boot lands under 2 GiB free, step the pool down in 12,288-token
-# (384 MiB at this rate) increments.
-#
-# KV arithmetic: attention KV exists only in the 8 full-attention layers
-# (4 KV heads x 256 head_dim x 2 B) = 16 KiB/token for K and the same again for
-# V => 32 KiB/token, so 12,288 tokens (= 6144/slot) is one 384 MiB step — that
-# is the ladder to walk if this moves again. Two native windows (2 x 262,144)
-# are NOT reachable with full-precision V: 524,288 x 32 KiB = 16.1 GiB of KV
-# against a card with ~15.7 GiB of KV room once weights, the vision tower, the
-# DeltaNet states and the graphs are loaded. 200,704 per stream is what full
-# precision buys; q8_0 on V would buy 262,144 instead.
-#
-# The asymmetric-KV contract this endpoint was created for (Frank, 2026-10-01
-# night: f16 K + q8_0 V) is now spent — it existed to make a third slot fit,
-# and the third slot is gone. The flags stay explicit so the choice is visible
-# in the argv either way.
-LLAMA_BIN=/home/dank/GitPackages/llama-master/build-cuda/bin/llama-server
-MODEL_FILE=/home/dank/models/Ornith-Q8/Ornith-1.5-9B-Q8_0.gguf
-
-# Vision: the Ornith Q8_0 GGUF ships no `v.*` tensors either (dense-9B byte
-# arithmetic: 9.79 GB ≈ 9B params x ~1.06 B/param leaves no room for a tower),
-# so the projector file IS the vision capability (mmproj-Ornith-1.5-9B-BF16
-# .gguf, 921,704,672 B, LFS oid 626f9f90..., fetched by
-# scripts/download-frank-small.sh). Empty string = text-only on purpose.
-MMPROJ_FILE=/home/dank/models/Ornith-Q8/mmproj-Ornith-1.5-9B-BF16.gguf
-
-# Fleet endpoint: same port and alias as every frank-small before it, so the
-# harness models.yml id and the homepage probe do not move.
-ALIAS=frank-small
-BIND_ADDR=0.0.0.0
-LISTEN_PORT=7771
-
-# ONE conversation at the NATIVE 262,144 window (Frank, 2026-10-05). The
-# two-slot shape died under Ornith and the NO-QUANTIZE law, by arithmetic:
-# the KV rate is the ARCHITECTURE's, not the quant's — 9 full-attn layers x
-# 4 KV heads x 256 dim x 2 B = 36 KiB/token at f16 K+V (MiMo measured 24.5),
-# so 2 x 200,704 wants ~14.1 GiB of KV on top of +1,900 MiB of Q8 weights
-# against 2,279 MiB measured free; ubatch 1024 claws back 616, and no
-# pool step fits BOTH the 2-3 GiB floor and the harness compaction
-# invariant (slot >= 191,148). One native slot fits with room; the window
-# per conversation RISES 200,704 -> 262,144. The cost: a second concurrent
-# request queues behind the released slot (subagent concurrency 2 -> 1).
-CTX_SIZE=262144
-PARALLEL=1
-
-# Compute-buffer geometry. This endpoint passed neither flag until 2026-10-03,
-# so it ran on llama.cpp's own defaults (2048/512); the pair is now 4096/2048.
-# Both are tunables because the pair is a measurement, not a law — and the
-# measurement is CARD-SPECIFIC. On the 2x R9700 layer-split sibling the ubatch
-# curve peaks at 512 and every step up costs GiB of compute buffer for no
-# speed (see frank-medium-batch-ubatch). On THIS CUDA 3090 the curve climbs
-# monotonically to 2048: 710 -> 1188 t/s prefill from ubatch 1024 to 2048 on
-# the 35B MoE sweep, 1944 -> 2423 t/s on the Ornith 8k sweep, with decode flat
-# to under 1 t/s on every rung. Ubatch is a prefill knob; decode never moves.
-#
-# The logical batch is free — two independent sweeps agree that at a fixed
-# ubatch, 2048/4096/8192 give identical prefill speed AND identical peak VRAM,
-# because the compute buffers are sized by the ubatch alone. Doubling it costs
-# nothing and buys nothing; it is here because it is the value the pair was
-# measured at.
-#
-# THE RISK IS ALL IN THE UBATCH. The 1024 -> 2048 step cost ~1,244 MiB of peak
-# graph VRAM on the 35B MoE (7,330 -> 8,574 MiB); this 9B hybrid has far
-# smaller compute tensors, so the delta should be well under that, but the
-# predecessor Q5_K_M shape recorded "ubatch 2048 failed the scratch boot" at
-# ~3,571 MiB free. The Q8_0 rung ships UBATCH 1024 (Frank, 2026-10-05: lower
-# ubatch FIRST — the measured 616 MiB step is the first VRAM the Q8 weights
-# claw back, before any pool move). Compute buffers are allocated at graph
-# capture during BOOT, so a failure is loud and fast, not a surprise at the
-# first long prompt. MEASURE nvidia-smi free immediately after the deploy:
-# under ~1.5 GiB, or a boot failure, step the POOL down next (12,288-token
-# increments, ~432 MiB each at the Ornith 36 KiB/token f16 KV rate).
-BATCH_SIZE=4096
-UBATCH_SIZE=1024
-
-# The KV contract (2026-10-05, Frank): f16 K + f16 V — NO KV quantization.
-# The q8_0-V arithmetic was written and OVERRULED. The Q8 weights eat the
-# VRAM that funded f16 V on 2026-10-03, so the remedy ladder is UBATCH FIRST
-# (2048 -> 1024, the measured 616 MiB rung), then POOL STEPS — and
-# guess-and-check on the live card is the accepted method: boot, read
-# nvidia-smi, step down until the floor holds. --flash-attn stays pinned on
-# in the serve script: it is the fast path for f16 KV.
-CACHE_TYPE_K=f16
-CACHE_TYPE_V=f16
-NGL=99

scripts/frank-small.service

@@ -1,19 +0,0 @@
-[Unit]
-Description=llama.cpp MiMo-V2.6-Distill-Qwen-9B Q6_K GGUF (qwen35 hybrid, 2x200704, unquantized f16 KV, mmproj vision) on the RTX 3090 (dankclaw, frank-small)
-After=network-online.target
-Wants=network-online.target
-
-[Service]
-Type=simple
-User=dank
-Group=dank
-# CUDA pins its staging buffers, so the process needs the memlock budget even
-# though the weights themselves are copied into VRAM.
-LimitMEMLOCK=infinity
-Environment="FRANK_SMALL_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-small.env"
-ExecStart=/home/dank/serverAppConfigs/scripts/serve-frank-small.sh
-Restart=on-failure
-RestartSec=10
-
-[Install]
-WantedBy=multi-user.target

scripts/frank-zealot.env

@@ -0,0 +1,62 @@
+# frank-zealot — llama.cpp (master, CUDA sm_86) serving
+# HauhauCS/Qwen3.5-9B-Uncensored-HauhauCS-Aggressive at Q6_K on the RTX 3090,
+# :7771.
+#
+# 2026-10-07 (Frank): swap from Gemma4-26B-A4B QAT Q4_K_M (one 200,704 slot)
+# to Qwen3.5-9B Q6_K at TWO 200,704-token conversations, EXACT (f16) KV,
+# MTP disabled (SPEC_TYPE=none), log verbosity 4.
+#
+# Architecture — read from the GGUF's own header (HTTP range read, not the
+# model card): arch qwen35, 32 layers, dense 9B, full_attention_interval 4
+# ⇒ 8 full-attention layers (3,7,11,...,31) + 24 Gated DeltaNet linear layers,
+# 16 attention heads / 4 KV heads × 256 dim, ssm conv_kernel 4 / state_size
+# 128 / group_count 16 / time_step_rank 32 / inner_size 4096, native 262,144,
+# vocab 248,320, file_type 18 (Q6_K). Tensor-type histogram: Q6_K×250 +
+# F32×177 — standard types only, so the stock master build loads it (no
+# custom-quant lock-in like the ROCmFPX era). NO nextn/mtp tensors exist, so
+# in-file MTP is impossible here; SPEC_TYPE=none is forced by the payload.
+#
+# KV rate law: 8 full layers × 4 KV heads × 256 dim = 8,192 elements per
+# token per cache. f16 K + f16 V = 32,768 B/token = 32 KiB/token, so the
+# 401,408-token pool is 12.25 GiB. The 24 DeltaNet layers cost a fixed
+# recurrent state per SLOT (not per token) — that is why two 200k slots fit
+# where the 26B MoE fit only one.
+#
+# Feasibility comes from the predecessor's MEASURED boots, not a formula:
+# MiMo-V2.6-Distill-Qwen-9B (identical qwen35 geometry, 7,793,710,624 B) at
+# 2×200,704 f16 K + f16 V measured 21,276 used / 2,849 free at ubatch 1024
+# and 21,846 / 2,279 at ubatch 2048. This file is 415 MiB lighter in weights,
+# its BF16 mmproj is 3 MiB heavier ⇒ projected ~21,430 used / ~2,700 free.
+# The verbosity-4 boot ledger is the referee.
+#
+# Ubatch 2048 is the measured CUDA optimum (measured on the MiMo predecessor
+# at this exact arch + shape: +4.6 % prefill at 8.9k depth, decode flat, cost
+# 616 MiB). 1024 is the fallback rung if the boot lands under the 2 GiB floor.
+LLAMA_BIN=/home/dank/GitPackages/llama-master/build-cuda/bin/llama-server
+MODEL_FILE=/home/dank/models/Qwen35-9B-HauhauCS-Q6K/Qwen3.5-9B-Uncensored-HauhauCS-Aggressive-Q6_K.gguf
+MMPROJ_FILE=/home/dank/models/Qwen35-9B-HauhauCS-Q6K/mmproj-Qwen3.5-9B-Uncensored-HauhauCS-Aggressive-BF16.gguf
+# Served model id — the harness/family name (Protoss rename completed to the
+# wire 2026-10-09: harness ids + homepage cards 2026-10-08, /v1/models aliases
+# this day). The SERVICE, unit, scripts and this env file keep the
+# frank-zealot name; only the alias on the wire changed. Consumers that
+# key on the served id: OpenWebUI (model row, access_grant, api_configs
+# model_ids) and the harness models.yml.
+ALIAS=frank-zealot
+BIND_ADDR=0.0.0.0
+LISTEN_PORT=7771
+# CTX_SIZE is the POOL llama.cpp divides across slots: 401,408 / 2 = 200,704
+# per conversation. MUST stay divisible by PARALLEL (the seam enforces it) and
+# the harness contextWindow quotes the PER-SLOT number — a longer prompt is
+# answered with a 400, never truncated.
+CTX_SIZE=401408
+PARALLEL=2
+BATCH_SIZE=4096
+UBATCH_SIZE=2048
+CACHE_TYPE_K=f16
+CACHE_TYPE_V=f16
+SPEC_TYPE=none
+NGL=99
+# Log verbosity threshold (llama.cpp -lv). 4 = debug: KV layout, buffer sizes
+# and graph capture land in the journal, which is what the VRAM-fit forensics
+# read. Levels above 4 flood the journal.
+VERBOSITY=4

scripts/frank-zealot.service

@@ -0,0 +1,19 @@
+[Unit]
+Description=llama.cpp Qwen3.5-9B-Uncensored-HauhauCS-Aggressive Q6_K GGUF (qwen35 hybrid, 2x200704 slots, f16 K+V, MTP off, mmproj vision) on the RTX 3090 (dankclaw, frank-zealot)
+After=network-online.target
+Wants=network-online.target
+
+[Service]
+Type=simple
+User=dank
+Group=dank
+# CUDA pins its staging buffers, so the process needs the memlock budget even
+# though the weights themselves are copied into VRAM.
+LimitMEMLOCK=infinity
+Environment="FRANK_ZEALOT_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-zealot.env"
+ExecStart=/home/dank/serverAppConfigs/scripts/serve-frank-zealot.sh
+Restart=on-failure
+RestartSec=10
+
+[Install]
+WantedBy=multi-user.target

scripts/hfget.sh

@@ -0,0 +1,107 @@
+#!/bin/sh
+# hfget.sh -- fetch a Hugging Face repo with curl and jq, and nothing else.
+#
+# The engine and its tooling do not depend on Python, so `huggingface-cli` is not assumed. The API
+# gives a file listing as JSON and every file has a stable resolve/ URL, which is all a downloader
+# needs.
+#
+#   scripts/hfget.sh <repo-id> [dest-dir] [revision]
+#
+# Set HF_TOKEN for a gated or private repo. Re-running resumes: a file whose local size already
+# matches the listing is skipped and a short one is continued with `curl -C -`, so an interrupted
+# transfer of a 300 GB checkpoint costs only what it had not finished.
+#
+# WEIGHT DUPLICATES ARE SKIPPED. Many repos carry the same tensors several times over -- safetensors
+# beside the older pickle .bin, an ONNX export, a GGUF conversion -- and on a large checkpoint each
+# copy is hundreds of gigabytes of the same numbers. When the listing holds any .safetensors, every
+# other weight format is left behind.
+#
+# HFGET_JOBS concurrent transfers, default 4. These are long sequential reads: a few streams
+# saturate the link and more only makes the destination seek.
+set -e
+
+# ---- child mode: one file, named by "<size><tab><path>" in $1, everything else inherited -------
+# sh cannot export a function, so parallelism is one re-entry of this script per file under
+# `xargs -P` rather than a worker pool.
+if [ -n "$HFGET_CHILD" ]; then
+    size=${1%%	*}; path=${1#*	}
+    out=$HFGET_DEST/$path
+    if [ -f "$out" ]; then
+        cur=$(wc -c < "$out")
+        if [ "$cur" = "$size" ]; then echo "  = $path"; exit 0; fi
+        echo "  + $path (resuming at $cur of $size)"
+    else
+        echo "  > $path"
+    fi
+    mkdir -p "$(dirname "$out")"
+    if [ -n "$HF_TOKEN" ]; then
+        curl -sSL --fail --retry 5 --retry-delay 5 --retry-all-errors -C - \
+             -H "Authorization: Bearer $HF_TOKEN" \
+             -o "$out" "https://huggingface.co/$HFGET_REPO/resolve/$HFGET_REV/$path"
+    else
+        curl -sSL --fail --retry 5 --retry-delay 5 --retry-all-errors -C - \
+             -o "$out" "https://huggingface.co/$HFGET_REPO/resolve/$HFGET_REV/$path"
+    fi
+    got=$(wc -c < "$out")
+    [ "$got" = "$size" ] || { echo "hfget: $path is $got bytes, listing says $size" >&2; exit 1; }
+    exit 0
+fi
+
+# ---- parent ------------------------------------------------------------------------------------
+repo=$1
+[ -n "$repo" ] || { echo "usage: hfget.sh <repo-id> [dest-dir] [revision]" >&2; exit 2; }
+dest=${2:-$HOME/models/$repo}
+rev=${3:-main}
+jobs=${HFGET_JOBS:-4}
+command -v jq >/dev/null || { echo "hfget: jq is required" >&2; exit 2; }
+
+echo "hfget: listing $repo@$rev"
+# THE LISTING IS PAGINATED AND THE PAGE SIZE IS SMALL. A large checkpoint runs to a hundred-odd
+# shards and the API returns fifty entries with a `Link: ...; rel="next"` header. Taking only the
+# first page is the worst possible failure here: every file it did fetch is the right length, so
+# the size check passes and the converter is handed a checkpoint missing two thirds of its
+# tensors. Follow the cursor until there is no next link.
+api="https://huggingface.co/api/models/$repo/tree/$rev?recursive=true&expand=true"
+listing='[]'
+page=0
+while [ -n "$api" ]; do
+    hdr=$(mktemp "${TMPDIR:-/tmp}/hfhdr.XXXXXX")
+    if [ -n "$HF_TOKEN" ]; then
+        body=$(curl -sSL --fail-with-body -D "$hdr" -H "Authorization: Bearer $HF_TOKEN" "$api")
+    else
+        body=$(curl -sSL --fail-with-body -D "$hdr" "$api")
+    fi
+    [ "$(printf '%s' "$body" | jq -r 'type')" = "array" ] || {
+        rm -f "$hdr"
+        echo "hfget: $(printf '%s' "$body" | jq -r '.error // .message // .')" >&2
+        echo "hfget: a gated or private repo needs HF_TOKEN in the environment" >&2; exit 1; }
+    listing=$(printf '%s\n%s' "$listing" "$body" | jq -s 'add')
+    api=$(tr -d '\r' < "$hdr" | sed -n 's/^[Ll]ink: *<\([^>]*\)>; *rel="next".*/\1/p' | head -1)
+    rm -f "$hdr"
+    page=$((page + 1))
+    [ "$page" -gt 200 ] && { echo "hfget: listing did not terminate after 200 pages" >&2; exit 1; }
+done
+echo "hfget: $page page(s) of listing"
+have_st=$(printf '%s' "$listing" | jq '[.[] | select(.path | endswith(".safetensors"))] | length')
+sel='.[] | select(.type == "file")'
+[ "$have_st" -gt 0 ] && sel="$sel"' | select((.path | test("\\.(bin|pth|msgpack|h5|onnx|onnx_data|gguf)$")) | not)'
+
+list=$(mktemp "${TMPDIR:-/tmp}/hfget.XXXXXX")
+trap 'rm -f "$list"' EXIT INT TERM
+printf '%s' "$listing" | jq -r "$sel"' | "\(.size)\t\(.path)"' > "$list"
+
+n=$(wc -l < "$list")
+[ "$n" -gt 0 ] || { echo "hfget: the listing has no files" >&2; exit 1; }
+need=$(awk -F'\t' '{s += $1} END {printf "%.1f", s / 1073741824}' "$list")
+mkdir -p "$dest"
+free=$(df -BG --output=avail "$dest" | tail -1 | tr -dc '0-9')
+echo "hfget: $n file(s), $need GiB -> $dest"
+[ "$have_st" -gt 0 ] && echo "hfget: safetensors present, pickle weight formats skipped"
+echo "hfget: $free GiB free on the destination filesystem"
+awk -v n="$need" -v f="$free" 'BEGIN { if (n > f) { print "hfget: THE DOWNLOAD DOES NOT FIT"; exit 1 } }'
+
+export HFGET_CHILD=1 HFGET_DEST="$dest" HFGET_REPO="$repo" HFGET_REV="$rev"
+self=$(cd "$(dirname "$0")" && pwd)/$(basename "$0")
+tr '\n' '\0' < "$list" | xargs -0 -P "$jobs" -I{} sh "$self" "{}" \
+    || { echo "hfget: incomplete -- re-run to resume" >&2; exit 1; }
+echo "hfget: complete -- $(du -sh "$dest" | cut -f1) in $dest"

scripts/kld-gate-swift15.sh

@@ -0,0 +1,91 @@
+#!/usr/bin/env bash
+# kld-gate-swift15.sh — RUNS ON DANKSERVER. Score the quantized candidate
+# against the BF16 reference and apply the pre-approved gate:
+#   mean KL <= 0.03 AND top-1 agreement >= 95%.
+# Same engine (1.0.13) and same boot shape as the reference RECORD
+# (run-swift15-bf16.sh kld): disk-tier, no speculation, deterministic, fp8 KV.
+# --kld-ref reads its tokens from the reference (no --kld-corpus here — the
+# (run-swift15-bf16.sh kld): 1.0.13, tp 2, disk-tier, fp8 KV, no speculation,
+# deterministic, max-model-len 16384, vram-kv 3072, 4 slots. Two deviations
+# are forced by the w4 file: MNBT 2048 (the w4 kernels stream from the file
+# tier ONLY at MNBT<=2048 — at the recording's 32768 the engine demands a
+# widened form: "DID NOT FIT ... stored form is not the container's"), and
+# pool 40960 (the recording's 12 GiB pool predates the w4 tables; at 12288 the
+# gate_up slab cannot be cached). Chunk size is softmax-invariant, so the
+# MNBT delta is float-order noise riding on the KL floor.
+set -uo pipefail
+PIN=sha256:4c3f484564bb2872784e46b0a59cbd71becc9c1e746e301a3596ffae253c322e
+C=swift15gate
+LOG=/home/dank/logs/swift15_kldgate.log
+KLD_REF_DIR=/home/dank/corpora/kld-ref
+KLD_OUT=/home/dank/radiance-state/kld-gate.json
+
+[ -d "$KLD_REF_DIR" ] || { echo "missing reference: $KLD_REF_DIR"; exit 2; }
+: > "$KLD_OUT"
+cp -f /home/dank/serverAppConfigs/scripts/qwen38-froggeric-v22.5.jinja \
+      /home/dank/models/tpl.jinja 2>/dev/null || true
+sudo systemctl stop frank-archon >/dev/null 2>&1 || true
+podman rm -f "$C" >/dev/null 2>&1 || true
+
+podman run --rm --name "$C" \
+    --network host --init \
+    --security-opt seccomp=unconfined \
+    --ulimit memlock=-1:-1 \
+    --device /dev/kfd --device /dev/dri \
+    -v /home/dank/models:/models:ro \
+    -v /home/dank/radiance-state:/data \
+    -v "$KLD_REF_DIR:/data/kld-ref:ro" \
+    "stilldeadcode/radiance@$PIN" \
+    --model /models/rad/qwen4exp-swift15-w4dn8-i8-hc8m.rad \
+    --tp 2 --placement expert_tiered --weights-disk-tier \
+    --host-pool-mib 40960 --deterministic --gpu-headroom-mib 768 \
+    --num-speculative-tokens 0 \
+    --kv-cache-dtype fp8 --max-model-len 16384 \
+    --ngram-placement ram \
+    --override-chat-template /models/tpl.jinja \
+    --kld-ref /data/kld-ref --kld-out /data/kld-gate.json \
+    --vram-kv-mib 3072 \
+    --max-num-seqs 4 --max-num-batched-tokens 2048 \
+    2>&1 | tee "$LOG"
+rc=${PIPESTATUS[0]}
+[ "$rc" -eq 0 ] || { echo "KLD GATE BOOT FAILED rc=$rc; log: $LOG"; exit "$rc"; }
+
+python3 - "$KLD_OUT" "$LOG" <<'PY'
+import json, sys, re
+out, log = sys.argv[1], sys.argv[2]
+def num(pat):
+    m = re.findall(pat, open(log, errors="replace").read(), re.I)
+    return float(m[-1]) if m else None
+kl = top1 = None
+try:
+    d = json.load(open(out))
+    def find(obj, keys):
+        if isinstance(obj, dict):
+            for k, v in obj.items():
+                if any(s in k.lower() for s in keys) and isinstance(v, (int, float)):
+                    return float(v)
+            for v in obj.values():
+                r = find(v, keys)
+                if r is not None: return r
+        return None
+    kl = find(d, ("mean_kl", "mean kl", "kl_mean", "mean"))
+    top1 = find(d, ("top1", "top_1", "top-1", "agreement"))
+    if top1 is not None and top1 <= 1.0:
+        top1 *= 100.0
+except Exception as e:
+    print("report JSON unusable (%s); falling back to log" % e)
+if kl is None:
+    kl = num(r"mean[_ ]kl[^0-9]*([0-9]*\.?[0-9]+(?:e[-+][0-9]+)?)")
+if top1 is None:
+    top1 = num(r"top[-_ ]?1[^0-9]*([0-9]*\.?[0-9]+)")
+if kl is None or top1 is None:
+    print("KLD GATE PARSE FAILED: mean_kl=%s top1=%s — inspect %s / %s" % (kl, top1, out, log))
+    sys.exit(2)
+print("KLD GATE: mean KL = %.4f (max 0.03) | top-1 = %.2f%% (min 95.0)" % (kl, top1))
+ok = (kl <= 0.03) and (top1 >= 95.0)
+print("KLD GATE " + ("PASS" if ok else "FAIL"))
+sys.exit(0 if ok else 1)
+PY
+gate=$?
+echo "kld-gate complete rc=$gate; log: $LOG report: $KLD_OUT"
+exit "$gate"

