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Author SHA1 Message Date
Frank e703b0c15c frank-primary: restore fp8 3x262144 (bf16 boot fails on a dynamo constraint)
bf16 at 2 x 262144 fails with and without --expert-precise-memory. The real
error (captured from the journal this time, container fixed via journald
rather than podman logs):

  RuntimeError: Worker failed with error 'Constraints violated
  (L['query_start_loc'].size()[0])! You marked it as dynamic but your code
  specialized it to be a constant (3)'

- a torch.compile/dynamo dynamic-shape violation, NOT an OOM. Ruled out a
  stale compile cache: ~/.cache/vllm holds only modelinfos (16K) and each
  podman run gets a fresh container filesystem.

The deltas from the last shape measured serving (fp8 3 x 262144 / MNBT 2048 /
792,069 tokens / 3.02x / arena 6,248) are KV dtype (fp8 -> bf16) and SEQS
(3 -> 2). Restoring the known-good shape; bisect bf16 vs SEQS in a window,
with --enforce-eager as the bypass.
2026-10-01 14:40:17 -07:00
Frank d3d180fd3f frank-primary: drop --expert-precise-memory (boot crash loop with bf16)
NRestarts climbed to 3, each attempt ~6.7 min then 'Deactivated successfully'
(API server drains after an EngineCore fatal error; Restart=always turned the
silent death into a visible loop). The arena is device-resident, so the budget
decides it: weights 6.28 + pool 6.80 (bf16 2 x 262144) + graphs 0.55 + arena
16.65 (precise overhead 5.25) + non-torch 1.45 = 31.73 of 31.86 GiB -> ~0.13
GiB free at boot, and graph capture is what allocates transiently.

Dropping the flag restores the 7.60 GiB default overhead: arena 14.31 GiB,
total ~29.4 GiB, ~2.4 GiB free. bf16 2 x 262144 (Frank's KV change) stays.
The serve script keeps the opt-in flag; the seam now asserts it is ABSENT.
2026-10-01 14:16:47 -07:00
Frank db54fa3af1 frank-small: record 2x262144 verification numbers
Live-verified post-deploy: context_len=262144, max_running_requests=2,
max_total_num_tokens=606208 in the boot log; a 200,000-token prompt
(compaction height is 183,501) prefilled+completed in one request
(97.3 s, ~2,056 tok/s eager); two concurrent 50k requests answered.
Docs-only change.
2026-10-01 14:08:51 -07:00
Frank 8029119b19 frank-large: Q4_K_XL payload + 4 x 163840 sessions (f16 KV)
Frank's call. Payload: ajgazin's abliterated Swift-1.5 UD-Q8_K_XL (29.3 GiB,
SWIFT OPEN LICENSE) -> unsloth/Qwen3.8-27B-GGUF UD-Q4_K_XL (16.35 GiB,
sha256 3f227079...b01e, vanilla/Apache-2.0). NOTE: the endpoint is no longer
uncensored — that was one of the reasons for the Swift payload on 2026-09-28.

New fetcher scripts/download-frank-large-q4.sh (no auth header: repo is public
and ungated; size + sha256 verified after transfer). The speculative drafter
and its fetcher are unchanged.

Shape: --sessions 4 --context 163840 with unquantized KV. gufo exposes no KV
quantization lever (execution_policy.hpp pins kv_cache_storage to kFp16), so
f16 is inherent.

KV arithmetic: f16 KV = 64 KiB/token (16 full-attention layers x 4 KV heads x
256 head_dim x 2 x 2B; the other 48 layers are linear-attention with a
per-sequence fp32 state). 4 x 163840 = 655,360 tokens = 40.0 GiB KV, each
session exactly 10 GiB. Budget ~62 GiB of the 114 GiB GTT.

Seam retargeted (FETCH -> the q4 script, TARGET_STUB, context/sessions pins).
2026-10-01 14:08:50 -07:00
Frank 35e24db7e6 frank-small: reslice to 2 x 262,144 native slots (was 4 x 151,552)
The KV pool stays pinned at 606,208 tokens (card is full: 531 MiB free at
the old shape; autofit's 687,388 would leave 0.53 GB and OOM on the first
long request). 2 x 262,144 = 524,288 leaves ~82k tokens of pool slack.

Motivation: harness compaction. frank-primary's contextWindow 262,144
compacts at 70% = 183,501 tokens, and the compaction request carries a
32,768-token summary budget -> 216,269 must fit ONE frank-small request.
The 151,552 slot window could not hold it; the native window does.