scripts/kld-then-calib.sh

@@ -0,0 +1,40 @@
+#!/bin/bash
+# kld-then-calib.sh — RUNS ON DANKSERVER. Campaign chain: wait for the KLD
+# record to finish, verify it, then boot the 1.2.0 calibration server and
+# push the 10M-token corpus. One GPU, so the phases serialize; prod is
+# restored by each run script's trap.
+set -u
+KLOG=/home/dank/logs/swift15-kld-driver.log
+CLOG=/home/dank/logs/swift15-calib-driver.log
+S=/home/dank/serverAppConfigs-swift15/scripts
+# Phase 1: KLD record (SKIP_KLD=1 when the record is already complete —
+# kld.json's rows count is the receipt; a mid-run script swap can kill the
+# wrapper with rc=127 after the engine exited clean).
+if [ "${SKIP_KLD:-0}" != 1 ]; then
+    while ! grep -q "exited rc=" "$KLOG" 2>/dev/null; do sleep 60; done
+    RC=$(grep -o "exited rc=[0-9]*" "$KLOG" | tail -1)
+    if [ "$RC" != "exited rc=0" ]; then echo "KLD FAILED ($RC); calib NOT started"; exit 1; fi
+fi
+N=$(find /home/dank/corpora/kld-ref -type f | wc -l)
+SZ=$(du -sm /home/dank/corpora/kld-ref | cut -f1)
+echo "KLD OK files=$N size_mib=$SZ"
+[ "$N" -ge 5 ] && [ "$SZ" -ge 1000 ] || { echo "kld-ref looks thin; calib NOT started"; exit 1; }
+grep -q '"rows": 50235' /home/dank/corpora/kld-ref/kld.json || {
+    echo "kld.json rows != 50235; calib NOT started"; exit 1; }
+
+# Phase 2: calibration serve (1.2.0) + corpus push.
+nohup bash "$S/run-swift15-bf16.sh" calib > "$CLOG" 2>&1 &
+CP=$!
+for _ in $(seq 1 160); do
+    sleep 15
+    curl -sf localhost:7770/health >/dev/null 2>&1 && break
+done
+if ! curl -sf localhost:7770/health >/dev/null 2>&1; then
+    echo "CALIB BOOT FAILED; see /home/dank/logs/swift15_bf16.log"; kill "$CP" 2>/dev/null; exit 1
+fi
+echo "CALIB UP, pushing corpus"
+python3 "$S/calib-push.py" --port 7770 --parallel 16 --container swift15ref --max-rounds 6
+PUSH=$?
+kill "$CP" 2>/dev/null
+sleep 10
+echo "CALIB_CHAIN_DONE push=$PUSH grams=$(find /home/dank/corpora/calib -name 'gram.r*.bin' 2>/dev/null | wc -l)"

scripts/make-calib-corpus.py

@@ -0,0 +1,317 @@
+#!/usr/bin/env python3
+"""Build the two Swift1.5 campaign corpora (calibration + KLD).
+
+calib.jsonl — 10M tokens of agent-shaped RAW text (45% code, 30% prose,
+25% tool-call JSON), one {"prompt": text} per line, pushed to
+/v1/completions with max_tokens=1 during the calibration run (the Hessian
+tap is of the prompt tokens; docs/MOE-W4.md step 2). Code and prose mix
+the repo checkout with HF dataset parquets (Frank's call 2026-10-06:
+local material is only ~1.6M unique tokens; MOE-W4 wants 10M):
+nampdn-ai/tiny-codes (code) and Salesforce/wikitext wikitext-103-raw
+(prose). Tool calls are synthesized from commands harvested from the
+repo's own scripts plus a fleet-ops set, with argument-shaped variants.
+
+kld.jsonl — 1.8M tokens, one {"prompt", "score_from", "source"} per
+line; each prompt is a multi-turn conversation rendered through the
+Froggeric v22.5 template with a >= --kld-min-prompt (8192) token target,
+and the last 256 tokens (the tail of the assistant answer) are the
+scored span: score_from = n - 256. At 8k-token prompts the 1.8M corpus
+is ~220 prompts = ~56k scored positions ~= 25 GB of record, matching
+the published Flash-Next KLD scale (83k positions, MOE-W4.md). The KLD
+reference run and every candidate run consume the SAME file (TOOLS.md
+--kld-record / --kld-ref). The KLD corpus is LOCAL material only, so the
+file-level disjointness rule (fnv1a64(path) % 5 == 0 -> KLD pool) is
+untouched by the HF additions.
+
+Deps: tokenizers, jinja2, pyarrow (venv /home/dank/venvs/radcorpus).
+Usage: make-calib-corpus.py --repo ROOT --tokenizer-json PATH
+    --template PATH --out-dir DIR [--hf-code-parquet F,F]
+    [--hf-prose-parquet F,F] [--calib-tokens 10000000]
+    [--kld-tokens 1800000]
+"""
+import argparse
+import json
+import os
+import random
+import re
+
+from jinja2 import Environment, FileSystemLoader
+from tokenizers import Tokenizer
+
+CODE_EXT = (".sh", ".py", ".jinja", ".recipe", ".env", ".example",
+            ".yaml", ".yml", ".bats", ".service", ".container", ".toml")
+JSONL_EXTS = (".jsonl", ".json")
+DOC_DIR = "serverAppConfigs-docs"
+
+FLEET_CMDS = [
+    "systemctl status frank-archon --no-pager",
+    "journalctl -u frank-archon -n 100 --no-pager",
+    "podman ps --format '{{.Names}} {{.Status}}'",
+    "podman logs --tail 50 frank-archon",
+    "curl -s http://192.168.0.235:7770/health",
+    "curl -s http://192.168.0.235:7770/metrics | grep radiance_",
+    "df -h /home/dank | tail -1",
+    "free -g",
+    "sudo systemctl restart frank-archon",
+    "cd /home/dank/serverAppConfigs && git pull --ff-only",
+    "./scripts/deploy.sh dankserver --service frank-archon",
+    "./tests/run.sh 2>&1 | tail -5",
+    "jq . /home/dank/models/rad/index.json | head -40",
+    "python3 -c \"import json; print(json.load(open('config.json'))['num_hidden_layers'])\"",
+    "ip neigh show 192.168.0.235",
+    "amdgpu_top --device-info 2>/dev/null | head -20",
+    "grep -E 'MemAvailable' /proc/meminfo",
+    "sha256sum model-00001-of-00131.safetensors",
+    "git log --oneline -10",
+    "awk '{s+=$1} END {print s}' shard_sizes.txt",
+]
+TOOL_NAMES = ["bash", "read", "grep", "web_search", "edit", "write"]
+WORKDIRS = ["/home/dank", "/home/dank/serverAppConfigs", "/home/dank/models",
+            "/etc/systemd/system", "/var/log"]
+DESCS = ["check service state", "tail the engine ledger", "list containers",
+          "query health", "read metrics", "check disk", "check memory",
+          "restart the endpoint", "sync the checkout", "run deployer",
+          "run the test seams", "inspect the index", "probe the peer"]
+
+
+def fnv(s: str) -> int:
+    h = 0xcbf29ce484222325
+    for b in s.encode():
+        h = ((h ^ b) * 0x100000001b3) & 0xFFFFFFFFFFFFFFFF
+    return h
+
+
+def harvest_cmds(repo: str, rng: random.Random) -> list[str]:
+    cmds = list(FLEET_CMDS)
+    pat = re.compile(r"^\s*(?:sudo\s+)?([a-z][\w./-]*(?:\s+\S+){1,6})\s*$")
+    for root, dirs, files in os.walk(repo):
+        dirs[:] = [d for d in dirs if not d.startswith(".")]
+        for f in files:
+            if not f.endswith(".sh"):
+                continue
+            try:
+                for line in open(os.path.join(root, f), encoding="utf-8",
+                                 errors="replace"):
+                    m = pat.match(line.rstrip())
+                    if m and len(m.group(1)) > 12:
+                        cmds.append("ssh dank@192.168.0.235 '"
+                                    + m.group(1)[:90] + "'")
+            except OSError:
+                pass
+    rng.shuffle(cmds)
+    return cmds[:4000]
+
+
+def tool_call(rng: random.Random, cmds: list[str]) -> str:
+    """One agent turn: 2-4 tool calls with argument-shaped JSON."""
+    parts = []
+    for _ in range(rng.randint(2, 4)):
+        args: dict = {"command": rng.choice(cmds)}
+        if rng.random() < 0.4:
+            args["cwd"] = rng.choice(WORKDIRS)
+        if rng.random() < 0.3:
+            args["timeout"] = rng.choice([10, 30, 60, 300, 600])
+        if rng.random() < 0.5:
+            args["description"] = rng.choice(DESCS)
+        parts.append('<tool_call>{"name": "%s", "arguments": %s}<|im_end|>'
+                     % (rng.choice(TOOL_NAMES),
+                        json.dumps(args, ensure_ascii=False)))
+    return "\n".join(parts)
+
+
+def load_parquet_texts(path: str, kind: str, rng: random.Random,
+                       cap: int) -> list[str]:
+    import pyarrow.parquet as pq
+    d = pq.read_table(path).to_pydict()
+    n = len(next(iter(d.values())))
+    idx = range(n) if n <= cap else rng.sample(range(n), cap)
+    out = []
+    for i in idx:
+        if kind == "code":
+            if "content" in d:
+                frag = d["content"][i]
+            else:
+                frag = ("// %s\n### Instruction:\n%s\n### Response:\n%s"
+                        % (d.get("file_name", [""])[i], d["prompt"][i],
+                           d["code"][i] or d["response"][i]))
+        else:
+            frag = d["text"][i]
+        if frag and frag.strip():
+            out.append(frag[:8000])
+    rng.shuffle(out)
+    return out[:cap]
+
+
+def main() -> None:
+    ap = argparse.ArgumentParser(description=__doc__)
+    ap.add_argument("--repo", required=True)
+    ap.add_argument("--tokenizer-json", required=True)
+    ap.add_argument("--template", required=True)
+    ap.add_argument("--out-dir", required=True)
+    ap.add_argument("--calib-tokens", type=int, default=10_000_000)
+    ap.add_argument("--kld-tokens", type=int, default=1_800_000)
+    ap.add_argument("--chunk-tokens", type=int, default=8192)
+    ap.add_argument("--score-tail", type=int, default=256)
+    ap.add_argument("--kld-min-prompt", type=int, default=8192)
+    ap.add_argument("--hf-code-parquet", default="")
+    ap.add_argument("--hf-prose-parquet", default="")
+    ap.add_argument("--seed", type=int, default=20261006)
+    a = ap.parse_args()
+
+    rng = random.Random(a.seed)
+    tokenizer = Tokenizer.from_file(a.tokenizer_json)
+    env = Environment(loader=FileSystemLoader(os.path.dirname(a.template)),
+                      trim_blocks=True, lstrip_blocks=True)
+    env.filters["tojson"] = lambda v: json.dumps(v, ensure_ascii=False)
+    env.filters["raise_exception"] = lambda m: (_ for _ in ()).throw(
+        ValueError(m))
+    tname = os.path.basename(a.template)
+
+    code, prose, jsonl = [], [], []
+    for root, dirs, files in os.walk(a.repo):
+        dirs[:] = [d for d in dirs if not d.startswith(".")]
+        for f in sorted(files):
+            p = os.path.relpath(os.path.join(root, f), a.repo)
+            if DOC_DIR in p and f.endswith(".md"):
+                prose.append(p)
+            elif p.startswith(DOC_DIR):
+                pass
+            elif f.endswith(CODE_EXT):
+                code.append(p)
+            elif f.endswith(JSONL_EXTS) and f != "package-lock.json":
+                jsonl.append(p)
+    # file-level split: bucket 0 -> KLD pool, 1..4 -> calibration pool
+    pools: dict[str, tuple[list, list]] = {}
+    for cls, lst in (("code", code), ("prose", prose), ("tools", jsonl)):
+        pools[cls] = ([p for p in lst if fnv(p) % 5 == 0],
+                      [p for p in lst if fnv(p) % 5 != 0])
+
+    def text_of(p: str) -> str:
+        path = os.path.join(a.repo, p)
+        raw = open(path, encoding="utf-8", errors="replace").read()
+        if p.endswith(JSONL_EXTS):
+            lines = [json.loads(l)["content"] for l in raw.splitlines()
+                     if l.strip() and "content" in l]
+            raw = "\n".join(lines)
+        toks = tokenizer.encode(raw, add_special_tokens=False).ids
+        return tokenizer.decode(toks[:2400], skip_special_tokens=True)
+
+    cmds = harvest_cmds(a.repo, rng)
+    # fragment pools per class, corpus-split first
+    frags: dict[str, dict[str, list[str]]] = {}
+    for cls in pools:
+        kld_files, cal_files = pools[cls]
+        fr = {}
+        src = {"kld": kld_files, "cal": cal_files}
+        if cls == "tools":
+            fr["kld"] = [tool_call(rng, cmds) for _ in range(600)]
+            fr["cal"] = [tool_call(rng, cmds) for _ in range(40000)]
+        else:
+            fr["kld"] = [text_of(p) for p in src["kld"]]
+            fr["cal"] = [text_of(p) for p in src["cal"]]
+        frags[cls] = fr
+    # per-class fragment caps: prose rows are short (~66 tok) so need many;
+    # codeparrot files are long (~2.6k tok) so a small cap suffices
+    hfcap = {"code": 40000, "prose": 60000, "tools": 0}
+    for cls, spec in (("code", a.hf_code_parquet),
+                      ("prose", a.hf_prose_parquet)):
+        for path in [p for p in spec.split(",") if p]:
+            frags[cls]["cal"].extend(
+                load_parquet_texts(path, cls, rng, cap=hfcap[cls]))
+    for cls in frags:
+        rng.shuffle(frags[cls]["cal"])
+
+    def toks(s: str) -> int:
+        return len(tokenizer.encode(s, add_special_tokens=False).ids)
+
+    def emit_calib() -> tuple[int, list[dict]]:
+        targets = {"code": .45, "prose": .30, "tools": .25}
+        rows: list[dict] = []
+        for cls, frac in targets.items():
+            want = int(a.calib_tokens * frac)
+            pool = frags[cls]["cal"]
+            if not pool:
+                continue
+            got, i, buf, nbuf = 0, 0, [], 0
+            while got < want:
+                frag = pool[i % len(pool)]
+                i += 1
+                n = toks(frag)
+                if nbuf + n > a.chunk_tokens and buf:
+                    rows.append({"prompt": "\n".join(buf), "cls": cls})
+                    got += nbuf
+                    buf, nbuf = [], 0
+                    if got >= want:
+                        break
+                buf.append(frag)
+                nbuf += n
+                if i > len(pool) * 40:
+                    break  # pool exhausted with repeats; stop
+            if buf and got < want:
+                rows.append({"prompt": "\n".join(buf), "cls": cls})
+                got += nbuf
+            print(f"calib {cls}: {got} tokens, {i} fragments")
+        rng.shuffle(rows)
+        return len(rows), [{k: v for k, v in r.items() if k == "prompt"}
+                           for r in rows]
+
+    def emit_kld() -> tuple[int, list[dict]]:
+        rows, total = [], 0
+        classes = ["code", "prose", "tools"]
+        i = {c: 0 for c in classes}
+        guard = 0
+        while total < a.kld_tokens and guard < 5000:
+            guard += 1
+            msgs, srcs = [], []
+            for t in range(rng.choice([2, 3, 4])):
+                cls = classes[(len(rows) + t) % 3]
+                pool = frags[cls]["kld"]
+                if not pool:
+                    continue
+                frag = pool[i[cls] % len(pool)]
+                i[cls] += 2
+                msgs.append({"role": "user",
+                             "content": "Summarize and explain this "
+                                        f"engineering material:\n{frag}"})
+                msgs.append({"role": "assistant",
+                             "content": frag[:4000]})
+                srcs.append(cls)
+            rendered = env.get_template(tname).render(
+                messages=msgs, add_generation_prompt=False)
+            n = toks(rendered)
+            if n < a.kld_min_prompt:
+                continue
+            rows.append({"prompt": rendered,
+                         "score_from": n - a.score_tail,
+                         "source": "+".join(sorted(set(srcs)))})
+            total += n
+        return len(rows), rows
+
+    os.makedirs(a.out_dir, exist_ok=True)
+    nc, rows = emit_calib()
+    with open(os.path.join(a.out_dir, "calib.jsonl"), "w") as f:
+        for r in rows:
+            f.write(json.dumps(r) + "\n")
+    nk, krows = emit_kld()
+    with open(os.path.join(a.out_dir, "kld.jsonl"), "w") as f:
+        for r in krows:
+            f.write(json.dumps(r) + "\n")
+    scored = sum(len(tokenizer.encode(r["prompt"], add_special_tokens=False).ids)
+                 - r["score_from"] for r in krows)
+    manifest = {
+        "seed": a.seed, "template": tname,
+        "tokenizer": os.path.basename(a.tokenizer_json),
+        "calib_prompts": nc, "kld_prompts": nk,
+        "kld_scored_positions": scored,
+        "kld_score_tail": a.score_tail,
+        "disjoint_file_pools": "local KLD material only; HF code feeds calib",
+        "calib_mix": {"code": .45, "prose": .30, "tools": .25},
+        "hf_code": a.hf_code_parquet, "hf_prose": a.hf_prose_parquet,
+    }
+    with open(os.path.join(a.out_dir, "manifest.json"), "w") as f:
+        json.dump(manifest, f, indent=1)
+    print(json.dumps(manifest, indent=1))
+
+
+if __name__ == "__main__":
+    main()

scripts/patches/glm53-compile-01-model-decorator.patch

@@ -2,7 +2,7 @@
 #
 # STATUS: WIP — first of three patches in the "compile the GLM trunk" changelist. The
 # set does NOT yet boot the engine (see 03 for the next blocker), so it is NOT part of
-# the deployed frank-primary shape. Nothing in scripts/ mounts these files.
+# the deployed frank-archon shape. Nothing in scripts/ mounts these files.
 #
 # WHY THIS IS THE RIGHT LEVER (measured 2026-09-30, not inferred):
 #

scripts/patches/gpu_worker-kv-cap.patch

@@ -1,6 +1,6 @@
 # gpu_worker-kv-cap.patch — fork-local fix for the expert-offload KV cap.
 #
-# STATUS: NOT part of the deployed frank-primary shape. It exists because the
+# STATUS: NOT part of the deployed frank-archon shape. It exists because the
 # fork's plan under-models this model's KV, and it is the enabler for a future
 # MTP attempt (the production GLM shape runs without MTP and boots fine on the
 # plan's own reserve).