No spec-decode interaction: checkpoint ships zero mtp.* tensors (config
lies), seam keeps every --speculative-* flag away from the engine.
2026-10-01 14:03:25 -07:00
Frank 389b605baf frank-primary: 2 bf16 windows + --expert-precise-memory
Both of Frank's changes at once.

KV is bf16 (--kv-cache-dtype auto) at two full-size windows (2 x 262144).
bf16 measures 13,839 B/token (bf16 3x241664 boot: 11,047,010,304 B -> 798,280
tokens), decomposing as 12,276 attention + 1,563 mamba/side caches vs fp8's
6,138 + 1,563 = 7,701. 524,288 tokens needs 7.256e9 B; pinned at 7.3e9
(~527,500 tokens, 3,206 margin). Pool cost: 5.68 -> 6.76 GiB per rank.

--expert-precise-memory selects the fitted overhead (5.25 GiB) over the default
(7.60 GiB = fitted + compile/graph-capture headroom). It moves only the plan's
 term, so the expert arena goes 6,248 -> ~7,278 slots (~1,025 more) at the
cost of boot-time capture slack. Overhead adds 0.22 GiB/1024 nbt above 4096, so
MNBT 2048 pays nothing.

Seam + docs + AGENTS row + log updated.
2026-10-01 13:52:13 -07:00
Frank 3f1860aa5f docs(log): record e2e 12-crawl flakiness (Plex redirect + transient ERR_ABORTED)
The gate failed twice in the same spec for two different reasons and then passed
33/33 on a manual re-run. Future sessions should re-run before treating the
DEPLOY INCOMPLETE banner as a real fleet fault.
2026-10-01 13:40:24 -07:00
Frank e3c3fad0f1 frank-primary: TimeoutStopSec=180, drop duplicate StartLimitIntervalSec
ExecStop runs 'podman stop -t 120' but the unit never set TimeoutStopSec, so
systemd's 90 s default cut the graceful stop short: journal shows 'Stopping
timed out. Terminating.' then 'Failed with result timeout' on 2026-10-01
13:27:17 — every stop of this unit was logging a failed stop. 180 s covers the
engine's drain with margin, and the seam now guards the RELATIONSHIP
(TimeoutStopSec > the podman grace) rather than a literal.

StartLimitIntervalSec is a [Unit] directive; the copy in [Service] made systemd
log 'Unknown key StartLimitIntervalSec in section Service' on every load. Seam
asserts it appears exactly once and not in [Service].
2026-10-01 13:30:29 -07:00
Frank a1b650aabc frank-primary: 3 full windows, pool at the contract floor, MNBT 2048
Frank's call 2026-10-01: MAXLEN 262144 x SEQS 3 = 786,432 tokens of contract.
Measured fp8 KV costs 7,698 B/token (4-slot boot 8,311,013,376 B -> 1,079,582
tokens; 5-slot boot 10,388,766,720 B -> 1,350,182 tokens), so the pool floor
for the contract is 6.054e9 B. Pinned at 6,100,000,000 (~792k tokens, ~5.9k
margin) so the remaining ~2.2 GiB versus the 4-slot shape goes to the expert
ARENA - the fork sizes its decode-critical expert cache from the remainder
after weights, pool and workspace.

MNBT 2048 (Frank): the arena sweep measured 6,499 slots at every rung <= 4096,
so the larger batch costs the arena nothing.

Seam retargeted (3 seqs / 6.1e9 / MNBT 2048); docs + AGENTS row + log updated,
including the closed DCP investigation.
2026-10-01 13:25:27 -07:00
Frank 6bbcaf3999 docs(frank-primary): parallelism survey — DCP rejected on 2 GPUs (GQA constraint)
--decode-context-parallel-size 2 fails VllmConfig validation at boot:
'Decode context parallelism for GQA/MQA requires --tensor-parallel-size (2) to
be greater than the model's total number of KV heads (2)'. DCP shards KV along
the sequence dimension AFTER KV heads spread across TP ranks, so it needs
TP > num_kv_heads; this model has 2 KV heads, so TP >= 4 — four GPUs, not two.
Recorded with the rest of the survey (PP/DP/EP/multi-node verdicts for this
box), the container-injection requirement for /home/dank/mtp_measure.py
(it imports /bench_iter.py by absolute path and must be copied in), and the
re-measured deployed capacity (1,079,582 tokens / 4.12x).
2026-10-01 13:17:45 -07:00
Frank 148a5f2575 frank-primary: wire --decode-context-parallel-size (opt-in)
DCP is passed only when FRANK_PRIMARY_DCP is set, so the deployed shape is
unchanged. Verified in this fork: DCP reuses the TP ranks when PCP is
disabled (tp % dcp == 0), so TP=2 + DCP=2 fits the two R9700s with no extra
ranks; the flash_attn backend carries DCP support, the 36 linear-attention
layers of this hybrid do not — which is what the A/B window tests.
2026-10-01 13:05:16 -07:00
Frank 667ec2987c frank-small: correct the unit description (no MTP, 4x151k) 2026-10-01 07:06:15 -07:00
Frank 0c5e054fb8 frank-small: SGLang MiMo-V2.6-Distill-Qwen-9B INT8 (qwen3_5 hybrid, RTX 3090)
Replaces llama.cpp Gemma4-12B-QAT (payload + binary retained as rollback).
SGLang in a self-contained python3.12 venv with an extracted CUDA 13.0
nvcc toolchain for the sgl-kernel/flashinfer JIT.