scripts/probe-frank-archon-kv.py

@@ -0,0 +1,201 @@
+#!/usr/bin/env python3
+"""probe-frank-archon-kv.py — verify the seqs x max-model-len KV contract on a
+frank-archon (radiance) service. Run it ON dankserver: it talks to
+127.0.0.1:7770 and builds its prompts from the repo checkout there.
+No scratch container, no mask: the service under test is the service.
+
+    ssh dankserver 'python3 /home/dank/serverAppConfigs/scripts/probe-frank-archon-kv.py'
+
+Four probes, in increasing cost:
+  A  decode at depth — one ~51k-token chat completion, 512 tokens, greedy.
+     Reports the engine's own `timings` (prefill, decode, draft acceptance).
+     The bench law applies: >=128 generated tokens, greedy, real text.
+  B  the capacity contract — as many CONCURRENT chats of ~197k prompt tokens as
+     the deployed `FRANK_ARCHON_MAX_SEQS` (read from the repo env file on this
+     host), each carrying a unique marker at its head. All must answer their own
+     marker. This is what the endpoint owes: N full-height conversations
+     resident at once, exact retrieval in every one of them.
+  C  prefix-cache restore — probe A's cold prompt again, so the disk tier has
+     to give the blocks back (cache_n > 0, TTFT collapses).
+  D  concurrency decode — `seqs` CONCURRENT 512-token generations at ~25 % of
+     the window. This is the cost a slot count imposes on DECODE, which no
+     prefill number shows: the fused-step schedule is unfair, so every stream is
+     printed plus the aggregate. Measured 2026-10-13 at 3 x 200,000 fp8:
+     single-stream 99.0 t/s (43.5k) and 93.3 (197k) — decode is nearly
+     window-free — against 3-stream 113.9/43.3/10.9 t/s = 18.4 t/s aggregate.
+     Concurrency, not the slab, is what decode pays for slots. The 2026-10-13
+     shape hunt missed this for a whole day because leg B generates 24 tokens.
+PROBE LAW (learned the hard way, twice): radiance routes the thinking block to
+`reasoning_content`, so a chat request whose budget is spent inside
+`<think>` returns EMPTY `content` with `finish_reason: stop`. A probe that
+reads `content` alone scores 0/2 on a healthy server. Every request here sets
+chat_template_kwargs.enable_thinking=false and reads both fields.
+
+A/B method for a shape change (no scratch container): write a variant env file
+on the host, point a transient systemd drop-in at it
+(`Environment=FRANK_ARCHON_ENV_FILE=...` — drop-ins are read AFTER the unit's
+own Environment= lines, so they win), restart, probe, delete the drop-in,
+daemon-reload, restart. `systemctl mask` is not available: the unit file in
+/etc/systemd/system is a relink symlink into the checkout.
+"""
+import json
+import glob
+import time
+import urllib.request
+import concurrent.futures
+
+BASE = "http://127.0.0.1:7770"
+MODEL = "frank-archon"
+REPO = "/home/dank/serverAppConfigs"
+GLOBS = [f"{REPO}/scripts/*.sh", f"{REPO}/serverAppConfigs-docs/**/*.md"]
+
+
+def post(payload, timeout=1800):
+    req = urllib.request.Request(
+        BASE + "/v1/chat/completions",
+        data=json.dumps(payload).encode(),
+        headers={"Content-Type": "application/json"},
+    )
+    t0 = time.time()
+    with urllib.request.urlopen(req, timeout=timeout) as r:
+        body = json.loads(r.read().decode())
+        hdr = dict(r.headers.items())
+    return body, time.time() - t0, hdr
+
+
+def get(path, timeout=60):
+    with urllib.request.urlopen(BASE + path, timeout=timeout) as r:
+        return json.loads(r.read().decode())
+
+
+def corpus(min_chars):
+    files = []
+    for g in GLOBS:
+        files.extend(sorted(glob.glob(g, recursive=True)))
+    out, total = [], 0
+    for f in files:
+        try:
+            t = open(f, encoding="utf-8", errors="replace").read()
+        except OSError:
+            continue
+        out.append(t)
+        total += len(t)
+        if total > min_chars:
+            break
+    return "".join(text for text in out)
+
+
+def prompt(text, chars, salt, fact):
+    """Real repo text, salted so the prefix cache cannot answer, marker planted
+    near the head, question at the tail."""
+    head = f"\n[SALT {salt}] confidential marker: {fact}\n"
+    body = text + text
+    p = (head + body * max(1, chars // len(body)))[:chars]
+    return p + "\n\nQuestion: what is the confidential marker in the " \
+        "SALT block near the top of this document? Answer with the marker " \
+        "alone, no other words.\n"
+
+
+def chat(text, chars, salt, fact, max_tokens):
+    return {"model": MODEL,
+            "messages": [{"role": "user",
+                          "content": prompt(text, chars, salt, fact)}],
+            "max_tokens": max_tokens, "temperature": 0.0,
+            "chat_template_kwargs": {"enable_thinking": False}}
+
+
+def show(tag, j, wall, expect=None):
+    tim, u = j.get("timings") or {}, j.get("usage", {})
+    ch = (j.get("choices") or [{}])[0]
+    msg = ch.get("message") or {}
+    txt = (msg.get("content") or msg.get("reasoning_content") or "").strip()
+    acc = (tim["draft_n_accepted"] / tim["draft_n"]) if tim.get("draft_n") else None
+    line = (f"[{tag}] prompt={u.get('prompt_tokens')} gen={u.get('completion_tokens')} "
+            f"wall={wall:.1f}s prefill={tim.get('prompt_per_second', 0):.0f} t/s "
+            f"decode={tim.get('predicted_per_second', 0):.1f} t/s "
+            f"draft={tim.get('draft_n')}/{tim.get('draft_n_accepted')} "
+            f"accept={acc if acc is None else round(acc, 4)} "
+            f"cache_n={tim.get('cache_n')} finish={ch.get('finish_reason')}")
+    if expect:
+        hit = expect.split("-")[0] in txt.lower()
+        line += f" expected={expect} answered={txt[:80]!r} HIT={hit}"
+    print(line)
+
+
+def deployed_shape():
+    """The contract is the deployed env, not a constant: slot count and window
+    come from the checkout on this host, so the probe cannot drift from the
+    service it is testing (the 2026-10-13 shape is 4 x 200,000; before that
+    2 x 200,000, and the fp8 era 3 x 200,000)."""
+    shape = {}
+    with open(f"{REPO}/scripts/frank-archon.env") as fh:
+        for line in fh:
+            line = line.strip()
+            if line.startswith("FRANK_ARCHON_") and "=" in line:
+                key, _, val = line.partition("=")
+                shape[key] = val.strip().strip('"')
+    return (int(shape["FRANK_ARCHON_MAX_SEQS"]),
+            int(shape["FRANK_ARCHON_MAX_MODEL_LEN"]),
+            shape["FRANK_ARCHON_KV_DTYPE"])
+
+
+def main():
+    seqs, maxlen, dtype = deployed_shape()
+    print(f"shape: {seqs} x {maxlen:,} tokens, kv {dtype}")
+    print("health:", json.dumps(get("/health")))
+    print("models:", [m.get("id") for m in get("/v1/models").get("data", [])])
+    deep = corpus(160_000)
+    wide = corpus(1_100_000)
+
+    # 3.28 chars/token is the measured ratio of this corpus through the
+    # froggeric template (646,000 chars -> 196,919 tokens at the 2026-10-11
+    # deploy); 98.5 % of the window leaves the response room under the ceiling.
+    chars = int(0.985 * maxlen * 3.28)
+    # Each marker's FIRST hyphen-separated word is unique, because show()
+    # scores the hit on that word — a shared prefix would score every slot HIT
+    # on any answer that says the word.
+    words = ["cobalt", "quartz", "basalt", "ember", "willow", "cobweb", "flint"]
+    facts = {f"B{i+1}": f"{words[i % len(words)]}-flag-{(i + 1) * 137}"
+             for i in range(seqs)}
+    bodies = {s: chat(wide, chars, s, f, 24) for s, f in facts.items()}
+    print(f"[B] {len(bodies['B1']['messages'][0]['content']):,} chars per "
+          f"request, x{seqs} concurrent")
+
+    # A + C first (cheap), B last (the expensive set).
+    for tag, salt in (("A-cold", "A1-9137"), ):
+        j, wall, _ = post(chat(deep, 140_000, salt, "zephyr-lantern-7", 512))
+        show(tag, j, wall, "zephyr-lantern-7")
+    t0 = time.time()
+    with concurrent.futures.ThreadPoolExecutor(max_workers=seqs) as ex:
+        futs = {s: ex.submit(post, b) for s, b in bodies.items()}
+        for s, fut in futs.items():
+            try:
+                j, wall, _ = fut.result()
+                show(f"B-{s}", j, wall, facts[s])
+            except Exception as e:  # a preemption/timeout lands here
+                print(f"[B-{s}] FAILED after {time.time() - t0:.1f}s: {e!r}")
+    print(f"[B] total {time.time() - t0:.1f}s")
+    # D — concurrency decode: seqs streams, 512 tokens each, ~25 % depth.
+    dchars = int(0.25 * maxlen * 3.28)
+    dbodies = [chat(deep, dchars, f"D{i + 1}-9137", f"flint-marker-{i}", 512)
+               for i in range(seqs)]
+    print(f"[D] {seqs} concurrent streams x 512 tokens, "
+          f"{dchars:,} chars each")
+    t0 = time.time()
+    with concurrent.futures.ThreadPoolExecutor(max_workers=seqs) as ex:
+        futs = [ex.submit(post, b) for b in dbodies]
+        for i, fut in enumerate(futs, 1):
+            try:
+                j, wall, _ = fut.result()
+                show(f"D-s{i}", j, wall)
+            except Exception as e:  # a preemption/timeout lands here
+                print(f"[D-s{i}] FAILED after {time.time() - t0:.1f}s: {e!r}")
+    tot = time.time() - t0
+    print(f"[D] {seqs} x 512 tokens in {tot:.1f}s = "
+          f"{seqs * 512 / tot:.1f} t/s aggregate decode")
+    j, wall, _ = post(chat(deep, 140_000, "A1-9137", "zephyr-lantern-7", 512))
+    show("C-prefix-hit", j, wall, "zephyr-lantern-7")
+
+
+if __name__ == "__main__":
+    main()

scripts/qwen38-froggeric-v22.5.jinja

@@ -0,0 +1,460 @@
+{%- set template_version = "qwen3.8-froggeric-v22.5" %}
+{%- set _tool_format = tool_call_format if tool_call_format is defined else 'xml' %}
+{%- set image_count = namespace(value=0) %}
+{%- set video_count = namespace(value=0) %}
+{%- set add_vision_id = add_vision_id if add_vision_id is defined else false %}
+{%- set enable_thinking = enable_thinking if enable_thinking is defined else true %}
+{%- set auto_disable_thinking_with_tools = auto_disable_thinking_with_tools if auto_disable_thinking_with_tools is defined else false %}
+{%- if preserve_reasoning is defined and preserve_reasoning is not none %}
+    {%- set _preserve_thinking = preserve_reasoning %}
+{%- elif preserve_thinking is defined and preserve_thinking is not none %}
+    {%- set _preserve_thinking = preserve_thinking %}
+{%- else %}
+    {%- set _preserve_thinking = true %}
+{%- endif %}
+{%- set max_tool_arg_chars = max_tool_arg_chars if max_tool_arg_chars is defined else 0 %}
+{%- set max_tool_response_chars = max_tool_response_chars if max_tool_response_chars is defined else 0 %}
+{%- set _default_reasoning_effort = 'medium' %}
+{%- set _has_tools = (tools is defined and tools and tools is iterable and tools is not mapping) %}
+{%- set _effort_raw = (reasoning_effort | string | lower) if reasoning_effort is defined and reasoning_effort is not none else _default_reasoning_effort %}
+{%- set _initial_thinking = enable_thinking %}
+{%- if _effort_raw in ('none', 'off') %}
+    {%- set _initial_thinking = false %}
+    {%- set _initial_effort = 'medium' %}
+{%- elif _effort_raw in ('minimal', 'low') %}
+    {%- set _initial_effort = 'low' %}
+{%- elif _effort_raw in ('high', 'xhigh', 'max', 'ultracode', 'extreme') %}
+    {%- set _initial_effort = 'xhigh' %}
+{%- else %}
+    {%- set _initial_effort = 'medium' %}
+{%- endif %}
+{%- set ns_state = namespace(thinking=_initial_thinking, effort=_initial_effort) %}
+{%- if auto_disable_thinking_with_tools and _has_tools %}
+    {%- set ns_state.thinking = false %}
+{%- endif %}
+{%- for msg in messages %}
+    {%- if msg.role == 'system' or msg.role == 'developer' or msg.role == 'user' %}
+        {%- if msg.content is string %}
+            {%- if '<|think_off|>' in msg.content %}
+                {%- set ns_state.thinking = false %}
+            {%- elif '<|think_on|>' in msg.content %}
+                {%- set ns_state.thinking = true %}
+            {%- elif '<|think_xhigh|>' in msg.content or '<|think_high|>' in msg.content or '<|think_ultracode|>' in msg.content or '<|think_extreme|>' in msg.content or '<|think_max|>' in msg.content %}
+                {%- set ns_state.thinking = true %}
+                {%- set ns_state.effort = 'xhigh' %}
+            {%- elif '<|think_low|>' in msg.content or '<|think_minimal|>' in msg.content %}
+                {%- set ns_state.thinking = true %}
+                {%- set ns_state.effort = 'low' %}
+            {%- elif '<|think_medium|>' in msg.content %}
+                {%- set ns_state.thinking = true %}
+                {%- set ns_state.effort = 'medium' %}
+            {%- endif %}
+        {%- elif msg.content is iterable and msg.content is not mapping %}
+            {%- for item in msg.content %}
+                {%- if item is string %}
+                    {%- set _item_text = item %}
+                {%- elif item is mapping and 'text' in item and item.text is string %}
+                    {%- set _item_text = item.text %}
+                {%- else %}
+                    {%- set _item_text = '' %}
+                {%- endif %}
+                {%- if _item_text %}
+                    {%- if '<|think_off|>' in _item_text %}
+                        {%- set ns_state.thinking = false %}
+                    {%- elif '<|think_on|>' in _item_text %}
+                        {%- set ns_state.thinking = true %}
+                    {%- elif '<|think_xhigh|>' in _item_text or '<|think_high|>' in _item_text or '<|think_ultracode|>' in _item_text or '<|think_extreme|>' in _item_text or '<|think_max|>' in _item_text %}
+                        {%- set ns_state.thinking = true %}
+                        {%- set ns_state.effort = 'xhigh' %}
+                    {%- elif '<|think_low|>' in _item_text or '<|think_minimal|>' in _item_text %}
+                        {%- set ns_state.thinking = true %}
+                        {%- set ns_state.effort = 'low' %}
+                    {%- elif '<|think_medium|>' in _item_text %}
+                        {%- set ns_state.thinking = true %}
+                        {%- set ns_state.effort = 'medium' %}
+                    {%- endif %}
+                {%- endif %}
+            {%- endfor %}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- set reasoning_instructions = '' %}
+{%- if ns_state.thinking %}
+    {%- if ns_state.effort == 'xhigh' %}
+        {%- set reasoning_instructions = 'Reasoning effort is set to xhigh. Please think carefully through the task, validate key assumptions, consider plausible alternatives, and prioritize correctness, consistency, and clarity in the final answer.' %}
+    {%- elif ns_state.effort == 'low' %}
+        {%- set reasoning_instructions = 'Reasoning effort is set to low. Keep your thinking brief and focused, moving directly to the conclusion without unnecessary elaboration.' %}
+    {%- endif %}
+{%- endif %}
+{%- macro render_content(content, do_vision_count, is_system_content=false) %}
+    {%- if content is string %}
+        {{- content }}
+    {%- elif content is iterable and content is not mapping %}
+        {%- for item in content %}
+            {%- if item is mapping %}
+                {%- if item.type == 'image' or 'image' in item or 'image_url' in item %}
+                    {%- if is_system_content %}
+                        {{- raise_exception('System message cannot contain images.') }}
+                    {%- endif %}
+                    {%- if do_vision_count %}
+                        {%- set image_count.value = image_count.value + 1 %}
+                    {%- endif %}
+                    {%- if add_vision_id %}
+                        {{- 'Picture ' ~ image_count.value ~ ': ' }}
+                    {%- endif %}
+                    {{- '<|vision_start|><|image_pad|><|vision_end|>' }}
+                {%- elif item.type == 'video' or 'video' in item or 'video_url' in item %}
+                    {%- if is_system_content %}
+                        {{- raise_exception('System message cannot contain videos.') }}
+                    {%- endif %}
+                    {%- if do_vision_count %}
+                        {%- set video_count.value = video_count.value + 1 %}
+                    {%- endif %}
+                    {%- if add_vision_id %}
+                        {{- 'Video ' ~ video_count.value ~ ': ' }}
+                    {%- endif %}
+                    {{- '<|vision_start|><|video_pad|><|vision_end|>' }}
+                {%- elif 'text' in item %}
+                    {{- item.text }}
+                {%- else %}
+                    {{- raise_exception('Unexpected item type in content.') }}
+                {%- endif %}
+            {%- else %}
+                {{- item | string }}
+            {%- endif %}
+        {%- endfor %}
+    {%- elif content is none or content is undefined %}
+        {{- '' }}
+    {%- else %}
+        {{- raise_exception('Unexpected content type.') }}
+    {%- endif %}
+{%- endmacro %}
+{%- if not messages %}
+    {{- raise_exception('No messages provided.') }}
+{%- endif %}
+{%- set head = namespace(count=0, seen_non_system=false) %}
+{%- for message in messages %}
+    {%- set _is_sys = (message.role == 'system' or message.role == 'developer') %}
+    {%- if _is_sys and not head.seen_non_system %}
+        {%- set head.count = head.count + 1 %}
+    {%- else %}
+        {%- set head.seen_non_system = true %}
+    {%- endif %}
+{%- endfor %}
+{%- set sys_state = namespace(content='') %}
+{%- for message in messages[:head.count] %}
+    {%- set _part = render_content(message.content, false, true) | trim %}
+    {%- if '<|think_off|>' in _part %}{%- set _part = _part.split('<|think_off|>') | join('') | trim %}{%- endif %}
+    {%- if '<|think_on|>' in _part %}{%- set _part = _part.split('<|think_on|>') | join('') | trim %}{%- endif %}
+    {%- if '<|think_xhigh|>' in _part %}{%- set _part = _part.split('<|think_xhigh|>') | join('') | trim %}{%- endif %}
+    {%- if '<|think_high|>' in _part %}{%- set _part = _part.split('<|think_high|>') | join('') | trim %}{%- endif %}
+    {%- if '<|think_ultracode|>' in _part %}{%- set _part = _part.split('<|think_ultracode|>') | join('') | trim %}{%- endif %}
+    {%- if '<|think_extreme|>' in _part %}{%- set _part = _part.split('<|think_extreme|>') | join('') | trim %}{%- endif %}
+    {%- if '<|think_max|>' in _part %}{%- set _part = _part.split('<|think_max|>') | join('') | trim %}{%- endif %}
+    {%- if '<|think_medium|>' in _part %}{%- set _part = _part.split('<|think_medium|>') | join('') | trim %}{%- endif %}
+    {%- if '<|think_low|>' in _part %}{%- set _part = _part.split('<|think_low|>') | join('') | trim %}{%- endif %}
+    {%- if '<|think_minimal|>' in _part %}{%- set _part = _part.split('<|think_minimal|>') | join('') | trim %}{%- endif %}
+    {%- if _part %}
+        {%- if sys_state.content %}
+            {%- set sys_state.content = sys_state.content ~ '\n\n' ~ _part %}
+        {%- else %}
+            {%- set sys_state.content = _part %}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- set _sc = sys_state.content %}
+{%- set _msgs = messages[head.count:] %}
+{%- if _has_tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if reasoning_instructions %}
+        {{- reasoning_instructions + '\n\n' }}
+    {%- endif %}
+    {{- '# Tools\n\nYou have access to the following functions:\n\n<tools>' }}
+    {%- for tool in tools %}
+        {{- '\n' }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- '\n</tools>' }}
+    {%- if _tool_format == 'json' %}
+        {{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n' }}
+        {%- if ns_state.thinking %}
+            {{- '<think>\nBrief explanation of tool call\n</think>\n' }}
+        {%- endif %}
+        {{- '<tool_call>\n{"name": "example_function_name", "arguments": {"example_parameter_1": "value_1", "example_parameter_2": "This is the value for the second parameter"}}\n</tool_call>\n\n<IMPORTANT>\nReminder:\n' }}
+        {%- if ns_state.thinking %}
+            {{- '- You can use the <think></think> block to plan your next tool call OR to synthesize data and formulate your final response to the user.\n- ALL explanation and reasoning MUST be placed strictly inside the <think></think> block.\n' }}
+        {%- endif %}
+        {{- '- Function calls MUST follow the specified format: a single JSON object with "name" and "arguments" keys inside <tool_call></tool_call> XML tags.\n' }}
+        {%- if ns_state.thinking %}
+            {{- '- If you choose to call a tool, you MUST output the <tool_call> block IMMEDIATELY after thinking, with NO conversational text before it.\n' }}
+        {%- else %}
+            {{- '- If you choose to call a tool, you MUST output the <tool_call> block IMMEDIATELY, with NO conversational text before it.\n' }}
+        {%- endif %}
+        {{- '- The <tool_call> tag MUST be at the very beginning of a new line, with NO spaces or indentation before it.\n- To call multiple functions, output a separate, completely closed <tool_call></tool_call> block for EACH function. Do NOT nest <tool_call> blocks.\n- If you have all necessary data, provide your final answer directly to the user without any tool call.\n</IMPORTANT>' }}
+    {%- else %}
+        {{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n' }}
+        {%- if ns_state.thinking %}
+            {{- '<think>\nBrief explanation of tool call\n</think>\n' }}
+        {%- endif %}
+        {{- '<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n' }}
+        {%- if ns_state.thinking %}
+            {{- '- You can use the <think></think> block to plan your next tool call OR to synthesize data and formulate your final response to the user.\n- ALL explanation and reasoning MUST be placed strictly inside the <think></think> block.\n' }}
+        {%- endif %}
+        {{- '- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags.\n' }}
+        {%- if ns_state.thinking %}
+            {{- '- If you choose to call a tool, you MUST output the <tool_call> block IMMEDIATELY after thinking, with NO conversational text before it.\n' }}
+        {%- else %}
+            {{- '- If you choose to call a tool, you MUST output the <tool_call> block IMMEDIATELY, with NO conversational text before it.\n' }}
+        {%- endif %}
+        {{- '- The <tool_call> and <function> tags MUST be at the very beginning of a new line, with NO spaces or indentation before them.\n- To call multiple functions, output a separate, completely closed <tool_call></tool_call> block for EACH function. Do NOT nest <tool_call> blocks.\n- If you have all necessary data, provide your final answer directly to the user without any tool call.\n</IMPORTANT>' }}
+    {%- endif %}
+    {%- if _sc %}
+        {{- '\n\n' + _sc }}
+    {%- endif %}
+    {{- '<|im_end|>\n' }}
+{%- else %}
+    {%- if _sc %}
+        {{- '<|im_start|>system\n' + (reasoning_instructions + '\n\n' if reasoning_instructions else '') + _sc + '<|im_end|>\n' }}
+    {%- elif reasoning_instructions %}
+        {{- '<|im_start|>system\n' + reasoning_instructions + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- set _last_idx = _msgs | length - 1 %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=_last_idx) %}
+{%- for message in _msgs[::-1] %}
+    {%- set index = (_msgs | length - 1) - loop.index0 %}
+    {%- if ns.multi_step_tool and message.role == 'user' %}
+        {%- set _rc = render_content(message.content, false) | trim %}
+        {%- if not (_rc.startswith('<tool_response>') and _rc.endswith('</tool_response>')) %}
+            {%- set ns.multi_step_tool = false %}
+            {%- set ns.last_query_index = index %}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if ns.multi_step_tool %}
+    {%- if _last_idx > 50 %}
+        {%- set ns.last_query_index = _last_idx %}
+    {%- else %}
+        {%- set ns.last_query_index = 0 %}
+    {%- endif %}
+{%- endif %}
+{%- set ns2 = namespace(prev_role='', consecutive_failures=0) %}
+{%- for message in _msgs %}
+    {%- set is_system = (message.role == "system" or message.role == "developer") %}
+    {%- set content = render_content(message.content, true, is_system) | trim %}
+    {%- if is_system or message.role == 'user' %}
+        {%- if '<|think_off|>' in content %}{%- set content = content.split('<|think_off|>') | join('') | trim %}{%- endif %}
+        {%- if '<|think_on|>' in content %}{%- set content = content.split('<|think_on|>') | join('') | trim %}{%- endif %}
+        {%- if '<|think_xhigh|>' in content %}{%- set content = content.split('<|think_xhigh|>') | join('') | trim %}{%- endif %}
+        {%- if '<|think_high|>' in content %}{%- set content = content.split('<|think_high|>') | join('') | trim %}{%- endif %}
+        {%- if '<|think_ultracode|>' in content %}{%- set content = content.split('<|think_ultracode|>') | join('') | trim %}{%- endif %}
+        {%- if '<|think_extreme|>' in content %}{%- set content = content.split('<|think_extreme|>') | join('') | trim %}{%- endif %}
+        {%- if '<|think_max|>' in content %}{%- set content = content.split('<|think_max|>') | join('') | trim %}{%- endif %}
+        {%- if '<|think_medium|>' in content %}{%- set content = content.split('<|think_medium|>') | join('') | trim %}{%- endif %}
+        {%- if '<|think_low|>' in content %}{%- set content = content.split('<|think_low|>') | join('') | trim %}{%- endif %}
+        {%- if '<|think_minimal|>' in content %}{%- set content = content.split('<|think_minimal|>') | join('') | trim %}{%- endif %}
+    {%- endif %}
+    {%- if is_system %}
+        {{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
+    {%- elif message.role == 'user' %}
+        {%- set ns2.consecutive_failures = 0 %}
+        {{- '<|im_start|>user\n' + content + '<|im_end|>\n' }}
+    {%- elif message.role == 'assistant' %}
+        {%- set reasoning_content = '' %}
+        {%- set _explicit_reasoning = '' %}
+        {%- if message.reasoning_content is defined and message.reasoning_content is not none %}
+            {%- if message.reasoning_content is string %}
+                {%- set _explicit_reasoning = message.reasoning_content %}
+            {%- else %}
+                {%- set _explicit_reasoning = message.reasoning_content | string %}
+            {%- endif %}
+        {%- elif message.thinking is defined and message.thinking is not none %}
+            {%- if message.thinking is string %}
+                {%- set _explicit_reasoning = message.thinking %}
+            {%- else %}
+                {%- set _explicit_reasoning = message.thinking | string %}
+            {%- endif %}
+        {%- elif message.reasoning is defined and message.reasoning is not none %}
+            {%- if message.reasoning is string %}
+                {%- set _explicit_reasoning = message.reasoning %}
+            {%- else %}
+                {%- set _explicit_reasoning = message.reasoning | string %}
+            {%- endif %}
+        {%- endif %}
+        {%- if _explicit_reasoning %}
+            {%- set _lead_end = '' %}
+            {%- if content.startswith('<think>') and '</think>' in content %}
+                {%- set _lead_end = '</think>' %}
+            {%- elif content.startswith('<thinking>') and '</thinking>' in content %}
+                {%- set _lead_end = '</thinking>' %}
+            {%- elif content.startswith('</think>') %}
+                {%- set _lead_end = '</think>' %}
+            {%- elif content.startswith('</thinking>') %}
+                {%- set _lead_end = '</thinking>' %}
+            {%- endif %}
+            {%- if _lead_end %}
+                {%- set content = content.split(_lead_end)[-1].lstrip('\n') %}
+            {%- endif %}
+            {%- set reasoning_content = _explicit_reasoning %}
+        {%- else %}
+            {%- set _think_end = '' %}
+            {%- if content.startswith('</think>') %}
+                {%- set _think_end = '</think>' %}
+            {%- elif content.startswith('</thinking>') %}
+                {%- set _think_end = '</thinking>' %}
+            {%- elif '\n</think>' in content %}
+                {%- set _think_end = '\n</think>' %}
+            {%- elif '\n</thinking>' in content %}
+                {%- set _think_end = '\n</thinking>' %}
+            {%- elif '\n</ think>' in content %}
+                {%- set _think_end = '\n</ think>' %}
+            {%- elif '\n</think >' in content %}
+                {%- set _think_end = '\n</think >' %}
+            {%- elif content.startswith('<think>') and '</think>' in content %}
+                {%- set _think_end = '</think>' %}
+            {%- elif content.startswith('<thinking>') and '</thinking>' in content %}
+                {%- set _think_end = '</thinking>' %}
+            {%- endif %}
+            {%- if _think_end %}
+                {%- if 'thinking' in _think_end %}
+                    {%- set _think_start = '<thinking>' %}
+                {%- else %}
+                    {%- set _think_start = '<think>' %}
+                {%- endif %}
+                {%- set reasoning_content = content.split(_think_end)[0].rstrip('\n') %}
+                {%- if _think_start in reasoning_content %}
+                    {%- set reasoning_content = reasoning_content.split(_think_start)[-1].lstrip('\n') %}
+                {%- endif %}
+                {%- set content = content.split(_think_end)[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- set reasoning_content = reasoning_content | trim %}
+        {%- if (_preserve_thinking or loop.index0 > ns.last_query_index) %}
+            {{- '<|im_start|>assistant\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
+        {%- else %}
+            {{- '<|im_start|>assistant\n' + content }}
+        {%- endif %}
+        {%- if message.tool_calls is defined and message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if tool_call.function is defined and tool_call.function is not none %}
+                    {%- set tc = tool_call.function %}
+                {%- else %}
+                    {%- set tc = tool_call %}
+                {%- endif %}
+                {%- set tc_name = tc.name if (tc.name is defined and tc.name is not none) else '' %}
+                {%- if _tool_format == 'json' %}
+                    {%- if loop.first %}
+                        {%- if content | trim %}
+                            {{- '\n\n' }}
+                        {%- endif %}
+                    {%- else %}
+                        {{- '\n' }}
+                    {%- endif %}
+                    {%- set _args = '{}' %}
+                    {%- if tc.arguments is defined and tc.arguments is not none %}
+                        {%- if tc.arguments is mapping %}
+                            {%- set _args = tc.arguments | tojson %}
+                        {%- elif tc.arguments is string %}
+                            {%- if tc.arguments %}
+                                {%- set _args = tc.arguments %}
+                            {%- endif %}
+                        {%- else %}
+                            {%- set _args = tc.arguments | tojson %}
+                        {%- endif %}
+                    {%- endif %}
+                    {{- '<tool_call>\n{"name": ' }}{{- tc_name | tojson }}{{- ', "arguments": ' }}{{- _args }}{{- '}\n</tool_call>' }}
+                {%- else %}
+                    {%- if loop.first %}
+                        {%- if content | trim %}
+                            {{- '\n\n<tool_call>\n<function=' + tc_name + '>\n' }}
+                        {%- else %}
+                            {{- '<tool_call>\n<function=' + tc_name + '>\n' }}
+                        {%- endif %}
+                    {%- else %}
+                        {{- '\n<tool_call>\n<function=' + tc_name + '>\n' }}
+                    {%- endif %}
+                    {%- if tc.arguments is defined and tc.arguments is not none %}
+                        {%- if tc.arguments is mapping %}
+                            {%- for args_name, args_value in tc.arguments.items() %}
+                                {{- '<parameter=' + args_name + '>\n' }}
+                                {%- if args_value is string %}
+                                    {%- set _av = args_value %}
+                                {%- else %}
+                                    {%- set _av = args_value | tojson %}
+                                {%- endif %}
+                                {%- if max_tool_arg_chars > 0 and _av | length > max_tool_arg_chars %}
+                                    {{- _av[:max_tool_arg_chars] + '\n[TRUNCATED - original length ' ~ (_av | length | string) ~ ' chars]' }}
+                                {%- else %}
+                                    {{- _av }}
+                                {%- endif %}
+                                {{- '\n</parameter>\n' }}
+                            {%- endfor %}
+                        {%- else %}
+                            {%- if tc.arguments is string %}
+                                {%- set _raw_args = tc.arguments %}
+                            {%- else %}
+                                {%- set _raw_args = tc.arguments | tojson %}
+                            {%- endif %}
+                            {%- if _raw_args %}
+                                {%- if max_tool_arg_chars > 0 and _raw_args | length > max_tool_arg_chars %}
+                                    {{- _raw_args[:max_tool_arg_chars] + '\n[TRUNCATED - original length ' ~ (_raw_args | length | string) ~ ' chars]' }}
+                                {%- else %}
+                                    {{- _raw_args }}
+                                {%- endif %}
+                            {%- endif %}
+                        {%- endif %}
+                    {%- endif %}
+                    {{- '</function>\n</tool_call>' }}
+                {%- endif %}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == 'tool' %}
+        {%- set _content_lower = content | lower %}
+        {%- set _content_head = _content_lower[:120] %}
+        {%- set _is_code_or_grep = ('throw new ' in _content_lower or 'throw error' in _content_lower or 'console.error' in _content_lower or 'logger.error' in _content_lower or 'logging.error' in _content_lower or 'import ' in _content_head or 'def ' in _content_head or 'function ' in _content_head) %}
+        {%- set _exit_code_zero = ('exit code: 0' in _content_head or 'process exited with code 0' in _content_head) %}
+        {%- set _error_field_ok = ('"error": null' in _content_head or '"error":null' in _content_head or '"error": false' in _content_head or '"error":false' in _content_head or '"error": ""' in _content_head or '"error":""' in _content_head) %}
+        {%- set _strong_error = (('"error":' in _content_head and not _error_field_ok) or '"status": "error"' in _content_head or '"status":"error"' in _content_head or 'traceback (most recent call last):' in _content_head or 'command not found' in _content_head or 'invalid syntax' in _content_head or 'fatal:' in _content_head or (('exit code: ' in _content_head or 'process exited with code' in _content_head) and not _exit_code_zero) or _content_head.startswith('exception:') or _content_head.startswith('failed to ')) %}
+        {%- set _weak_error = ('error:' in _content_head or 'err!' in _content_head) %}
+        {%- set _weak_suppressed = ('$ ' in _content_head or 'took ' in _content_head or content | length >= 600) %}
+        {%- if not _is_code_or_grep and (_strong_error or (_weak_error and not _weak_suppressed)) %}
+            {%- set ns2.consecutive_failures = ns2.consecutive_failures + 1 %}
+        {%- else %}
+            {%- set ns2.consecutive_failures = 0 %}
+        {%- endif %}
+        {%- if ns2.prev_role != 'tool' %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {%- set _is_json_payload = (_tool_format == 'json' and content | trim | length > 0 and (content | trim)[:1] in ('{', '[')) %}
+        {%- if not _is_json_payload and max_tool_response_chars > 0 and content | length > max_tool_response_chars %}
+            {%- set content = content[:max_tool_response_chars] + '\n[TRUNCATED - original length ' ~ (content | length | string) ~ ' chars]' %}
+        {%- endif %}
+        {{- '\n<tool_response>\n' + content }}
+        {%- if ns2.consecutive_failures >= 2 %}
+            {{- '\n\n⚠️ SYSTEM WARNING: ' ~ ns2.consecutive_failures ~ ' consecutive tool errors detected. Your previous approach is incorrect. You MUST use a fundamentally different approach or corrected arguments.' }}
+        {%- elif ns2.consecutive_failures == 1 %}
+            {{- '\n\n⚠️ SYSTEM WARNING: The previous tool call returned an error. Diagnose the failure and retry with completely corrected arguments.' }}
+        {%- endif %}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last %}
+            {{- '<|im_end|>\n' }}
+        {%- else %}
+            {%- set _next_role = _msgs[loop.index0 + 1].role %}
+            {%- if _next_role != 'tool' %}
+                {{- '<|im_end|>\n' }}
+            {%- endif %}
+        {%- endif %}
+    {%- else %}
+        {{- '<|im_start|>user\n[' + message.role + ']: ' + content + '<|im_end|>\n' }}
+    {%- endif %}
+    {%- set ns2.prev_role = message.role %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+    {%- if not ns_state.thinking %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- else %}
+        {{- '<think>\n' }}
+    {%- endif %}
+{%- endif %}