Shape: fp8 KV, pinned 606,208-token pool / 4 x 151,552 slots, bf16 mamba
states pinned at 32 slots (the engine autofills the ssm pool to a fixed
~5.1 GB regardless of dtype), eager prefill (no headroom for graph
capture), no spec decode (the checkpoint ships no mtp.* tensors despite
mtp_num_hidden_layers=1 — NEXTN drafts with an uninitialised 4.24 GiB
ghost at 0% acceptance).

Verified: 83.9 tok/s decode, 170k single prompt, 4 concurrent 54k
requests, vision (in-checkpoint tower), reasoning_content field.
2026-10-01 06:55:48 -07:00
Frank 7da504a651 frank-primary: four full windows + Restart=always (runtime survivability)
Five 262144-token contexts passed every boot gate (KV 1,350,182 / 5.15x) but
left 0 bytes free at runtime: a real client request (995-token prompt,
max_tokens=261149, sampling params straight from models.yml) killed Worker_TP1
with torch.OutOfMemoryError 'Tried to allocate 50.00 MiB ... 0 bytes free'.
Boot is not proof of runtime survivability.

Four slots x 262144 fp8 (KV_BYTES 8,311,013,376/rank) returns ~1.93 GiB per
rank for activations/graph capture.

Unit: Restart=always instead of on-failure — a runtime worker fault makes
vLLM's API server exit clean, so ExecStart returned 0 and on-failure never
fired, leaving the endpoint down until a human noticed. Also
StartLimitIntervalSec=0 and OOMScoreAdjust=-500.
2026-10-01 04:14:25 -07:00
Frank bd311bf591 frank-primary: 5 x full 262144 contexts at fp8 (final shape)
Frank's call after the night ladder: five contexts at the model's full native
262,144 window beat six shortened ones. Six full-length contexts do NOT fit at
any KV dtype (6 x 241664 fp8 asked 10.70 GiB against 9.18 GiB free — the
6-seq graph/activation footprint leaves too little for the pool); 5 x 262144
at fp8 PASSED on the first rung: KV_BYTES 10,388,766,720/rank, measured
'GPU KV cache size: 1,350,182 tokens, Maximum concurrency for 262,144 tokens
per request: 5.15x' (39,462 tokens of margin).

Also documented: the SEQS=3 bf16 max (241,664, KV 732,359 / 3.03x) measured
earlier the same night, and the root-cause read that the 7.2 GiB KV ceiling
law was the MTP4 workspace, not VRAM. Seam and harness (contextWindow 262144)
re-pinned.
2026-10-01 03:52:10 -07:00
Frank 7cab15ac39 frank-primary: max-possible window (241664) + reasoning/tool contract
Night ladder result (Frank's subtract-16k method): 262144 and 245760 both OOM
at CUDA graph capture ('Tried to allocate 76.00 MiB ... 0 bytes free'), 237568
passed (KV 718,606 tokens), and the +4096 bonus step PASSED -> 241664 is max
possible and DEPLOYED at util 0.98 (KV 732,359 tokens / 3.03x concurrency at
241,664-token requests). Util stays 0.98: lowering it shrinks the engine's own
budget instead of buying slack.

Client contract restored (the GLM rollback d91379d dropped all three and the
qwen rollback inherited the gap): --reasoning-parser qwen3 fixes the malformed
thinking block (thinking was landing inline in content with a dangling
</think> and a null reasoning field), --enable-auto-tool-choice with
--tool-call-parser qwen3_xml makes tools work, and
--default-chat-template-kwargs enables enable_thinking + preserve_thinking.