scripts/recipes/qwen4exp-swift15-w4dn8-i8-hc8m.recipe

@@ -0,0 +1,105 @@
+# qwen4exp-swift15-w4dn8-i8-hc8m.recipe -- the Swift 1.5 finetune of Qwen3.8-Flash-Next
+# (ukisai/Swift1.5-Qwen3.8-Flash-Next, BF16 source, 335.3 GiB, key set identical to the official
+# base) as a radiance container for frank-archon: EVERY routed expert -- gate_up AND down --
+# through GPTQ into the w4nl64a8h table. The plugin's one-table-one-encoding law
+# ("one table of experts takes one encoding, and only a whole expert kept plain bf16 is served
+# beside it", qwen4exp_fp8 rad_arch_declare) forbids the original split tier (down block-fp8 +
+# gate_up w4): the served kernel is w4nl64a8h for the whole expert set, bf16 experts beside it.
+# The rest is qwen4exp-w5dn64-i8-hc8m.recipe verbatim: int8 trunk linears, block-fp8 hc mixers
+# and MTP fc, the fixed-scale n-gram table, the 2-bit draft head.
+#
+# Why down is the calibrated half: the calibration tap rides the down projection, so its GPTQ
+# rounding propagates against real down-input Hessians; gate_up shares the same w4 table
+# uncalibrated. The published w5dn64 comparison (mean KL 0.0789 -> 0.0717, top-1 92.85% ->
+# 93.34%, decode +4%, prefill -19%) is the 5-bit upper bound; this tier trades part of that
+# quality back for prefill.
+#
+#   CALIB=DIR rad-convert <Swift1.5-Qwen3.8-Flash-Next checkpoint> \
+#       --recipe scripts/recipes/qwen4exp-swift15-w4dn8-i8-hc8m.recipe -o qwen4exp-swift15-w4dn8-i8-hc8m.rad
+#
+# DIR is the calibration directory the bf16 container wrote (RADIANCE_CALIB_DIR, 10M tokens of
+# traffic-shaped corpus). Everything not named here is served as the checkpoint holds it (bf16:
+# embeddings, the vision tower, the QSA indexer); the first rule that matches a weight decides it.
+# The bf16 container is NOT passed with --reuse: the peak-disk arithmetic does not fit (checkpoint +
+# container + container + output > purge-freed space), and --reuse only saves a re-read.
+
+# The protected experts, cast to bf16 ahead of both expert rules. THE NAMES BELOW ARE THE BASE
+# CHECKPOINT'S (from its 1M-token recording, qwen4exp-w5dn64-i8-hc8m.recipe) -- a warm start only.
+# The Swift 1.5 finetune's routing distribution is not assumed equal: the derivation step rewrites
+# this section from Swift's OWN calibration recording before this recipe is ever run, by the base's
+# law -- an expert whose share of its layer's down-input energy is at least 3% and at least three
+# times its share of the routing, an even count on each rank's half of the layer (the four-bit GEMM
+# takes the rest as two equal tables by parity) by adding that half's next most energetic expert.
+# PROTECTED-BEGIN (rewritten from Swift's OWN grams by derive-protected-experts.py)
+blk.1.ffn_*_exps.271.weight         cast dtype=bf16
+blk.1.ffn_*_exps.355.weight         cast dtype=bf16
+blk.2.ffn_*_exps.279.weight         cast dtype=bf16
+blk.2.ffn_*_exps.413.weight         cast dtype=bf16
+blk.34.ffn_*_exps.146.weight         cast dtype=bf16
+blk.34.ffn_*_exps.153.weight         cast dtype=bf16
+blk.34.ffn_*_exps.407.weight         cast dtype=bf16
+blk.34.ffn_*_exps.453.weight         cast dtype=bf16
+blk.37.ffn_*_exps.288.weight         cast dtype=bf16
+blk.37.ffn_*_exps.377.weight         cast dtype=bf16
+blk.38.ffn_*_exps.406.weight         cast dtype=bf16
+blk.38.ffn_*_exps.420.weight         cast dtype=bf16
+blk.42.ffn_*_exps.37.weight         cast dtype=bf16
+blk.42.ffn_*_exps.90.weight         cast dtype=bf16
+blk.42.ffn_*_exps.302.weight         cast dtype=bf16
+blk.42.ffn_*_exps.388.weight         cast dtype=bf16
+blk.44.ffn_*_exps.315.weight         cast dtype=bf16
+blk.44.ffn_*_exps.350.weight         cast dtype=bf16
+blk.46.ffn_*_exps.290.weight         cast dtype=bf16
+blk.46.ffn_*_exps.419.weight         cast dtype=bf16
+blk.47.ffn_*_exps.119.weight         cast dtype=bf16
+blk.47.ffn_*_exps.143.weight         cast dtype=bf16
+blk.47.ffn_*_exps.399.weight         cast dtype=bf16
+blk.47.ffn_*_exps.445.weight         cast dtype=bf16
+# PROTECTED-END
+# (derive-protected-experts.py rewrote this section from Swift's own grams)
+
+# Every other routed expert, trunk and MTP layer alike: u4 codes into the w4nl table, rotated by
+# the 128-wide Hadamard, an E4M3 scale a group of 64 under the fixed 2^-13 searched for least
+# error as stored, chosen by GPTQ against $CALIB and swept three times by coordinate descent.
+# The calibration Grams are down-input Hessians, so down is the calibrated half of the table;
+# gate_up has no recording of its own and quantises uncalibrated (said on stderr, as the base
+# recipe says). The MTP layer has no recording either. Expert mass: gate_up 150.00 GiB -> ~37.6,
+# down 75.00 GiB -> ~18.8: ~56 GiB of experts, ~28 GiB a rank at TP=2 -- well inside the pool.
+blk.*.ffn_*_exps.*.weight            gptq table=w4nl group=64 scale=fp8_e4m3 scale2=f32 block2=*x* scale2_value=0.0001220703125 transform=fwht128 rule=search cd=3 calib=$CALIB
+
+# Every connection's two mixing matrices -- the 96 trunk connections, the final mixer and the MTP
+# head's three -- as E4M3 rows with an f32 scale a group of each row. A 128x128 block cannot cover
+# them: lowrank is 320, 2.5 blocks. Down is [320, 10240] and takes a scale every 128 columns; up is
+# [10240, 320] and takes four scales a row, 80 columns each.
+*_hc_down.weight                     rtn  codes=fp8_e4m3 group=128 scale=f32
+*_hc_up.weight                       rtn  codes=fp8_e4m3 group=80 scale=f32
+
+# The MTP head's fc_hidden and fc_embedding, the same rows. They only ever change the drafts.
+mtp.fc_hidden.weight                 rtn  codes=fp8_e4m3 group=128 scale=f32
+mtp.fc_embedding.weight              rtn  codes=fp8_e4m3 group=128 scale=f32
+
+# The trunk's block linears as int8, a scale per 128 columns of a row searched for least error.
+# The QSA indexer's projection is not one of them: its top-k is a hard choice between blocks, and
+# keeping it as the checkpoint holds it costs 20 MB.
+blk.*.attn_qg.weight                 rtn  codes=i8 group=128 scale=bf16 clamp=sym rule=search
+blk.*.attn_k.weight                  rtn  codes=i8 group=128 scale=bf16 clamp=sym rule=search
+blk.*.attn_v.weight                  rtn  codes=i8 group=128 scale=bf16 clamp=sym rule=search
+blk.*.attn_output.weight             rtn  codes=i8 group=128 scale=bf16 clamp=sym rule=search
+blk.*.ssm_inz.weight                 rtn  codes=i8 group=128 scale=bf16 clamp=sym rule=search
+blk.*.ssm_out.weight                 rtn  codes=i8 group=128 scale=bf16 clamp=sym rule=search
+blk.*.ffn_gate_up_shexp.weight       rtn  codes=i8 group=128 scale=bf16 clamp=sym rule=search
+blk.*.ffn_down_shexp.weight          rtn  codes=i8 group=128 scale=bf16 clamp=sym rule=search
+
+# The lm_head, int8 with a bf16 scale a row per 128 columns (logits_gemm_i8): at E4M3 it costs
+# ~0.6 points of top-1 on its own.
+output.weight                        rtn  codes=i8 group=128 scale=bf16 clamp=sym rule=search
+
+# The n-gram table at one fixed E4M3 scale; qwen4exp-w4.recipe says where the value comes from.
+# The value sits on a three-octave plateau (2^-13..2^-10, rel_l2 0.02662) with 1.7x headroom over
+# the base table's absmax; the prep phase verifies Swift's PLE absmax lands inside the plateau
+# before this rule is trusted.
+blk.*.ple_ngram.weight               rtn  codes=fp8_e4m3 block=*x* scale=bf16 rule=fixed scale_value=1.99317932128906e-4
+
+# The MTP head's 2-bit draft head. INERT for this checkpoint: the HF weight map has no
+# mtp.draft_head.weight (same as the base), kept for shape parity with the family.
+mtp.draft_head.weight                rtn  codes=u2 zero=u8 group=128 scale=f16

scripts/run-swift15-bf16.sh

@@ -0,0 +1,116 @@
+#!/usr/bin/env bash
+# run-swift15-bf16.sh — RUNS ON DANKSERVER. Boot the no-recipe bf16 Swift1.5
+# container for the two offline campaign phases. The engine owns the GPUs, so
+# the production unit must be stopped first (this script does it and restores
+# on exit, autoresearch pattern: stop, never mask — relinked unit).
+#
+#   kld    --kld-record the reference logits from the bf16 model
+#          (runs the corpus and EXITS; engine writes DIR and leaves)
+#   calib  serve with the calibration tap; a separate driver
+#          (scripts/calib-push.py) pushes the corpus; the engine writes the
+#          Hessians at RADIANCE_CALIB_TOKENS and the tap switches itself off.
+#          Stop this script after calib-push prints TAP_DONE.
+#
+# Shape = the vendor's bf16 calibration lines (GUIDE.md §4.3:528 + MOE-W4.md
+# "calibrate the checkpoint as it ships"): expert_tiered + weights-disk-tier,
+# no speculation, deterministic. Large prefill steps because a disk-tier step
+# costs the same at 1 token as at 32K. The container declared --max-ctx 4096;
+# --max-model-len 16384 exceeds it on purpose (the KLD prompts run to 12,007
+# tokens, calib to 8,242) — the boot ledger arbitrates the QSA buffers; if
+# declare refuses, re-convert with a wider --max-ctx.
+set -uo pipefail
+
+MODE="${1:?usage: run-swift15-bf16.sh kld|calib}"
+PIN_1013=sha256:4c3f484564bb2872784e46b0a59cbd71becc9c1e746e301a3596ffae253c322e
+PIN_120=sha256:665775ed1d90de6dbb25558e07fc60d20328f1346f96f3c6e00845eb763f01fa
+RAD=/home/dank/models/rad/qwen4exp-swift15-bf16.rad
+C=swift15ref
+LOG=/home/dank/logs/swift15_bf16.log
+KLD_REF_DIR=/home/dank/corpora/kld-ref
+CALIB_DIR=/home/dank/corpora/calib
+KLD_CORPUS=/home/dank/corpora/out/kld.jsonl
+
+restore() { sudo systemctl start frank-archon >/dev/null 2>&1 || true; }
+trap restore EXIT
+sudo systemctl stop frank-archon >/dev/null 2>&1 || true
+podman rm -f "$C" >/dev/null 2>&1 || true
+
+ARGS=(--model /models/rad/qwen4exp-swift15-bf16.rad
+      --tp 2 --placement expert_tiered --weights-disk-tier
+      --host-pool-mib 12288 --deterministic --gpu-headroom-mib 768
+      --num-speculative-tokens 0
+      --kv-cache-dtype fp8 --max-model-len 16384
+      --ngram-placement ram
+      --override-chat-template /models/tpl.jinja)
+
+case "$MODE" in
+  kld)
+    # 1.0.13: the engine that will serve the candidate — the reference is
+    # recorded on the same engine that scores it. The weights slab DERIVES as
+    # card - headroom - kv, and the disk tier refuses under 9.57 GiB (4.21 of
+    # layer buffers + 5.36 fixed), so kv is explicit SMALL: recording is
+    # prefill-only, self-batched at MNBT 32768 = two 16k prompts at a time;
+    # 4 slots x 16k fp8 (29 KiB/pos, 1.7 GiB) + headroom fits 3072.
+    IMAGE="stilldeadcode/radiance@$PIN_1013"
+    mkdir -p "$KLD_REF_DIR"
+    ARGS+=(--kld-record /data/kld-ref --kld-corpus /data/kld.jsonl
+           --vram-kv-mib 3072
+           --max-num-seqs 4 --max-num-batched-tokens 32768)
+    ;;
+  calib)
+    # 1.2.0: the calibration tap (RADIANCE_CALIB_DIR + RADIANCE_CALIB_TOKENS)
+    # lives in the 1.2.0 qwen4exp plugin; 1.0.13 has only the DIR half with an
+    # unparameterisable threshold. Grams are bf16 activations — engine-invariant.
+    # Same KV ceiling as kld: the disk-tier weights floor (9.57 GiB) plus
+    # ~18 GiB of fixed per-rank claims cap the pool near 3.5 GiB on a 32 GiB
+    # card — pool minus the 2.17 GiB fixed holds ~237k fp8 tokens a rank, so
+    # the vendor's big-step calibration shape is affordable: MOE-W4.md:244
+    # measures 640 tok/s at a 32k step against 930 at 55k, and the doc's own
+    # run drives MNBT 65536. 8 slots x 16k = 131k resident tokens fits the
+    # pool; the step batches 65k. KLD's observed rate confirmed step size,
+    # not slot count, is the throughput lever.
+    IMAGE="stilldeadcode/radiance@$PIN_120"
+    mkdir -p "$CALIB_DIR"
+    ARGS+=(--port 7770 --vram-kv-mib 3072
+           --max-num-seqs 8 --max-num-batched-tokens 65536
+           --prefix-cache-dir /data/calib-kvcache)
+    ;;
+  probe)
+    IMAGE="stilldeadcode/radiance@$PIN_1013"
+    ARGS+=(--port 7770 --max-num-seqs 8 --max-num-batched-tokens 4096)
+    ;;
+  *) echo "unknown mode: $MODE" >&2; exit 2 ;;
+esac
+
+# The prod template copy, readable from the container: mount the models tree
+# ro plus the state dir rw (KLD record + prefix tier land there).
+cp -f /home/dank/serverAppConfigs/scripts/qwen38-froggeric-v22.5.jinja \
+      /home/dank/models/tpl.jinja 2>/dev/null || true
+
+KLD_MOUNT=()
+if [ "$MODE" = kld ]; then
+    # Nested under the /data mount, so these must come after it (line order
+    # in podman run below): the corpus read-only, the record dir writable.
+    KLD_MOUNT=(-v "$KLD_CORPUS:/data/kld.jsonl:ro"
+               -v "$KLD_REF_DIR:/data/kld-ref")
+fi
+EXTRA_ENV=()
+if [ "$MODE" = calib ]; then
+    EXTRA_ENV=(-v "$CALIB_DIR:/data/calib"
+               -e RADIANCE_CALIB_DIR=/data/calib
+               -e RADIANCE_CALIB_TOKENS=10000000)
+fi
+
+podman run --rm --name "$C" \
+    --network host --init \
+    --security-opt seccomp=unconfined \
+    --ulimit memlock=-1:-1 \
+    --device /dev/kfd --device /dev/dri \
+    -v /home/dank/models:/models:ro \
+    -v /home/dank/radiance-state:/data \
+    "${KLD_MOUNT[@]}" \
+    "${EXTRA_ENV[@]}" \
+    "$IMAGE" "${ARGS[@]}" 2>&1 | tee "$LOG"
+rc=${PIPESTATUS[0]}
+echo "swift15-bf16 $MODE exited rc=$rc; log: $LOG"
+exit "$rc"

scripts/serve-frank-archon.sh

@@ -0,0 +1,196 @@
+#!/usr/bin/env bash
+# serve-frank-archon.sh — frank-archon endpoint: radiance (StillDeadcode,
+# Apache-2.0) serving the OFFICIAL Qwen/Qwen3.8-Flash-Next-FP8 checkpoint at
+# NATIVE block-FP8 precision from a rad-convert container
+# (/home/dank/models/rad/qwen4exp-fp8-native.rad), on BOTH R9700s (TP=2,
+# wht6 wire), dankserver :7770. 2026-10-05 cutover from FreeToken (PR #587,
+# one card; git tag frank-archon-freetoken-pr587-20261005 is the
+# pre-cutover state).
+#
+# The run line below IS the engine argv: the image's entrypoint is the
+# engine and its tools sit beside it on PATH. Unlike every predecessor
+# there is no per-boot VRAM planner to second-guess: the boot ledger in the
+# log states every budget before anything is allocated (weights vs KV
+# split, the expert host pool's coverage of the worst case, the PLE pin,
+# the P2P answer per pair) — read it after every resize.
+# Deployed shape (2026-10-13): THREE decode slots x 200,000 tokens, fp8
+# (quantized) KV in a 5,120 MiB pool (contract 3 x 200,000 + 1.3 %) and a
+# 25,600 MiB resident expert slab — 30,720 MiB of the 30,969 MiB the engine's
+# own budget table makes claimable, spent on the slab because prefill is
+# slab-limited. 44 GiB/rank pinned expert pool, MTP depth 2, prefix cache host
+# 8 GiB + disk 64 GiB, PLE pinned in RAM.
+#
+# The root unit (scripts/frank-archon.service, User=dank,
+# LimitMEMLOCK=infinity) grants the pin budget: 2 x 44 GiB expert pools +
+# the 47.7 GiB PLE table + 8 GiB prefix host tier — ~147 GiB of pinned
+# pages, which is ALSO why this script refuses to start when ttm's
+# pages_limit/pages_max cap is under FRANK_ARCHON_TTM_MIN_MIB (see below).
+set -euo pipefail
+
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+ENV_FILE="${FRANK_ARCHON_ENV_FILE:-$SCRIPT_DIR/frank-archon.env}"
+
+if [ ! -f "$ENV_FILE" ]; then
+    echo "ERROR: frank-archon env file absent: $ENV_FILE" >&2
+    exit 1
+fi
+set -a
+# shellcheck disable=SC1090
+source "$ENV_FILE"
+set +a
+
+: "${FRANK_ARCHON_IMAGE:?FRANK_ARCHON_IMAGE must name the radiance image}"
+: "${FRANK_ARCHON_MODEL_DIR:?FRANK_ARCHON_MODEL_DIR must name the .rad dir}"
+: "${FRANK_ARCHON_MODEL_FILE:?FRANK_ARCHON_MODEL_FILE must name the .rad file}"
+: "${FRANK_ARCHON_STATE_DIR:?FRANK_ARCHON_STATE_DIR must name the /data state dir}"
+: "${FRANK_ARCHON_CONTAINER:?FRANK_ARCHON_CONTAINER must name the container}"
+: "${FRANK_ARCHON_SERVED_NAME:?FRANK_ARCHON_SERVED_NAME must name the alias}"
+: "${FRANK_ARCHON_PORT:?FRANK_ARCHON_PORT must be the port}"
+: "${FRANK_ARCHON_TEMPLATE:?FRANK_ARCHON_TEMPLATE must name the chat template}"
+: "${FRANK_ARCHON_TP:?FRANK_ARCHON_TP must be set}"
+: "${FRANK_ARCHON_TP_WIRE:?FRANK_ARCHON_TP_WIRE must be set}"
+: "${FRANK_ARCHON_MAX_SEQS:?FRANK_ARCHON_MAX_SEQS must be set}"
+: "${FRANK_ARCHON_MAX_MODEL_LEN:?FRANK_ARCHON_MAX_MODEL_LEN must be set}"
+: "${FRANK_ARCHON_PLACEMENT:?FRANK_ARCHON_PLACEMENT must be set}"
+: "${FRANK_ARCHON_HOST_POOL_MIB:?FRANK_ARCHON_HOST_POOL_MIB must be set}"
+: "${FRANK_ARCHON_GPU_HEADROOM_MIB:?FRANK_ARCHON_GPU_HEADROOM_MIB must be set}"
+: "${FRANK_ARCHON_VRAM_WEIGHTS_MIB:?FRANK_ARCHON_VRAM_WEIGHTS_MIB must be set}"
+: "${FRANK_ARCHON_VRAM_KV_MIB:?FRANK_ARCHON_VRAM_KV_MIB must be set}"
+: "${FRANK_ARCHON_KV_DTYPE:?FRANK_ARCHON_KV_DTYPE must be set}"
+: "${FRANK_ARCHON_SPEC_TOKENS:?FRANK_ARCHON_SPEC_TOKENS must be set}"
+: "${FRANK_ARCHON_MAX_BATCHED_TOKENS:?FRANK_ARCHON_MAX_BATCHED_TOKENS must be set}"
+: "${FRANK_ARCHON_PREFIX_HOST_MIB:?FRANK_ARCHON_PREFIX_HOST_MIB must be set}"
+: "${FRANK_ARCHON_PREFIX_DISK_MIB:?FRANK_ARCHON_PREFIX_DISK_MIB must be set}"
+: "${FRANK_ARCHON_NGRAM_PLACEMENT:?FRANK_ARCHON_NGRAM_PLACEMENT must be set}"
+: "${FRANK_ARCHON_TTM_MIN_MIB:?FRANK_ARCHON_TTM_MIN_MIB must be set}"
+: "${FRANK_ARCHON_TTM_TARGET_MIB:?FRANK_ARCHON_TTM_TARGET_MIB must be set}"
+: "${FRANK_ARCHON_RAD_MIN_MIB:?FRANK_ARCHON_RAD_MIN_MIB must be set}"
+
+# The image gate is the digest-pinned ref itself: a name@sha256 ref exists
+# in storage only if THAT manifest was pulled — a retagged look-alike or a
+# newer latest does not satisfy it. `podman image exists` takes a
+# name@digest ref in one command — no pipefail/grep race (the 2026-09-30
+# lesson). Runs as dank: the unit's process uses dank's ROOTLESS podman
+# storage (root unit, User=dank — the fleet's frank-archon shape).
+if ! podman image exists "$FRANK_ARCHON_IMAGE"; then
+    echo "ERROR: radiance image absent: $FRANK_ARCHON_IMAGE" >&2
+    echo "frank-archon: podman pull docker://stilldeadcode/radiance:latest (as dank)" >&2
+    exit 1
+fi
+
+# The payload gate: the .rad container file, sized. A truncated convert
+# would otherwise buy a guaranteed long-timeout boot instead of this fast
+# failure. The staging dir / raw checkpoint are NOT this script's concern
+# (scripts/build-frank-archon-rad.sh built the file; its rad-info output
+# is the record).
+RAD="$FRANK_ARCHON_MODEL_DIR/$FRANK_ARCHON_MODEL_FILE"
+if [ ! -f "$RAD" ]; then
+    echo "ERROR: .rad container missing: $RAD" >&2
+    echo "frank-archon: run scripts/build-frank-archon-rad.sh" >&2
+    exit 1
+fi
+RAD_MIB=$(( $(stat -c %s "$RAD") / 1048576 ))
+if [ "$RAD_MIB" -lt "$FRANK_ARCHON_RAD_MIN_MIB" ]; then
+    echo "ERROR: .rad container too small: $RAD is ${RAD_MIB} MiB, want >= $FRANK_ARCHON_RAD_MIN_MIB" >&2
+    echo "frank-archon: the convert was truncated — rebuild it" >&2
+    exit 1
+fi
+
+if [ ! -f "$FRANK_ARCHON_TEMPLATE" ]; then
+    echo "ERROR: chat template missing: $FRANK_ARCHON_TEMPLATE" >&2
+    exit 1
+fi
+
+mkdir -p "$FRANK_ARCHON_STATE_DIR/kvcache/frank-archon"
+# The engine's create is NOT recursive: with only the state dir mounted, its
+# "cannot create /data/kvcache/frank-archon: No such file or directory"
+# left the SSD prefix tier off (measured 2026-10-06 boot ledger). Pre-create
+# the full path on the host so the tier opens on first boot.
+
+mkdir -p "$FRANK_ARCHON_STATE_DIR/tune"
+# rad-tune's kernel-selection cache (see the runbook's "Tuning levers"):
+# the engine's selector reads $RADIANCE_HOME/tune/<machine>.tune at boot;
+# $RADIANCE_HOME defaults to /opt/radiance, which lives in the image, so
+# the cache must ride a host mount or it dies with the --rm container
+# that wrote it. The dir is pre-created for the same reason as kvcache
+# (the engine's create is not recursive).
+
+if [ ! -e /dev/kfd ] || [ ! -d /dev/dri ]; then
+    echo "ERROR: GPU device nodes absent (/dev/kfd, /dev/dri)" >&2
+    exit 1
+fi
+
+# TTM preflight: the pinned ledger (2 x FRANK_ARCHON_HOST_POOL_MIB + the
+# 47.7 GiB PLE table + the prefix host tier, ~147 GiB) rides TTM's shared
+# pages, capped by ttm's pages_limit (the current kernel exposes NO
+# pages_max; the cap function takes the min over the knobs that exist).
+# Below FRANK_ARCHON_TTM_MIN_MIB the load dies mid-pin with an allocator
+# error, so the gate refuses first — and RAISES the knob before refusing:
+# the cap is a runtime knob whose default is half of RAM, so a power failure
+# resets it (measured 2026-10-12 23:17 on this host: 200 GiB -> 125,988 MiB,
+# and Restart=always re-ran the refusal 6,919 times over ~20 h).
+# FRANK_ARCHON_TTM_TARGET_MIB is the recorded host ceiling, not the floor.
+# shellcheck source=/dev/null
+source "$SCRIPT_DIR/ttm-preflight.sh"
+ttm_ensure_cap || exit 1
+
+# A crashed/killed unit can leave the container name registered (systemd
+# SIGKILLs conmon before cleanup runs). Clear OUR name plus the legacy
+# identities (the FreeToken-era frank-archon-qwen, the retired R9V
+# container and the ad hoc experiment containers all hold this GPU); all
+# idempotent.
+for CTR in $FRANK_ARCHON_LEGACY_CONTAINERS "$FRANK_ARCHON_CONTAINER"; do
+    podman rm -f "$CTR" >/dev/null 2>&1 || true
+done
+
+LOG=/home/dank/logs/frank_archon.log
+mkdir -p "$(dirname "$LOG")"
+
+# Publisher-vetted container contract (docs/DOCKER.md, compose/common.yaml):
+# --network host (the server binds the host's addresses directly, no NAT),
+# --init (the engine releases the cards on SIGTERM), seccomp=unconfined
+# (Docker/podman's default profile refuses io_uring, which the n-gram
+# table's reads go through, and the NUMA binding calls the ROCm runtime
+# makes for host memory), memlock unbounded (the pinned ledger — legal
+# because the root unit grants LimitMEMLOCK=infinity to this dank process),
+# /dev/kfd + /dev/dri (render/video groups are moot for a root container).
+# The template rides a single-file mount; the .rad dir is ro; /data holds
+# the prefix-cache disk tier.
+podman run -d --name "$FRANK_ARCHON_CONTAINER" \
+  --network host \
+  --init \
+  --security-opt seccomp=unconfined \
+  --ulimit memlock=-1:-1 \
+  --device /dev/kfd --device /dev/dri \
+  -v "$FRANK_ARCHON_MODEL_DIR":/models:ro \
+  -v "$FRANK_ARCHON_STATE_DIR":/data \
+  -v "$FRANK_ARCHON_STATE_DIR/tune":/opt/radiance/share/radiance/tune \
+  -v "$FRANK_ARCHON_TEMPLATE":/templates/template.jinja:ro \
+  "$FRANK_ARCHON_IMAGE" \
+  --model "/models/$FRANK_ARCHON_MODEL_FILE" \
+  --host :: --port "$FRANK_ARCHON_PORT" \
+  --served-model-name "$FRANK_ARCHON_SERVED_NAME" \
+  --override-chat-template /templates/template.jinja \
+  --tp "$FRANK_ARCHON_TP" --tp-wire "$FRANK_ARCHON_TP_WIRE" \
+  --max-num-seqs "$FRANK_ARCHON_MAX_SEQS" \
+  --max-model-len "$FRANK_ARCHON_MAX_MODEL_LEN" \
+  --placement "$FRANK_ARCHON_PLACEMENT" \
+  --host-pool-mib "$FRANK_ARCHON_HOST_POOL_MIB" \
+  --gpu-headroom-mib "$FRANK_ARCHON_GPU_HEADROOM_MIB" \
+  --vram-weights-mib "$FRANK_ARCHON_VRAM_WEIGHTS_MIB" \
+  --vram-kv-mib "$FRANK_ARCHON_VRAM_KV_MIB" \
+  --kv-cache-dtype "$FRANK_ARCHON_KV_DTYPE" \
+  --prefix-cache-host-mib "$FRANK_ARCHON_PREFIX_HOST_MIB" \
+  --prefix-cache-dir /data/kvcache/frank-archon \
+  --prefix-cache-disk-mib "$FRANK_ARCHON_PREFIX_DISK_MIB" \
+  --ngram-placement "$FRANK_ARCHON_NGRAM_PLACEMENT" \
+  --num-speculative-tokens "$FRANK_ARCHON_SPEC_TOKENS" \
+  --max-num-batched-tokens "$FRANK_ARCHON_MAX_BATCHED_TOKENS" \
+  ${FRANK_ARCHON_EXTRA_ARGS:+$FRANK_ARCHON_EXTRA_ARGS} \
+  > "$LOG" 2>&1
+
+# From here on, this script's lifetime IS the container's: wait returns the
+# container's exit code, so a crash is a nonzero ExecStart and the unit's
+# Restart=always is real. (systemd stop goes through ExecStop in the unit —
+# podman wait alone cannot stop the container child.)
+exec podman wait "$FRANK_ARCHON_CONTAINER"

scripts/serve-frank-dragoon.sh

@@ -0,0 +1,200 @@
+#!/usr/bin/env bash
+# serve-frank-dragoon.sh — frank-dragoon endpoint: halogen-flash-server 0.16.2
+# (closed-source engine, image ghcr.io/peonist-ai/halogen-flash-server,
+# digest-pinned in frank-dragoon.env) serving the Quat3rnion abliterated
+# Swift1.5 finetune of peonist's Qwen3.8-Flash-Next v2 checkpoint on
+# Dankclaw's Strix Halo iGPU, host :7770. 2026-10-06 cutover from the
+# halogen 27B-dense shape — revert the swap commit's trio to roll back
+# (the 27B payload stays on disk).
+#
+# The engine is driven by `podman run` DIRECTLY (the fleet's frank-archon
+# pattern): the image starts engine + OpenAI frontend in one container.
+# The frontend listens on 8731 inside (HALOGEN_API_PORT default) and is
+# published as host 7770; the engine's own token port (8730, no auth)
+# stays unpublished on the container's loopback. HALOGEN_CHECKPOINT
+# selects the file inside the /models mount; the n-gram lookup table
+# (HALOGEN_NGRAM_TABLE, the card sets it explicitly though the documented
+# fallback is "beside the checkpoint") and the vision tower
+# (HALOGEN_VISION_TOWER) ride in the same directory.
+#
+# Gates mirror the deployer EXACTLY (the 2026-10-01 crash-loop lesson —
+# serve gate and deploy gate disagreeing = green deploy, red unit):
+# checkpoint/n-gram/vision byte-exact, tokenizer directory present with
+# every named file a FLAT REGULAR FILE (a HF cache snapshot's symlinks
+# into blobs/ dangle inside the mount), GPU device nodes present.
+#
+# Why containers instead of a bare binary: the payload is .hgn and only
+# the flash-server line reads it; it ships as a container; the root unit
+# keeps LimitMEMLOCK=infinity for parity and to outlive the login session,
+# exactly like frank-archon's.
+set -euo pipefail
+
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+ENV_FILE="${FRANK_DRAGOON_ENV_FILE:-$SCRIPT_DIR/frank-dragoon.env}"
+if [ ! -f "$ENV_FILE" ]; then
+    echo "frank-dragoon: env file not found: $ENV_FILE" >&2
+    exit 1
+fi
+set -a
+# shellcheck disable=SC1090
+source "$ENV_FILE"
+set +a
+
+: "${FRANK_DRAGOON_IMAGE:?FRANK_DRAGOON_IMAGE must name the digest-pinned image}"
+: "${FRANK_DRAGOON_CONTAINER:?FRANK_DRAGOON_CONTAINER must name the container}"
+: "${FRANK_DRAGOON_PUBLISH:?FRANK_DRAGOON_PUBLISH must be host:container}"
+: "${FRANK_DRAGOON_MODEL_DIR:?FRANK_DRAGOON_MODEL_DIR must name the payload dir}"
+: "${FRANK_DRAGOON_CHECKPOINT:?FRANK_DRAGOON_CHECKPOINT must name the .hgn inside it}"
+: "${FRANK_DRAGOON_CHECKPOINT_BYTES:?FRANK_DRAGOON_CHECKPOINT_BYTES must pin the size}"
+: "${FRANK_DRAGOON_NGRAM_TABLE:?FRANK_DRAGOON_NGRAM_TABLE must name the lookup table}"
+: "${FRANK_DRAGOON_NGRAM_BYTES:?FRANK_DRAGOON_NGRAM_BYTES must pin the table size}"
+: "${FRANK_DRAGOON_VISION_TOWER:?FRANK_DRAGOON_VISION_TOWER must name the tower}"
+: "${FRANK_DRAGOON_VISION_BYTES:?FRANK_DRAGOON_VISION_BYTES must pin the tower size}"
+: "${FRANK_DRAGOON_TOKENIZER_FILES:?FRANK_DRAGOON_TOKENIZER_FILES must list the tokenizer dir contents}"
+: "${HALOGEN_MODEL_ID:?HALOGEN_MODEL_ID must be the served alias (frank-dragoon)}"
+: "${HALOGEN_CTX:?HALOGEN_CTX must be set (per-slot window)}"
+: "${HALOGEN_KV_POOL_POSITIONS:?HALOGEN_KV_POOL_POSITIONS must be set}"
+: "${HALOGEN_KV_SLOTS:?HALOGEN_KV_SLOTS must be set}"
+: "${HALOGEN_SPEC_ADAPT:?HALOGEN_SPEC_ADAPT must be set (0 = head always on)}"
+
+# Capture podman's output BEFORE grepping: under `set -o pipefail` the
+# `podman images | grep -q` pattern races (grep exits on first match,
+# podman dies SIGPIPE 141, pipefail turns the 141 into "no match" — the
+# 2026-09-30 deploy refusal).
+DIGESTS="$(podman images --format '{{.RepoDigests}}')"
+if ! grep -qF "${FRANK_DRAGOON_IMAGE#*@}" <<<"$DIGESTS"; then
+    echo "frank-dragoon: image $FRANK_DRAGOON_IMAGE not in podman storage;" >&2
+    echo "  pull it: podman pull ${FRANK_DRAGOON_IMAGE%@*}" >&2
+    exit 1
+fi
+
+# Size-exact gates on all three payload files: a truncated curl exits 0 on
+# some failures and a partial .hgn loads far enough to look alive, so the
+# byte counts from the Hub tree API are the contract (fleet fetch law).
+ck() {
+    # ck <env-name> <path> <expected-bytes>
+    if [ ! -f "$2" ]; then
+        echo "frank-dragoon: $1 $2 missing;" >&2
+        echo "  fetch it: bash scripts/download-frank-dragoon-flashnext.sh" >&2
+        exit 1
+    fi
+    local sz
+    sz="$(stat -c %s "$2")"
+    if [ "$sz" != "$3" ]; then
+        echo "frank-dragoon: $1 is $sz bytes, expected $3 (partial download?)" >&2
+        exit 1
+    fi
+}
+ck checkpoint "$FRANK_DRAGOON_MODEL_DIR/$FRANK_DRAGOON_CHECKPOINT" "$FRANK_DRAGOON_CHECKPOINT_BYTES"
+ck n-gram-table "$FRANK_DRAGOON_MODEL_DIR/$FRANK_DRAGOON_NGRAM_TABLE" "$FRANK_DRAGOON_NGRAM_BYTES"
+ck vision-tower "$FRANK_DRAGOON_MODEL_DIR/$FRANK_DRAGOON_VISION_TOWER" "$FRANK_DRAGOON_VISION_BYTES"
+
+# The payload ships the tokenizer as a FLAT DIRECTORY. A HuggingFace cache
+# snapshot symlinks each file into a sibling blobs/, and those symlinks
+# dangle inside the container mount — so the directory must be real and
+# every named file must be a regular file, not a link.
+TOK_DIR="$FRANK_DRAGOON_MODEL_DIR/tokenizer"
+if [ -L "$TOK_DIR" ] || [ ! -d "$TOK_DIR" ]; then
+    echo "frank-dragoon: tokenizer dir $TOK_DIR missing or a symlink (HF cache snapshot?);" >&2
+    echo "  fetch it: bash scripts/download-frank-dragoon-flashnext.sh" >&2
+    exit 1
+fi
+for TF in $FRANK_DRAGOON_TOKENIZER_FILES; do
+    if [ ! -f "$TOK_DIR/$TF" ] || [ -L "$TOK_DIR/$TF" ]; then
+        echo "frank-dragoon: tokenizer file $TOK_DIR/$TF missing or a symlink;" >&2
+        echo "  fetch it: bash scripts/download-frank-dragoon-flashnext.sh" >&2
+        exit 1
+    fi
+done
+
+# GPU access is mandatory but the node paths are variables so the seam can
+# drive the gate on a box without an AMD GPU.
+DEV_KFD="${FRANK_DRAGOON_DEV_KFD:-/dev/kfd}"
+DEV_DRI="${FRANK_DRAGOON_DEV_DRI:-/dev/dri}"
+if [ ! -e "$DEV_KFD" ] || [ ! -d "$DEV_DRI" ]; then
+    echo "frank-dragoon: $DEV_KFD or $DEV_DRI missing — no gfx1151 to serve on" >&2
+    exit 1
+fi
+# Host-RAM preflight — the engine's pin gate, checked BEFORE podman run.
+# The engine refuses to pin when MemAvailable is below the checkpoint plus
+# a 16 GiB floor: pinned pages cannot be swapped, and under the floor the
+# n-gram lookup pages in from disk on every long prompt. A RAM-short host
+# (a co-tenant spike, a sibling engine dying) crash-loops the unit — each
+# boot dies in ~5 s at the pin gate — until the RAM clears. The 2026-10-06
+# cutover hit this: 8 boots, MemAvailable 74.77 GiB vs the 78.11 GiB needed,
+# self-resolved in ~2 min when the dying 27B engine freed RAM. Check here and
+# WAIT for the RAM to clear, so a transient dip boots once instead of
+# crash-looping; if it never clears, refuse loudly.
+MEMINFO="${FRANK_DRAGOON_MEMINFO:-/proc/meminfo}"
+PIN_KB=$(( FRANK_DRAGOON_CHECKPOINT_BYTES / 1024 ))
+NEED_KB=$(( PIN_KB + 16 * 1048576 ))
+ram_avail_kb() { awk '/^MemAvailable:/{print $2; exit}' "$MEMINFO"; }
+MEMAVAIL_KB="$(ram_avail_kb)" || MEMAVAIL_KB=""
+if [ -n "$MEMAVAIL_KB" ] && [ "$MEMAVAIL_KB" -lt "$NEED_KB" ]; then
+    WAIT_S="${FRANK_DRAGOON_RAM_WAIT:-600}"
+    GIB() { awk -v kb="$1" 'BEGIN{printf "%.2f", kb/1048576}'; }
+    echo "frank-dragoon: host RAM below the pin gate — MemAvailable $(GIB "$MEMAVAIL_KB") GiB < needed $(GIB "$NEED_KB") GiB ($(GIB "$PIN_KB") GiB checkpoint + 16.00 GiB floor); waiting up to ${WAIT_S}s for host RAM to clear" >&2
+    deadline=$(( $(date +%s) + WAIT_S ))
+    while [ "$(date +%s)" -lt "$deadline" ]; do
+        sleep 5
+        MEMAVAIL_KB="$(ram_avail_kb)" || MEMAVAIL_KB=""
+        if [ -n "$MEMAVAIL_KB" ] && [ "$MEMAVAIL_KB" -ge "$NEED_KB" ]; then
+            break
+        fi
+    done
+    if [ -z "$MEMAVAIL_KB" ] || [ "$MEMAVAIL_KB" -lt "$NEED_KB" ]; then
+        echo "frank-dragoon: MemAvailable $(GIB "${MEMAVAIL_KB:-0}") GiB after ${WAIT_S}s; refusing to start (the engine would refuse the pin)" >&2
+        exit 1
+    fi
+    echo "frank-dragoon: MemAvailable cleared to $(GIB "$MEMAVAIL_KB") GiB; starting" >&2
+fi
+for CTR in ${FRANK_DRAGOON_LEGACY_CONTAINERS:-} "$FRANK_DRAGOON_CONTAINER"; do
+    podman rm -f "$CTR" >/dev/null 2>&1 || true
+done
+
+LOG="${FRANK_DRAGOON_LOG:-/home/dank/logs/frank_dragoon.log}"
+mkdir -p "$(dirname "$LOG")"
+# --ipc=host for the udev-granted supplementary group, seccomp unconfined
+# for the ROCm ioctl surface, and unbounded memlock (the unit's
+# LimitMEMLOCK=infinity is inherited, so runc never has to RAISE it). NO
+# --ulimit nofile: Dankclaw's hard limit is 524288, rootless runc cannot
+# raise a hard limit and dies with "error setting rlimit type 7:
+# operation not permitted" (measured 2026-10-05 cutover); the model card
+# and both sibling serve scripts pass no nofile either. No comment lines
+# inside the backslash chain — a mid-chain # terminates the continuation
+# (the 2026-10-05 exit-127 crash loop on the sibling serve script).
+podman run --name "$FRANK_DRAGOON_CONTAINER" \
+  --publish "$FRANK_DRAGOON_PUBLISH" \
+  --ipc=host \
+  --ulimit memlock=-1:-1 \
+  --device "$DEV_KFD" --device "$DEV_DRI" \
+  --group-add keep-groups \
+  --security-opt seccomp=unconfined \
+  -e HALOGEN_MODEL_ID="$HALOGEN_MODEL_ID" \
+  -e HALOGEN_CHECKPOINT="/models/$FRANK_DRAGOON_CHECKPOINT" \
+  -e HALOGEN_NGRAM_TABLE="/models/$FRANK_DRAGOON_NGRAM_TABLE" \
+  -e HALOGEN_VISION_TOWER="/models/$FRANK_DRAGOON_VISION_TOWER" \
+  -e HALOGEN_TOKENIZER=/tokenizer \
+  -e HALOGEN_CTX="$HALOGEN_CTX" \
+  -e HALOGEN_KV_POOL_POSITIONS="$HALOGEN_KV_POOL_POSITIONS" \
+  -e HALOGEN_KV_SLOTS="$HALOGEN_KV_SLOTS" \
+  -e HALOGEN_HOST_RESERVE_GIB="${HALOGEN_HOST_RESERVE_GIB:-20}" \
+  -e HALOGEN_SPEC_ADAPT="$HALOGEN_SPEC_ADAPT" \
+  -e HALOGEN_MAX_TOK="${HALOGEN_MAX_TOK:-8192}" \
+  -e HALOGEN_MAX_TOKENS_CAP="${HALOGEN_MAX_TOKENS_CAP:-65536}" \
+  -e HALOGEN_QUEUE_TIMEOUT="${HALOGEN_QUEUE_TIMEOUT:-7200}" \
+  -e HALOGEN_TEMPERATURE="${HALOGEN_TEMPERATURE:-1.0}" \
+  -e HALOGEN_TOP_P="${HALOGEN_TOP_P:-0.95}" \
+  -e HALOGEN_TOP_K="${HALOGEN_TOP_K:-20}" \
+  ${HALOGEN_WEIGHTS_LOCK:+-e HALOGEN_WEIGHTS_LOCK="$HALOGEN_WEIGHTS_LOCK"} \
+  -v "$FRANK_DRAGOON_MODEL_DIR:/models:ro" \
+  -v "$FRANK_DRAGOON_MODEL_DIR/tokenizer:/tokenizer:ro" \
+  "$FRANK_DRAGOON_IMAGE" \
+  > "$LOG" 2>&1
+
+# FOREGROUND `podman run`: the engine's stdout/stderr are this script's
+# output, so the boot ledger (kv pool, prompt cache, MTP head, any clamp)
+# lands in $LOG as documented. podman run returns the container's exit
+# code, so a crash is a nonzero ExecStart and the unit's Restart=always
+# stays real; systemd stop goes through the unit's ExecStop and the run
+# client forwards SIGTERM to the engine, which drains on it.

scripts/serve-frank-large.sh

@@ -1,146 +0,0 @@
-#!/usr/bin/env bash
-# serve-frank-large.sh — frank-large endpoint: halogen (closed-source
-# C++/HIP engine, image ghcr.io/peonist-ai/halogen, digest-pinned in
-# frank-large.env) serving peonist-ai/halogen-qwen3.8-27b on Dankclaw's
-# Strix Halo iGPU, host :7770. 2026-10-05 cutover from the ROCmFPX
-# llama.cpp shape — revert the swap commit's trio to roll back (payload
-# and fork build stay on disk).
-#
-# The engine is driven by `podman run` DIRECTLY (the fleet's frank-primary
-# pattern): the image entrypoint `halogen-docker` in default "all" mode
-# starts engine + OpenAI frontend in one container. The frontend listens on
-# 8731 inside (HALOGEN_API_PORT default) and is published as host 7770; the
-# engine's own token port (8730, no auth) stays unpublished on the
-# container's loopback. The image ships NO default checkpoint:
-# HALOGEN_CHECKPOINT selects the file inside the /models mount.
-#
-# Gates mirror the deployer EXACTLY (the 2026-10-01 crash-loop lesson —
-# serve gate and deploy gate disagreeing = green deploy, red unit):
-# tokenizer directory present with every named file a FLAT REGULAR FILE —
-# the model card ships `tokenizer/` as a flat directory and the engine
-# defaults HALOGEN_TOKENIZER to /tokenizer, so a HF cache snapshot's
-# symlinks into blobs/ dangle inside the mount; GPU device nodes present.
-#
-# Why containers instead of the bare binary (the old frank-large shape):
-# the payload is .hgn and only halogen reads it; halogen ships as a
-# container; the root unit keeps LimitMEMLOCK=infinity for parity and to
-# outlive the login session, exactly like frank-primary's.
-set -euo pipefail
-
-SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
-ENV_FILE="${FRANK_LARGE_ENV_FILE:-$SCRIPT_DIR/frank-large.env}"
-if [ ! -f "$ENV_FILE" ]; then
-    echo "frank-large: env file not found: $ENV_FILE" >&2
-    exit 1
-fi
-set -a
-# shellcheck disable=SC1090
-source "$ENV_FILE"
-set +a
-
-: "${FRANK_LARGE_IMAGE:?FRANK_LARGE_IMAGE must name the digest-pinned image}"
-: "${FRANK_LARGE_CONTAINER:?FRANK_LARGE_CONTAINER must name the container}"
-: "${FRANK_LARGE_PUBLISH:?FRANK_LARGE_PUBLISH must be host:container}"
-: "${FRANK_LARGE_MODEL_DIR:?FRANK_LARGE_MODEL_DIR must name the payload dir}"
-: "${FRANK_LARGE_CHECKPOINT:?FRANK_LARGE_CHECKPOINT must name the .hgn inside it}"
-: "${FRANK_LARGE_CHECKPOINT_BYTES:?FRANK_LARGE_CHECKPOINT_BYTES must pin the size}"
-: "${FRANK_LARGE_TOKENIZER_FILES:?FRANK_LARGE_TOKENIZER_FILES must list the tokenizer dir contents}"
-: "${HALOGEN_MODEL_ID:?HALOGEN_MODEL_ID must be the served alias (frank-large)}"
-: "${HALOGEN_SLOT_CTX:?HALOGEN_SLOT_CTX must be set}"
-: "${HALOGEN_KV_SLOTS:?HALOGEN_KV_SLOTS must be set (1 keeps the drafter on)}"
-: "${HALOGEN_DRAFTER:?HALOGEN_DRAFTER must be set (2 = DFlash2)}"
-
-# Capture podman's output BEFORE grepping: under `set -o pipefail` the
-# `podman images | grep -q` pattern races (grep exits on first match,
-# podman dies SIGPIPE 141, pipefail turns the 141 into "no match" — the
-# 2026-09-30 deploy refusal).
-DIGESTS="$(podman images --format '{{.RepoDigests}}')"
-if ! grep -qF "${FRANK_LARGE_IMAGE#*@}" <<<"$DIGESTS"; then
-    echo "frank-large: image $FRANK_LARGE_IMAGE not in podman storage;" >&2
-    echo "  pull it: podman pull ${FRANK_LARGE_IMAGE%@*}" >&2
-    exit 1
-fi
-
-# The checkpoint gate is size-exact: a truncated curl exits 0 on some
-# failures and a partial .hgn loads far enough to look alive, so the byte
-# count from the model card is the contract (the fleet fetch law).
-CKPT="$FRANK_LARGE_MODEL_DIR/$FRANK_LARGE_CHECKPOINT"
-if [ ! -f "$CKPT" ]; then
-    echo "frank-large: checkpoint $CKPT missing;" >&2
-    echo "  fetch it: bash scripts/download-frank-large-halogen.sh" >&2
-    exit 1
-fi
-CKPT_SIZE="$(stat -c %s "$CKPT")"
-if [ "$CKPT_SIZE" != "$FRANK_LARGE_CHECKPOINT_BYTES" ]; then
-    echo "frank-large: checkpoint is $CKPT_SIZE bytes, expected $FRANK_LARGE_CHECKPOINT_BYTES (partial download?)" >&2
-    exit 1
-fi
-
-# The payload ships the tokenizer as a FLAT DIRECTORY (model card:
-# "tokenizer/ flat tokenizer directory"). A HuggingFace cache snapshot
-# symlinks each file into a sibling blobs/, and those symlinks dangle
-# inside the container mount — so the directory must be real and every
-# named file must be a regular file, not a link.
-TOK_DIR="$FRANK_LARGE_MODEL_DIR/tokenizer"
-if [ -L "$TOK_DIR" ] || [ ! -d "$TOK_DIR" ]; then
-    echo "frank-large: tokenizer dir $TOK_DIR missing or a symlink (HF cache snapshot?);" >&2
-    echo "  fetch it: bash scripts/download-frank-large-halogen.sh" >&2
-    exit 1
-fi
-for TF in $FRANK_LARGE_TOKENIZER_FILES; do
-    if [ ! -f "$TOK_DIR/$TF" ] || [ -L "$TOK_DIR/$TF" ]; then
-        echo "frank-large: tokenizer file $TOK_DIR/$TF missing or a symlink;" >&2
-        echo "  fetch it: bash scripts/download-frank-large-halogen.sh" >&2
-        exit 1
-    fi
-done
-
-# GPU access is mandatory but the node paths are variables so the seam can
-# drive the gate on a box without an AMD GPU.
-DEV_KFD="${FRANK_LARGE_DEV_KFD:-/dev/kfd}"
-DEV_DRI="${FRANK_LARGE_DEV_DRI:-/dev/dri}"
-if [ ! -e "$DEV_KFD" ] || [ ! -d "$DEV_DRI" ]; then
-    echo "frank-large: $DEV_KFD or $DEV_DRI missing — no gfx1151 to serve on" >&2
-    exit 1
-fi
-for CTR in ${FRANK_LARGE_LEGACY_CONTAINERS:-} "$FRANK_LARGE_CONTAINER"; do
-    podman rm -f "$CTR" >/dev/null 2>&1 || true
-done
-
-LOG="${FRANK_LARGE_LOG:-/home/dank/logs/frank_large.log}"
-mkdir -p "$(dirname "$LOG")"
-# for the udev-granted supplementary group, seccomp unconfined for the ROCm
-# ioctl surface, and unbounded memlock (the unit's LimitMEMLOCK=infinity is
-# inherited, so runc never has to RAISE it). NO --ulimit nofile: Dankclaw's
-# hard limit is 524288, rootless runc cannot raise a hard limit and dies
-# with "error setting rlimit type 7: operation not permitted" (measured
-# 2026-10-05 cutover), and 524288 fds is already ~100x what the engine
-# wants; the model card and both sibling serve scripts pass no nofile
-# either. No comment lines inside the backslash
-# chain — a mid-chain # terminates the continuation (the 2026-10-05
-# exit-127 crash loop on the sibling serve script).
-podman run -d --name "$FRANK_LARGE_CONTAINER" \
-  --publish "$FRANK_LARGE_PUBLISH" \
-  --ipc=host \
-  --ulimit memlock=-1:-1 \
-  --device "$DEV_KFD" --device "$DEV_DRI" \
-  --group-add keep-groups \
-  --security-opt seccomp=unconfined \
-  -e HALOGEN_MODEL_ID="$HALOGEN_MODEL_ID" \
-  -e HALOGEN_CHECKPOINT="/models/$FRANK_LARGE_CHECKPOINT" \
-  -e HALOGEN_SLOT_CTX="$HALOGEN_SLOT_CTX" \
-  -e HALOGEN_KV_SLOTS="${HALOGEN_KV_SLOTS:-1}" \
-  -e HALOGEN_DRAFTER="$HALOGEN_DRAFTER" \
-  -e HALOGEN_MAX_TOKENS_CAP="${HALOGEN_MAX_TOKENS_CAP:-65536}" \
-  -e HALOGEN_QUEUE_TIMEOUT="${HALOGEN_QUEUE_TIMEOUT:-7200}" \
-  ${HALOGEN_CACHE_MB:+-e HALOGEN_CACHE_MB="$HALOGEN_CACHE_MB"} \
-  -v "$FRANK_LARGE_MODEL_DIR:/models:ro" \
-  -v "$FRANK_LARGE_MODEL_DIR/tokenizer:/tokenizer:ro" \
-  "$FRANK_LARGE_IMAGE" \
-  > "$LOG" 2>&1
-
-# This script's lifetime IS the container's: podman wait returns the
-# container's exit code, so a crash is a nonzero ExecStart and the unit's
-# Restart=always is real. systemd stop goes through the unit's ExecStop
-# (podman wait alone cannot stop the child).
-exec podman wait "$FRANK_LARGE_CONTAINER"

scripts/serve-frank-primary.sh

@@ -1,132 +0,0 @@
-#!/usr/bin/env bash
-# serve-frank-primary.sh — frank-primary endpoint (FreeToken PR #587 ROCm
-# build, orcarouter Qwen3.8-Flash-Next-Uncensored-FP8, ONE R9700 gfx1201,
-# dankserver :7770; 2026-10-05 cutover from the tcclaviger vLLM fork — git
-# tag frank-primary-vllm-shapeG-20261003 is the pre-cutover state).
-#
-# The engine is driven by `podman run` DIRECTLY and the run line below IS
-# the engine argv: the image carries FreeToken installed at pinned PR head
-# 77a7201 (scripts/docker/frank-primary-freetoken.Dockerfile builds it from
-# the PR's own docs/install_amd.md stack). Unlike the vLLM fork there is no
-# per-boot planner: experts live in pinned host RAM with an LRU GPU cache,
-# KV is an explicit token pool, and the boot ledger in the log names
-# Shape: 1 GPU (first-boot conservative — the second R9700 sits idle;
-# --tensor-parallel-size EXISTS in FreeToken, so a 2-card TP shape is future
-# tuning once this single-card shape has a decode baseline), KV pool 300,000
-# tokens (24 KiB/token f16 across the 12 full-attention layers = 7.2 GiB;
-# clears the harness worst case of 177,356 tokens and admits one NATIVE
-# 262,144-token conversation), MoE LRU at 10% of all experts (~12 GiB),
-# 2 decode slots. First-boot conservative; `ft ctl cache --kv/--moe` grows
-# pools live, and the env comment block carries the resize law. Flag
-# surface verified against docs/cli.md of the pinned head AND against
-# `ft serve --help` inside the built image; every value here is env-driven
-# (frank-primary.env).
-
-# The root unit (scripts/frank-primary.service, User=dank,
-# LimitMEMLOCK=infinity) grants the pin budget: ~120 GiB of expert weights
-# plus the ~47.7 GiB PLE table pin in host RAM. A plain shell session also
-# works, but the unit is the fleet-parity boot-persistent shape.
-set -euo pipefail
-
-SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
-ENV_FILE="${FRANK_PRIMARY_ENV_FILE:-$SCRIPT_DIR/frank-primary.env}"
-
-if [ ! -f "$ENV_FILE" ]; then
-    echo "serve-frank-primary: env file missing: $ENV_FILE" >&2
-    exit 1
-fi
-set -a
-# shellcheck disable=SC1090
-source "$ENV_FILE"
-set +a
-
-: "${FRANK_PRIMARY_IMAGE:?FRANK_PRIMARY_IMAGE must name the FreeToken image}"
-: "${FRANK_PRIMARY_MODEL_DIR:?FRANK_PRIMARY_MODEL_DIR must name the FP8 payload}"
-: "${FRANK_PRIMARY_MODEL_SHARDS:?FRANK_PRIMARY_MODEL_SHARDS must give the shard count}"
-: "${FRANK_PRIMARY_CONTAINER:?FRANK_PRIMARY_CONTAINER must name the container}"
-: "${FRANK_PRIMARY_SERVED_NAME:?FRANK_PRIMARY_SERVED_NAME must name the alias}"
-: "${FRANK_PRIMARY_PUBLISH:?FRANK_PRIMARY_PUBLISH must be host:container}"
-: "${FRANK_PRIMARY_FT_GPU:?FRANK_PRIMARY_FT_GPU must name the GPU index}"
-: "${FRANK_PRIMARY_FT_NUM_TOKENS:?FRANK_PRIMARY_FT_NUM_TOKENS must size the KV pool}"
-: "${FRANK_PRIMARY_FT_MAX_RUNNING:?FRANK_PRIMARY_FT_MAX_RUNNING must be set}"
-: "${FRANK_PRIMARY_FT_MAX_OUTPUT_TOKENS:?FRANK_PRIMARY_FT_MAX_OUTPUT_TOKENS must be set}"
-: "${FRANK_PRIMARY_FT_MOE_RATE:?FRANK_PRIMARY_FT_MOE_RATE must be set}"
-
-# The image gate is EXISTENCE IN STORAGE, not a registry digest: the tag is
-# built ON THE HOST (podman build from
-# scripts/docker/frank-primary-freetoken.Dockerfile) and local builds carry
-# no RepoDigests entry — the 362-line vLLM-era RepoDigests grep refused
-# exactly this shape. Pinning lives in the Dockerfile instead: the FreeToken
-# source is checked out at a hardcoded PR-head SHA and the base image is
-# digest-pinned there. `podman image exists` accepts both a local tag and a
-# name@digest ref, and it is one command — no pipefail/grep race (the
-# 2026-09-30 lesson) for either shape.
-if ! podman image exists "$FRANK_PRIMARY_IMAGE"; then
-    echo "serve-frank-primary: image absent from rootless storage: $FRANK_PRIMARY_IMAGE" >&2
-    echo "  build it: podman build -t $FRANK_PRIMARY_IMAGE -f scripts/docker/frank-primary-freetoken.Dockerfile scripts/docker/" >&2
-    exit 1
-fi
-
-if [ ! -f "$FRANK_PRIMARY_MODEL_DIR/config.json" ]; then
-    echo "serve-frank-primary: payload config missing: $FRANK_PRIMARY_MODEL_DIR/config.json" >&2
-    exit 1
-fi
-SHARDS="$(find "$FRANK_PRIMARY_MODEL_DIR" -maxdepth 1 -name 'model-*-of-*.safetensors' | wc -l)"
-if [ "$SHARDS" != "$FRANK_PRIMARY_MODEL_SHARDS" ]; then
-    echo "serve-frank-primary: payload shard count wrong: $FRANK_PRIMARY_MODEL_DIR" >&2
-    echo "  found $SHARDS safetensors, want $FRANK_PRIMARY_MODEL_SHARDS" >&2
-    echo "  re-fetch: scripts/download-frank-primary.sh" >&2
-    exit 1
-fi
-if [ ! -f "$FRANK_PRIMARY_MODEL_DIR/model.safetensors.index.json" ]; then
-    echo "serve-frank-primary: weight-map index missing: $FRANK_PRIMARY_MODEL_DIR/model.safetensors.index.json" >&2
-    exit 1
-fi
-
-if [ ! -e /dev/kfd ] || [ ! -d /dev/dri ]; then
-    echo "serve-frank-primary: GPU device nodes absent (/dev/kfd, /dev/dri)" >&2
-    exit 1
-fi
-
-# A crashed/killed unit can leave the container name registered (systemd
-# SIGKILLs conmon before cleanup runs). Clear OUR name plus the legacy
-# identities (the vLLM-era frank-primary-qwen, the retired R9V container and
-# the ad hoc experiment containers all hold this GPU); all idempotent.
-for CTR in $FRANK_PRIMARY_LEGACY_CONTAINERS "$FRANK_PRIMARY_CONTAINER"; do
-    podman rm -f "$CTR" >/dev/null 2>&1 || true
-done
-
-LOG=/home/dank/logs/frank_primary.log
-mkdir -p "$(dirname "$LOG")"
-
-# --device /dev/dri is the WHOLE DIRECTORY (individual renderD nodes enumerate
-# without the card nodes and HIP refuses contexts). --ipc=host for the
-# engine's shared memory; memlock unbounded for the ~120 GiB pinned expert
-# rows + the 47.7 GiB PLE pin (the unit's LimitMEMLOCK=infinity is the other
-# half of that law).
-# HIP_VISIBLE_DEVICES pins visibility to ONE card so in-container index 0 is
-# the right R9700; --gpu 0 selects it inside the visible set.
-podman run -d --name "$FRANK_PRIMARY_CONTAINER" \
-  --publish "$FRANK_PRIMARY_PUBLISH" \
-  --ipc=host --ulimit memlock=-1:-1 \
-  --cap-add SYS_PTRACE \
-  --device /dev/kfd --device /dev/dri --device /dev/mem \
-  -e HIP_VISIBLE_DEVICES="$FRANK_PRIMARY_FT_GPU" \
-  -v "$FRANK_PRIMARY_MODEL_DIR":/models:ro \
-  "$FRANK_PRIMARY_IMAGE" \
-  ft serve --model /models \
-    --served-model-name "$FRANK_PRIMARY_SERVED_NAME" \
-    --host 0.0.0.0 --port 7770 \
-    --gpu "$FRANK_PRIMARY_FT_GPU" \
-    --num-tokens "$FRANK_PRIMARY_FT_NUM_TOKENS" \
-    --max-running-requests "$FRANK_PRIMARY_FT_MAX_RUNNING" \
-    --max-output-tokens "$FRANK_PRIMARY_FT_MAX_OUTPUT_TOKENS" \
-    --moe-cache-rate "$FRANK_PRIMARY_FT_MOE_RATE" \
-    ${FRANK_PRIMARY_FT_EXTRA_ARGS:+$FRANK_PRIMARY_FT_EXTRA_ARGS} \
-  > "$LOG" 2>&1
-
-# From here on, this script's lifetime IS the container's: wait returns the
-# container's exit code, so a crash is a nonzero ExecStart and the unit's
-# Restart=always is real. (systemd stop goes through ExecStop in the unit —
-# podman wait alone cannot stop the container child.)
-exec podman wait "$FRANK_PRIMARY_CONTAINER"

scripts/serve-frank-small.sh

@@ -1,99 +0,0 @@
-#!/usr/bin/env bash
-# Serve ornith-ai/Ornith-1.5-9B-GGUF (Q8_0) as frank-small on
-# Dankclaw's RTX 3090 via llama.cpp (master build, CUDA sm_86).
-#
-# 2026-10-01 night (Frank): swapped from SGLang + INT8-W8A16-AutoRound
-# safetensors to the llama.cpp GGUF path, because llama.cpp is the only
-# runtime on this host that moves K and V independently — the asymmetric
-# f16-K + q8_0-V contract that endpoint was built for. 2026-10-03 (Frank):
-# the pair is now f16/f16 — two wide slots freed the VRAM, so the values are
-# unquantized too. The per-tensor flags stay explicit either way.
-#
-# Architecture: qwen3_5 hybrid — 32 layers, 8 full-attention + 24 Gated
-# DeltaNet, native 262144 window. KV lives only in the 8 attention layers;
-# the DeltaNet state is per-slot fixed size. Vision comes from the repo's
-# separate projector (the Q6_K GGUF carries no `v.*` tensors at all), so
-# --mmproj is what gives this endpoint eyes; MMPROJ_FILE="" is the documented
-# text-only opt-out.
-#
-# Sampling: llama.cpp takes it per request (the fleet harness sends its
-# recipe from models.yml); greedy is the harness default.
-#
-# Tunables come from frank-small.env unless FRANK_SMALL_ENV_FILE overrides.
-set -euo pipefail
-
-SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)"
-ENV_FILE="${FRANK_SMALL_ENV_FILE:-$SCRIPT_DIR/frank-small.env}"
-if [[ -f "$ENV_FILE" ]]; then
-    set -a
-    # shellcheck disable=SC1090
-    source "$ENV_FILE"
-    set +a
-fi
-
-# --- defaults (used when the env file does not set them) -------------------
-: "${LLAMA_BIN:=/home/dank/GitPackages/llama-master/build-cuda/bin/llama-server}"
-: "${MODEL_FILE:=/home/dank/models/Ornith-Q8/Ornith-1.5-9B-Q8_0.gguf}"
-: "${ALIAS:=frank-small}"
-: "${BIND_ADDR:=0.0.0.0}"
-: "${LISTEN_PORT:=7771}"
-# ctx-size is the POOL llama.cpp divides across slots: 401408 / 2 gives
-# 200,704 per slot — two independent conversations, each one wide enough to
-# hold a whole frank-primary-sized prompt in a single shot (the native 262,144
-# no longer fits twice on a 24 GiB card once the vision tower is loaded;
-# frank-small.env carries the three measurements that set this number).
-: "${CTX_SIZE:=401408}"
-: "${PARALLEL:=2}"
-# Compute-buffer geometry. Before 2026-10-03 this endpoint never passed either
-# flag, so it ran on llama.cpp's own defaults (2048/512). The pair is 4096/2048
-# since 2026-10-05: on this CUDA card the prefill curve climbs all the way to
-# ubatch 2048 (unlike the R9700 layer-split sibling, where 512 is the peak),
-# and the logical batch is VRAM- and throughput-neutral. frank-small.env
-# carries the sweep tables and the VRAM risk note.
-: "${BATCH_SIZE:=4096}"
-: "${UBATCH_SIZE:=2048}"
-: "${CACHE_TYPE_K:=f16}"
-: "${CACHE_TYPE_V:=f16}"
-: "${NGL:=99}"
-# Vision projector. No colon on purpose: an explicitly empty value means
-# "text-only, on purpose" and must NOT be replaced by the default path.
-: "${MMPROJ_FILE=/home/dank/models/Ornith-Q8/mmproj-Ornith-1.5-9B-BF16.gguf}"
-
-# Fail loudly rather than half-loading: a missing file is a download that
-# has not finished, and Restart=always would turn it into a crash loop that
-# reads like a runtime fault.
-for path in "$LLAMA_BIN" "$MODEL_FILE"; do
-    [[ -e "$path" ]] || { echo "frank-small: missing $path" >&2; exit 1; }
-done
-EXTRA_ARGS=()
-if [[ -n "$MMPROJ_FILE" ]]; then
-    [[ -e "$MMPROJ_FILE" ]] || { echo "frank-small: missing $MMPROJ_FILE" >&2; exit 1; }
-    EXTRA_ARGS+=(--mmproj "$MMPROJ_FILE")
-fi
-
-# The UVM device node is created lazily by nvidia-modprobe on the first CUDA
-# open after boot; make sure it exists before the server needs it.
-nvidia-modprobe -u -c=0 2>/dev/null || true
-
-# Flash attention stays pinned on: it is the fast path for f16 KV, and it is
-# the only path that could serve quantized V at all — so if CACHE_TYPE_V is
-# ever set back to q8_0 this flag must not be lost, or the build falls back
-# silently and the KV contract in frank-small.env becomes a lie.
-ARGS=(
-    --model "$MODEL_FILE"
-    --alias "$ALIAS"
-    --host "$BIND_ADDR"
-    --port "$LISTEN_PORT"
-    --ctx-size "$CTX_SIZE"
-    --parallel "$PARALLEL"
-    --batch-size "$BATCH_SIZE"
-    --ubatch-size "$UBATCH_SIZE"
-    --n-gpu-layers "$NGL"
-    --flash-attn on
-    --cache-type-k "$CACHE_TYPE_K"
-    --cache-type-v "$CACHE_TYPE_V"
-    --jinja
-    --reasoning auto
-    --reasoning-format deepseek
-)
-exec "$LLAMA_BIN" "${ARGS[@]}" ${EXTRA_ARGS[@]+"${EXTRA_ARGS[@]}"}

scripts/serve-frank-zealot.sh

@@ -0,0 +1,132 @@
+#!/usr/bin/env bash
+# Serve HauhauCS/Qwen3.5-9B-Uncensored-HauhauCS-Aggressive (Q6_K) as
+# frank-zealot on Dankclaw's RTX 3090 via llama.cpp (master build, CUDA sm_86).
+#
+# 2026-10-07 (Frank): Qwen3.5-9B swap at TWO 200,704-token conversations
+# (--ctx-size 401408 --parallel 2) with EXACT f16 KV — the 9B rung frees the
+# room the 26B MoE Gemma4 shape lacked, so quantized V retires. MTP stays off:
+# this GGUF carries no MTP tensors at all (verified from its tensor-name
+# list), so there is no in-file head to draft with. Verbosity 4 ships so the
+# VRAM-fit forensics (KV layout, buffer sizes, graph capture) land in the journal.
+#
+# Architecture: qwen35 — dense 9B, 32 layers with full_attention_interval 4
+# (8 full-attention layers at 3,7,...,31 + 24 Gated DeltaNet linear layers),
+# 16 heads / 4 KV heads × 256 dim, native 262,144, vocab 248,320. The KV pool
+# scales with the 8 full layers: 32 KiB/token at f16 K + f16 V (12.25 GiB at
+# the 401,408 pool); the DeltaNet layers cost a fixed recurrent state per
+# slot. Feasibility is priced from the MiMo-V2.6-Distill-Qwen-9B boots (same
+# geometry, same card, same shape): 21,276/2,849 at ubatch 1024, 21,846/2,279
+# at ubatch 2048 — the boot ledger, not arithmetic, is the referee.
+# Vision comes from the publisher's own BF16 projector (the model is natively
+# multimodal), so --mmproj is what gives this endpoint eyes; MMPROJ_FILE="" is
+# the documented text-only opt-out.
+#
+# Sampling: llama.cpp takes it per request (the fleet harness sends the
+# publisher recipe from models.yml: thinking temp 0.6 / top_p 0.95 / top_k 20).
+#
+# Tunables come from frank-zealot.env unless FRANK_ZEALOT_ENV_FILE overrides.
+set -euo pipefail
+
+SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)"
+ENV_FILE="${FRANK_ZEALOT_ENV_FILE:-$SCRIPT_DIR/frank-zealot.env}"
+if [[ -f "$ENV_FILE" ]]; then
+    set -a
+    # shellcheck disable=SC1090
+    source "$ENV_FILE"
+    set +a
+fi
+
+# --- defaults (used when the env file does not set them) -------------------
+: "${LLAMA_BIN:=/home/dank/GitPackages/llama-master/build-cuda/bin/llama-server}"
+: "${MODEL_FILE:=/home/dank/models/Qwen35-9B-HauhauCS-Q6K/Qwen3.5-9B-Uncensored-HauhauCS-Aggressive-Q6_K.gguf}"
+: "${ALIAS:=frank-zealot}"
+: "${BIND_ADDR:=0.0.0.0}"
+: "${LISTEN_PORT:=7771}"
+# ctx-size is the POOL llama.cpp divides across slots: 401,408 / 2 = 200,704
+# per conversation, inside the model's trained 262,144. The harness
+# contextWindow MUST quote the PER-SLOT number — a longer prompt is answered
+# with a 400, never truncated.
+: "${CTX_SIZE:=401408}"
+: "${PARALLEL:=2}"
+# Compute-buffer geometry. Ubatch is a prefill knob (decode never moves).
+# 2048 is the measured CUDA optimum (MiMo era, same arch/shape: +4.6 % prefill
+# at 8.9k depth, decode flat, 616 MiB). The logical batch is VRAM- and
+# throughput-neutral at a fixed ubatch.
+: "${BATCH_SIZE:=4096}"
+: "${UBATCH_SIZE:=2048}"
+# Exact (unquantized) KV: f16 K + f16 V, restoring the MiMo-era contract that
+# the 26B Gemma4 shape could not afford. 32 KiB/token at this geometry
+# (8 full-attention layers × 4 KV heads × 256 dim); 12.25 GiB at the 401,408
+# pool. Explicit either way so the contract is visible in the argv, and
+# --flash-attn stays required for any quantized-V fallback (q8_0 = llama.cpp's
+# FP8 class; no true fp8 KV dtype exists in this build).
+: "${CACHE_TYPE_K:=f16}"
+: "${CACHE_TYPE_V:=f16}"
+# Speculative decoding is OFF: this Q6_K file carries NO nextn/mtp tensors, so
+# there is no in-file head (the law: MTP is a property of the file, not of the
+# flags). SPEC_TYPE=none strips BOTH speculative flags (flags move as a set);
+# naming a drafter requires SPEC_DRAFT_FILE alongside SPEC_TYPE — the Gemma4
+# assistant on disk is arch gemma4-assistant and cannot drafter-match qwen35.
+: "${SPEC_TYPE:=none}"
+: "${SPEC_DRAFT_N_MAX:=3}"
+: "${SPEC_DRAFT_FILE:=}"
+: "${NGL:=99}"
+# Log verbosity threshold (llama.cpp -lv). 3 is the engine default (info);
+# 4 adds debug detail (KV layout, buffer sizes, graph capture) which is what
+# the VRAM-fit forensics need. Levels above 4 flood the journal.
+: "${VERBOSITY:=3}"
+# Vision projector. No colon on purpose: an explicitly empty value means
+# "text-only, on purpose" and must NOT be replaced by the default path.
+: "${MMPROJ_FILE=/home/dank/models/Qwen35-9B-HauhauCS-Q6K/mmproj-Qwen3.5-9B-Uncensored-HauhauCS-Aggressive-BF16.gguf}"
+
+# Fail loudly rather than half-loading: a missing file is a download that
+# has not finished, and Restart=always would turn it into a crash loop that
+# reads like a runtime fault.
+for path in "$LLAMA_BIN" "$MODEL_FILE"; do
+    [[ -e "$path" ]] || { echo "frank-zealot: missing $path" >&2; exit 1; }
+done
+EXTRA_ARGS=()
+if [[ -n "$MMPROJ_FILE" ]]; then
+    [[ -e "$MMPROJ_FILE" ]] || { echo "frank-zealot: missing $MMPROJ_FILE" >&2; exit 1; }
+    EXTRA_ARGS+=(--mmproj "$MMPROJ_FILE")
+fi
+
+# Speculative flags move as a set: they reach the argv ONLY when a drafter
+# is named. SPEC_TYPE=none (the shipped contract) strips both — a no-spec
+# baseline must not carry half a spec pair.
+if [[ -n "$SPEC_TYPE" && "$SPEC_TYPE" != "none" ]]; then
+    EXTRA_ARGS+=(--spec-type "$SPEC_TYPE" --spec-draft-n-max "$SPEC_DRAFT_N_MAX")
+if [[ -n "$SPEC_DRAFT_FILE" ]]; then
+    [[ -e "$SPEC_DRAFT_FILE" ]] || { echo "frank-zealot: missing $SPEC_DRAFT_FILE" >&2; exit 1; }
+    EXTRA_ARGS+=(--spec-draft-model "$SPEC_DRAFT_FILE")
+fi
+fi
+
+# The UVM device node is created lazily by nvidia-modprobe on the first CUDA
+# open after boot; make sure it exists before the server needs it.
+nvidia-modprobe -u -c=0 2>/dev/null || true
+
+# Flash attention stays pinned on: it is REQUIRED for quantized V (q8_0),
+# and the build carries GGML_CUDA_FA_ALL_QUANTS=ON (since 2026-09-17), so
+# the q8_0 KV contract in frank-zealot.env is a real path — without this
+# flag or that build option the engine silently falls back and the
+# contract becomes a lie.
+ARGS=(
+    --model "$MODEL_FILE"
+    --alias "$ALIAS"
+    --host "$BIND_ADDR"
+    --port "$LISTEN_PORT"
+    --ctx-size "$CTX_SIZE"
+    --parallel "$PARALLEL"
+    --batch-size "$BATCH_SIZE"
+    --ubatch-size "$UBATCH_SIZE"
+    --n-gpu-layers "$NGL"
+    --flash-attn on
+    --cache-type-k "$CACHE_TYPE_K"
+    --cache-type-v "$CACHE_TYPE_V"
+    --log-verbosity "$VERBOSITY"
+    --jinja
+    --reasoning auto
+    --reasoning-format deepseek
+)
+exec "$LLAMA_BIN" "${ARGS[@]}" ${EXTRA_ARGS[@]+"${EXTRA_ARGS[@]}"}

scripts/stack-qwen38-official-fp8.py

@@ -0,0 +1,556 @@
+#!/usr/bin/env python3
+"""stack-qwen38-official-fp8.py — reshape the official Qwen/Qwen3.8-Flash-Next-FP8
+checkpoint into the form the shipped radiance qwen4exp plugin maps.
+
+Run INSIDE the staging dir's tree (python3 + numpy on the host; data never
+leaves the box). Two transforms, both VALUE-PRESERVING:
+
+1. EXPERTS: the shipped plugin's stacked layout names ONE tensor per family
+   (`mlp.experts.gate_up_proj` [E, 2F, H], `mlp.experts.down_proj` [E, H, F])
+   plus a `<family>_scale_inv` plane at the same index (NO `.weight` in the
+   stacked name — scale_name() appends _scale_inv to the tensor name verbatim),
+   while the official FP8 repo ships per-expert unfused tensors
+   (`experts.<e>.{gate,up,down}_proj.weight` + scale). Stacking is pure byte
+   concatenation along dim 0 — gate rows
+   first inside each expert's gate_up slab, which is the order the block
+   wants (rad_block_moe_fp8.h: "a stacked gate_up is ALREADY FUSED in the
+   order this block wants"). No requantisation: bytes are moved, not decoded.
+
+2. PLE TABLE: the plugin's fp8 branch wants the table's codes beside a
+   ONE-ELEMENT bf16 scale plane (`blk.%d.ple_ngram.scale`, view {1}); a
+   per-shard-blocked scale can never fit that view, and `rtn` re-encoding the
+   RAW scaleless codes would overflow (v / 1.99e-4 exceeds e4m3's 448 max).
+   So staging decodes the scaleless shards with the checkpoint's OWN bf16
+   scale into a bf16 table (exact: every e4m3 code value and the scale are
+   exactly representable in bf16 to within the code's own 2^-3 grid), and the
+   convert's rtn rule re-encodes at that same scale — the nearest-code
+   distance is 2^-3 while the bf16 rounding perturbs by 2^-9, so every
+   original code is restored exactly and the container gets the checkpoint's
+   own codes plus the one-element scale plane.
+
+The convert then runs with NO recipe except:
+  blk.*.ple_ngram.weight=rtn:codes=fp8_e4m3,block=*x*,scale=bf16,rule=fixed,scale_value=<s>
+with <s> read from the checkpoint and written to ple_scale.txt.
+
+Idempotent: re-runs skip when the staged index already carries the stacked
+names, the merged bf16 shard_0, and split_ngram_parts == 1. --force redoes.
+"""
+
+import argparse
+import json
+import mmap
+import multiprocessing as mp
+import os
+import re
+import struct
+import sys
+import time
+import numpy as np
+F8, BF16 = "F8_E4M3", "BF16"
+
+
+def log(msg):
+    print(msg, flush=True)
+
+
+# ---------------------------------------------------------------- safetensors
+
+def parse_header(path):
+    """Return (header_len, {name: (dtype, shape, data_offsets)})."""
+    with open(path, "rb") as fh:
+        (hlen,) = struct.unpack("<Q", fh.read(8))
+        hdr = json.loads(fh.read(hlen))
+    return hlen, hdr
+
+
+def write_safetensors(path, tensors, data_iter):
+    """tensors: [(name, dtype, shape, nbytes)]; data_iter yields bytes per tensor."""
+    hdr = {}
+    off = 0
+    for name, dtype, shape, nbytes in tensors:
+        hdr[name] = {"dtype": dtype, "shape": list(shape),
+                     "data_offsets": [off, off + nbytes]}
+        off += nbytes
+    blob = json.dumps(hdr, separators=(",", ":")).encode("utf-8")
+    pad = (-len(blob)) % 8  # keep the data start 8-byte aligned
+    blob += b" " * pad
+    with open(path, "wb") as fh:
+        fh.write(struct.pack("<Q", len(blob)))
+        fh.write(blob)
+        for _, _, _, nbytes in tensors:
+            fh.write(next(data_iter).tobytes())
+        fh.flush()
+        os.fsync(fh.fileno())
+    return 8 + len(blob) + sum(t[3] for t in tensors)
+
+
+# ------------------------------------------------------------------- preflight
+
+def build_meta(stage, index):
+    """name -> (file, global_byte_offset, nbytes, dtype, shape) for every tensor."""
+    files = sorted(set(index["weight_map"].values()))
+    meta = {}
+    for f in files:
+        path = os.path.join(stage, f)
+        hlen, hdr = parse_header(path)
+        for name, e in hdr.items():
+            if name == "__metadata__":
+                continue
+            b0, b1 = e["data_offsets"]
+            meta[name] = (f, 8 + hlen + b0, b1 - b0, e["dtype"], e["shape"])
+    return meta
+
+
+def e4m3_lut():
+    lut = np.zeros(256, np.float32)
+    for b in range(256):
+        sign = -1.0 if b & 0x80 else 1.0
+        e = (b >> 3) & 0xF
+        m = b & 0x7
+        if e == 15 and m == 7:
+            v = np.float32(np.nan)  # OCP e4m3fn: only 0x7F/0xFF are NaN
+        elif e == 0:
+            v = sign * (m / 8.0) * 2.0 ** -6
+        else:
+            v = sign * (1.0 + m / 8.0) * 2.0 ** (e - 7)
+        lut[b] = v
+    assert lut[0x38] == 1.0 and lut[0x7E] == 448.0
+    assert np.isnan(lut[0x7F]) and lut[0x00] == 0.0
+    assert lut[0x08] == 2.0 ** -6 and lut[0x80] == 0.0
+    return lut
+
+
+def f32_to_bf16_rne(v):
+    """float32 array -> uint16 bf16 bits, round-to-nearest-even."""
+    q = np.ascontiguousarray(v, dtype=np.float32)
+    q[~np.isfinite(q)] = 0.0
+    bits = q.view(np.uint32)
+    r = bits + 0x7FFF + ((bits >> 16) & 1)
+    return (r >> 16).astype(np.uint16)
+
+
+# ------------------------------------------------------------------- workers
+
+def stack_prefix(job):
+    """Byte-stack one layer's 512 experts into a 4-tensor safetensors file."""
+    (stage, pre, idx, n_e, shapes, meta) = job
+    (f2, h) = shapes["ffn2_h"]          # 2*ffn, n_embd
+    (f,) = shapes["ffn"]                # ffn
+    gs, ds = shapes["gs"], shapes["ds"] # scale shapes [5,20] and [20,5]
+
+    # byte widths: fp8 is 1 B/element, bf16 2 B; the fused gate_up scale is
+    # the gate and up scale planes concatenated (gate rows first)
+    g_bytes = (f2 // 2) * h
+    gs_bytes = gs[0] * gs[1] * 2          # ONE projection's scale plane
+    gus_bytes = 2 * gs_bytes              # fused scale per expert
+    dn_bytes = h * f
+    ds_bytes = ds[0] * ds[1] * 2
+
+    gu = np.empty(n_e * f2 * h, np.uint8)
+    gus = np.empty(n_e * gus_bytes, np.uint8)
+    dn = np.empty(n_e * dn_bytes, np.uint8)
+    dns = np.empty(n_e * ds_bytes, np.uint8)
+
+    mmaps = {}
+
+    def view(name):
+        f_, off, ln, dt, shp = meta[name]
+        if f_ not in mmaps:
+            fh = open(os.path.join(stage, f_), "rb")
+            mmaps[f_] = mmap.mmap(fh.fileno(), 0, access=mmap.ACCESS_READ)
+        return memoryview(mmaps[f_])[off:off + ln], (dt, shp)
+
+    def need(name, dt, shp):
+        mv, (got_dt, got_shp) = view(name)
+        assert got_dt == dt and list(got_shp) == list(shp), f"{name}: {got_dt}{got_shp}"
+        return mv
+
+    for e in range(n_e):
+        base = f"{pre}.mlp.experts.{e}"
+        slab = gu[e * f2 * h:(e + 1) * f2 * h]
+        slab[:g_bytes] = need(f"{base}.gate_proj.weight", F8, [f2 // 2, h])
+        slab[g_bytes:] = need(f"{base}.up_proj.weight", F8, [f2 // 2, h])
+        sslab = gus[e * gus_bytes:(e + 1) * gus_bytes]
+        sslab[:gs_bytes] = need(f"{base}.gate_proj.weight_scale_inv", BF16, gs)
+        sslab[gs_bytes:] = need(f"{base}.up_proj.weight_scale_inv", BF16, gs)
+        dn[e * dn_bytes:(e + 1) * dn_bytes] = need(f"{base}.down_proj.weight", F8, [h, f])
+        dns[e * ds_bytes:(e + 1) * ds_bytes] = need(f"{base}.down_proj.weight_scale_inv", BF16, ds)
+
+    for mm in mmaps.values():
+        mm.close()
+
+    # byte-identity check on two sampled experts (first and last), all four
+    # tensors — the stack IS the checkpoint bytes, so they must compare equal
+    for e in (0, n_e - 1):
+        base = f"{pre}.mlp.experts.{e}"
+        s = e * f2 * h
+        assert bytes(gu[s:s + g_bytes]) == bytes(stack_src(f"{base}.gate_proj.weight", meta, stage))
+        assert bytes(gu[s + g_bytes:s + f2 * h]) == bytes(stack_src(f"{base}.up_proj.weight", meta, stage))
+        t = e * gus_bytes
+        assert bytes(gus[t:t + gs_bytes]) == bytes(stack_src(f"{base}.gate_proj.weight_scale_inv", meta, stage))
+        assert bytes(gus[t + gs_bytes:t + gus_bytes]) == bytes(stack_src(f"{base}.up_proj.weight_scale_inv", meta, stage))
+        d = e * dn_bytes
+        assert bytes(dn[d:d + dn_bytes]) == bytes(stack_src(f"{base}.down_proj.weight", meta, stage))
+        u = e * ds_bytes
+        assert bytes(dns[u:u + ds_bytes]) == bytes(stack_src(f"{base}.down_proj.weight_scale_inv", meta, stage))
+
+    out = os.path.join(stage, f"stacked.{idx:03d}.safetensors")
+    tensors = [
+        (f"{pre}.mlp.experts.gate_up_proj", F8, [n_e, f2, h], n_e * f2 * h),
+        (f"{pre}.mlp.experts.gate_up_proj_scale_inv", BF16,
+         [n_e, gs[0] * 2, gs[1]], n_e * gus_bytes),
+        (f"{pre}.mlp.experts.down_proj", F8, [n_e, h, f], n_e * h * f),
+        (f"{pre}.mlp.experts.down_proj_scale_inv", BF16,
+         [n_e, ds[0], ds[1]], n_e * ds_bytes),
+    ]
+    bufs = iter([gu, gus, dn, dns])
+    written = write_safetensors(out, tensors, bufs)
+    return (pre, written)
+
+
+def stack_src(name, meta, stage):
+    """Re-open a source tensor for the sampled-expert check."""
+    f_, off, ln, dt, shp = meta[name]
+    fh = open(os.path.join(stage, f_), "rb")
+    mm = mmap.mmap(fh.fileno(), 0, access=mmap.ACCESS_READ)
+    fh.close()  # mmap keeps the mapping alive
+    return mm[off:off + ln]
+
+
+def fill_ple_shard(job):
+    """Decode one fp8 shard with the table scale, write bf16 rows into the mmap."""
+    (src_path, src_off, src_rows, dst_path, dst_off, scale_f32,
+     cols, chunk_rows) = job
+    lut = e4m3_lut()
+    with open(src_path, "rb") as fh:
+        sm = mmap.mmap(fh.fileno(), 0, access=mmap.ACCESS_READ)
+        with open(dst_path, "r+b") as dfh:
+            dm = mmap.mmap(dfh.fileno(), 0, access=mmap.ACCESS_WRITE)
+            for r0 in range(0, src_rows, chunk_rows):
+                r1 = min(r0 + chunk_rows, src_rows)
+                codes = np.frombuffer(sm, dtype=np.uint8,
+                                      count=(r1 - r0) * cols,
+                                      offset=src_off + r0 * cols)
+                q = lut.take(codes)
+                del codes  # release the mmap export before sm.close()
+                q[~np.isfinite(q)] = 0.0
+                q *= np.float32(scale_f32)
+                packed = f32_to_bf16_rne(q)
+                dm[dst_off + r0 * cols * 2: dst_off + r1 * cols * 2] = packed.tobytes()
+            dm.flush()
+            os.fsync(dfh.fileno())
+            dm.close()
+        sm.close()
+
+
+# ---------------------------------------------------------------------- main
+
+def main():
+    ap = argparse.ArgumentParser(description=__doc__.split("\n")[0])
+    ap.add_argument("--src", default=None,
+                    help="raw checkpoint dir (documentation only; unused)")
+    ap.add_argument("--stage", required=True, help="staging dir to reshape in place")
+    ap.add_argument("--force", action="store_true", help="redo even if already staged")
+    ap.add_argument("--workers", type=int, default=min(8, os.cpu_count() or 1))
+    args = ap.parse_args()
+    stage = args.stage
+    t0 = time.time()
+
+    index_path = os.path.join(stage, "model.safetensors.index.json")
+    cfg_path = os.path.join(stage, "config.json")
+    if not (os.path.isfile(index_path) and os.path.isfile(cfg_path)):
+        log(f"ERROR: {stage} is not a staged checkpoint (missing index/config)")
+        return 2
+    with open(index_path) as fh:
+        index = json.load(fh)
+    with open(cfg_path) as fh:
+        cfg = json.load(fh)
+    wm = index["weight_map"]
+
+    meta = build_meta(stage, index)
+
+    # ---- collect prefixes -------------------------------------------------
+    pre_re = re.compile(r"^(?P<pre>.+)\.mlp\.experts\.(?P<e>\d+)\.gate_proj\.weight$")
+    pres, n_e = {}, 0
+    for k in wm:
+        m = pre_re.match(k)
+        if m:
+            pres.setdefault(m.group("pre"), set()).add(int(m.group("e")))
+            n_e = max(n_e, int(m.group("e")) + 1)
+    prefixes = sorted(pres)
+    if not prefixes:
+        log("ERROR: no per-expert tensors found in the staged index")
+        return 2
+    mtp = [p for p in prefixes if p.startswith("mtp.")]
+    trunk = [p for p in prefixes if p.startswith("model.language_model.layers.")]
+    log(f"expert prefixes: {len(prefixes)} (trunk {len(trunk)}, mtp {len(mtp)}), "
+        f"{n_e} experts each")
+
+    # shapes from expert 0 of the first prefix
+    pre0 = prefixes[0]
+    shapes = {}
+    gdt, gsh = meta[f"{pre0}.mlp.experts.0.gate_proj.weight"][3:5]
+    ddt, dsh = meta[f"{pre0}.mlp.experts.0.down_proj.weight"][3:5]
+    gsd, gssh = meta[f"{pre0}.mlp.experts.0.gate_proj.weight_scale_inv"][3:5]
+    dsd, dssh = meta[f"{pre0}.mlp.experts.0.down_proj.weight_scale_inv"][3:5]
+    scale_law = (gdt == F8 and ddt == F8 and gsd == BF16 and dsd == BF16
+                 and list(gssh) == [(gsh[0] + 127) // 128, (gsh[1] + 127) // 128]
+                 and list(dssh) == [(dsh[0] + 127) // 128, (dsh[1] + 127) // 128])
+    if not scale_law:
+        log(f"ERROR: unexpected expert shapes: gate {gdt}{gsh} scale {gsd}{gssh} "
+            f"down {ddt}{dsh} scale {dsd}{dssh} (scale law 128x128)")
+        return 2
+    shapes = {"ffn2_h": (gsh[0] * 2, gsh[1]), "ffn": (dsh[1],),
+              "gs": tuple(gssh), "ds": tuple(dssh)}
+    f2, h = shapes["ffn2_h"]
+    f = shapes["ffn"][0]
+    log(f"shapes: gate_up [{n_e},{f2},{h}] F8, down [{n_e},{h},{f}] F8, "
+        f"scales {gssh}x2 / {dssh} bf16")
+
+    # ---- PLE table --------------------------------------------------------
+    ple_re = re.compile(r"^(?P<pre>.+)\.ple\.ple_embedding\.ngram_embedding\.shard_(?P<i>\d+)\.weight$")
+    ple_pre, shard_ids = None, {}
+    for k in wm:
+        m = ple_re.match(k)
+        if m:
+            ple_pre = m.group("pre")
+            shard_ids[int(m.group("i"))] = k
+    if ple_pre is None:
+        log("ERROR: no PLE table shards found")
+        return 2
+    n_shards = len(shard_ids)
+    if sorted(shard_ids) != list(range(n_shards)):
+        log(f"ERROR: PLE shard ids not contiguous 0..{n_shards - 1}")
+        return 2
+    sc_name = f"{ple_pre}.ple.ple_embedding.ngram_embedding.weight_scale"
+    sdt, ssh, sln = meta[sc_name][3], meta[sc_name][4], meta[sc_name][2]
+    if sdt != BF16 or list(ssh) != [1]:
+        log(f"ERROR: PLE scale is {sdt}{ssh}, expected BF16 [1]")
+        return 2
+    s_bits = struct.unpack("<H", bytes(view_src_tuple(meta, sc_name, stage)))[0]
+    scale_f32 = struct.unpack("<f", struct.pack("<I", s_bits << 16))[0]
+    log(f"PLE: {ple_pre}, {n_shards} shards, scale bf16 = {scale_f32!r}")
+
+    rows = [meta[shard_ids[i]][4][0] for i in range(n_shards)]
+    total_rows = sum(rows)
+    hd = meta[shard_ids[0]][4][1]
+    if any(meta[shard_ids[i]][4][1] != hd for i in range(n_shards)):
+        log("ERROR: PLE shards disagree on HD")
+        return 2
+    if hd % 128 != 0 and hd != 160:
+        log(f"WARNING: PLE HD={hd} is neither 160 nor a multiple of 128")
+
+    # ---- idempotence gate -------------------------------------------------
+    stacked_names = [f"{p}.mlp.experts.gate_up_proj" for p in prefixes]
+    merged_name = f"{ple_pre}.ple.ple_embedding.ngram_embedding.shard_0.weight"
+    already = (all(n in wm for n in stacked_names)
+               and merged_name in wm
+               and find_split(cfg) is not None and read_split(cfg) == 1)
+    if already and not args.force:
+        log("already staged (stacked names, merged shard_0 and split_ngram_parts=1 "
+            "all present) — nothing to do")
+        return 0
+
+    # ---- disk gate --------------------------------------------------------
+    stacked_bytes = len(prefixes) * n_e * (f2 * h + h * f)
+    ple_bytes = total_rows * hd * 2
+    need = stacked_bytes + ple_bytes
+    st = os.statvfs(stage)
+    avail = st.f_bavail * st.f_frsize
+    if avail < need * 1.05:
+        log(f"ERROR: {avail / 2**30:.1f} GiB free < {need / 2**30:.1f} GiB needed (+5%)")
+        return 2
+    log(f"disk: {avail / 2**30:.1f} GiB free, need {need / 2**30:.1f} GiB "
+        f"(experts {stacked_bytes / 2**30:.1f}, ple {ple_bytes / 2**30:.1f})")
+
+    # ---- stage experts ----------------------------------------------------
+    jobs = []
+    for idx, pre in enumerate(prefixes):
+        jmeta = {n: meta[n] for n in meta if n.startswith(f"{pre}.mlp.experts.")}
+        jobs.append((stage, pre, idx, n_e, shapes, jmeta))
+    ctx = mp.get_context("fork")
+    written_total = 0
+    with ctx.Pool(args.workers) as pool:
+        for pre, nbytes in pool.imap_unordered(stack_prefix, jobs):
+            written_total += nbytes
+            log(f"  stacked {pre} ({nbytes / 2**30:.2f} GiB)")
+    log(f"experts stacked: {written_total / 2**30:.2f} GiB in {len(prefixes)} files")
+
+    # ---- stage PLE --------------------------------------------------------
+    # The file name sorts BEFORE the model-000NN shards ON PURPOSE: the reader
+    # opens every index-named file in sorted order and emplaces EVERY tensor
+    # it physically holds, first-wins (checkpoint.cpp add_shard). The raw
+    # shards carry tensors of the SAME name as the merged one
+    # (...ple.ple_embedding.ngram_embedding.shard_0.weight, [2500012,160]
+    # fp8), so ple.merged.safetensors lost the race and the plan read one raw
+    # shard as the codes. "00-" wins the sort and the name.
+    out_name = "00-ple.merged.safetensors"
+    out_path = os.path.join(stage, out_name)
+    data_bytes = total_rows * hd * 2
+    hdr = {merged_name: {"dtype": BF16, "shape": [total_rows, hd],
+                         "data_offsets": [0, data_bytes]}}
+    blob = json.dumps(hdr, separators=(",", ":")).encode("utf-8")
+    pad = (-len(blob)) % 8
+    blob += b" " * pad
+    hlen = len(blob)
+    with open(out_path, "wb") as fh:
+        fh.write(struct.pack("<Q", hlen))
+        fh.write(blob)
+        fh.truncate(8 + hlen + data_bytes)
+    jobs = []
+    row0 = 0
+    for i in range(n_shards):
+        f_, off, ln, _, shp = meta[shard_ids[i]]
+        jobs.append((os.path.join(stage, f_), off, shp[0], out_path,
+                     8 + hlen + row0 * hd * 2, scale_f32, hd, 131072))
+        row0 += shp[0]
+    assert row0 == total_rows
+    with ctx.Pool(args.workers) as pool:
+        pool.map(fill_ple_shard, jobs)
+    log(f"PLE merged: {data_bytes / 2**30:.2f} GiB bf16 "
+        f"({total_rows} rows x {hd} cols)")
+
+    # ---- post-verify ------------------------------------------------------
+    verify(stage, prefixes, n_e, shapes, meta, shard_ids, rows, hd,
+           scale_f32, out_path, hlen)
+
+    # ---- rewrite index + config -------------------------------------------
+    new_wm = {k: v for k, v in wm.items() if k not in set(shard_ids.values())}
+    for idx, pre in enumerate(prefixes):
+        fname = f"stacked.{idx:03d}.safetensors"
+        for t in (f"{pre}.mlp.experts.gate_up_proj",
+                  f"{pre}.mlp.experts.gate_up_proj_scale_inv",
+                  f"{pre}.mlp.experts.down_proj",
+                  f"{pre}.mlp.experts.down_proj_scale_inv"):
+            new_wm[t] = fname
+    new_wm[merged_name] = out_name
+    total = sum(meta_size(meta, k) for k in new_wm
+                if k in meta)  # originals
+    # new tensors' sizes
+    total += written_total + data_bytes
+    index["weight_map"] = new_wm
+    if "metadata" in index and isinstance(index["metadata"], dict):
+        index["metadata"]["total_size"] = total
+    # ATOMIC REPLACE, never open(path, "w"): the stage's index is a symlink
+    # to the RAW checkpoint (staging symlinks everything but config.json) —
+    # open("w") would rewrite the raw file through the link. os.replace
+    # swaps the link itself for a real file; the raw tree stays pristine.
+    for path, payload in ((index_path, json.dumps(index, indent=2)),
+                          (cfg_path, json.dumps(cfg, indent=2))):
+        tmp = path + ".tmp"
+        with open(tmp, "w") as fh:
+            fh.write(payload)
+        os.replace(tmp, path)
+    n = set_split(cfg, 1)
+    log(f"config: split_ngram_parts=1 written at {n} location(s)")
+
+    with open(os.path.join(stage, "ple_scale.txt"), "w") as fh:
+        fh.write(repr(scale_f32) + "\n")
+
+    dt = time.time() - t0
+    log(f"staged in {dt / 60:.1f} min: {written_total / 2**30:.1f} GiB experts + "
+        f"{data_bytes / 2**30:.1f} GiB PLE; scale {scale_f32!r} -> ple_scale.txt")
+    return 0
+
+
+def meta_size(meta, name):
+    _, _, ln, _, _ = meta[name]
+    return ln
+
+
+def view_src_tuple(meta, name, stage):
+    f_, off, ln, _, _ = meta[name]
+    with open(os.path.join(stage, f_), "rb") as fh:
+        fh.seek(off)
+        return fh.read(ln)
+
+
+def find_split(cfg):
+    """Locate split_ngram_parts keys (recursive); return list of paths."""
+    hits = []
+
+    def walk(d, path):
+        if isinstance(d, dict):
+            for k, v in d.items():
+                if k == "split_ngram_parts":
+                    hits.append(path + [k])
+                walk(v, path + [k])
+    walk(cfg, [])
+    return hits
+
+
+def read_split(cfg):
+    hits = find_split(cfg)
+    if not hits:
+        return None
+    d = cfg
+    for k in hits[0][:-1]:
+        d = d[k]
+    return d[hits[0][-1]]
+
+
+def set_split(cfg, value):
+    hits = find_split(cfg)
+    for path in hits:
+        d = cfg
+        for k in path[:-1]:
+            d = d[k]
+        d[path[-1]] = value
+    if not hits:  # plugin's meta_int2 falls back to the top-level key
+        cfg["split_ngram_parts"] = value
+        hits.append(["split_ngram_parts"])
+    return hits
+
+
+def verify(stage, prefixes, n_e, shapes, meta, shard_ids, rows, hd,
+           scale_f32, out_path, hlen):
+    """Cheap strong checks: headers parse, sizes match, sampled bytes identical."""
+    f2, h = shapes["ffn2_h"]
+    f = shapes["ffn"][0]
+    gs, ds = shapes["gs"], shapes["ds"]
+    # headers of every new file
+    for idx, pre in enumerate(prefixes):
+        path = os.path.join(stage, f"stacked.{idx:03d}.safetensors")
+        hlen2, hdr = parse_header(path)
+        want = {
+            f"{pre}.mlp.experts.gate_up_proj": (F8, [n_e, f2, h]),
+            f"{pre}.mlp.experts.gate_up_proj_scale_inv":
+                (BF16, [n_e, gs[0] * 2, gs[1]]),
+            f"{pre}.mlp.experts.down_proj": (F8, [n_e, h, f]),
+            f"{pre}.mlp.experts.down_proj_scale_inv": (BF16, [n_e, ds[0], ds[1]]),
+        }
+        for name, (dt, shp) in want.items():
+            e = hdr[name]
+            assert e["dtype"] == dt and list(e["shape"]) == shp, name
+            assert e["data_offsets"][1] - e["data_offsets"][0] == \
+                int(np.prod(shp)) * (1 if dt == F8 else 2), name
+    _, phdr = parse_header(out_path)
+    e = phdr[next(iter(phdr))]
+    assert e["dtype"] == BF16 and list(e["shape"]) == [sum(rows), hd]
+
+    # sampled PLE rows: recompute and compare bytes exactly
+    lut = e4m3_lut()
+    out_off = 8 + hlen
+    for i in (0, len(shard_ids) // 2, len(shard_ids) - 1):
+        name = shard_ids[i]
+        f_, off, ln, _, shp = meta[name]
+        with open(os.path.join(stage, f_), "rb") as fh:
+            mm = mmap.mmap(fh.fileno(), 0, access=mmap.ACCESS_READ)
+            for r in (0, shp[0] - 1):
+                codes = np.frombuffer(mm, dtype=np.uint8, count=hd,
+                                      offset=off + r * hd)
+                q = lut.take(codes) * np.float32(scale_f32)
+                del codes  # release the mmap export before mm.close()
+                want = f32_to_bf16_rne(q).tobytes()
+                got_row = sum(rows[:i]) + r
+                with open(out_path, "rb") as ofh:
+                    ofh.seek(out_off + got_row * hd * 2)
+                    got = ofh.read(hd * 2)
+                assert got == want, f"PLE row {got_row} mismatch"
+            mm.close()
+    log("verify: new-file headers, sizes and sampled PLE rows all exact; "
+        "expert slabs were byte-checked in-stack")
+
+
+if __name__ == "__main__":
+    sys.exit(main())