Harness: contextWindow 241664 (compaction gap recomputed), preserve_thinking
moved into chat_template_kwargs.
2026-10-01 03:08:52 -07:00
Frank e8524d4046 frank-primary: util 0.90 — production bf16 boot OOM fix
The 0.98 boot died at KV allocation: torch OOM tried 10.28 GiB (the exact
3x262144 bf16 pool = 11,047,010,304 bytes) with 9.46 GiB free per rank.
The rootless bench probe had booted the same numbers; the root unit's
pinned-expert path holds ~0.8 GiB/rank more. Util 0.90 returns ~2.5 GiB/rank
of workspace with the pool ask unchanged; measured KV capacity law
(798,280 tokens at 11.05e9) unchanged.
2026-10-01 02:12:54 -07:00
Frank c1248d4a5d frank-primary: bf16 no-spec cutover (262144x3, gather 32x64, MNBT 1024)
Overnight redo campaign verdict + Frank's call: the fp8+MTP4 shape is retired
to git tag frank-primary-fp8-mtp-20261001. The new incumbent: KV cache
unquantized (auto), no speculative decode, KV_BYTES 11,047,010,304/rank
(engine-measured 798,280 tokens, 3.05x concurrency at 262,144-token
requests), MNBT 1024, MoE gather 32x64 (+18.7% decode, grows with depth).
Measured at the deployed shape: 39.38/38.79/36.42 tok/s (166/1087/4064 ctx).
Seam re-pinned: the 7.2 GiB/rank KV ceiling was the MTP4 workspace, not VRAM;
spec decode absent by measurement; bf16 trade documented (clean cache +
262k windows for ~14% decode at 4064 ctx).
2026-10-01 01:54:27 -07:00
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@@ -13,7 +13,7 @@ merge absorbed the former `vllmScripts` repo, history preserved).
- **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` (stock llama.cpp on
the gfx1151 iGPU) and `frank-small` (llama.cpp on the RTX 3090). Caddy on
the gfx1151 iGPU) and `frank-small` (SGLang 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 +24,9 @@ merge absorbed the former `vllmScripts` repo, history preserved).
| Target | Service | Runtime | Model | Port |
|--------|---------|---------|-------|------|
| Dankserver | `frank-primary` | tcclaviger RDNA4 vLLM fork (`docker.io/tcclaviger/vllm@sha256:da4029666…`, digest-pinned, plain `podman run`, root systemd unit) | `orcarouter/Qwen3.8-Flash-Next-Uncensored-FP8` (~172.8 GiB, 131 shards), TP=2, expert offload behind a 15.05 GiB / 6,574-slot VRAM LRU arena, MTP4, prefetch OFF, 200000 ctx × 3 seqs, fp8 KV; measured 37.4-40.6 tok/s decode / ~54 % acceptance (the fleet's only endpoint meeting the 35 target). Rolled back 2026-10-01 from the failed GLM/DFlash2 experiment (commit `2339fae` trio) | 7770 |
| Dankclaw | `frank-large` | gufo `gufo-org/gufo` v0.1.1, the Strix Halo engine, BUILT FROM SOURCE (root systemd unit; links the host ROCm 7.2.4) | Swift-1.5-Qwen3.8-27B-Uncensored UD-Q8_K_XL (27B dense, ABLITERATED/uncensored, 29.3 GiB, SWIFT OPEN LICENSE 1.0) with the z-lab DFlash2 Q4_K_M drafter (adaptive block policy, cap 7) on the gfx1151 iGPU (Strix Halo LPDDR, 114 GiB GTT), 262144 ctx single session, greedy, gufo's compiled-in Qwen renderer (NO Qwen-Sharp), text only | 7770 |
| Dankclaw | `frank-small` | mainline llama.cpp master 37b53fd (root systemd unit) | HauhauCS Gemma4-12B-QAT-Uncensored-Balanced Q4_K_M (BF16 mmproj + MTP assistant sidecar, `draft-mtp,ngram-mod`) on the RTX 3090, 1048576 pool / 4 slots of 262,144, q8_0 KV, the fleet's fastest vision endpoint | 7771 |
| Dankserver | `frank-primary` | tcclaviger RDNA4 vLLM fork (`docker.io/tcclaviger/vllm@sha256:da4029666…`, digest-pinned, plain `podman run`, root systemd unit) | `orcarouter/Qwen3.8-Flash-Next-Uncensored-FP8` (~172.8 GiB, 131 shards), TP=2, expert offload automatic (fork plans it), prefetch OFF, **bf16 KV** (`--kv-cache-dtype auto`), **no speculative decode**, MNBT 2048, MoE gather 32×64, **2 seqs × 262144 ctx (the model's full native window)** at KV_BYTES 7,300,000,000/rank (bf16 measures 13,839 B/token), with **`--expert-precise-memory`** — the fitted 5.25 GiB overhead instead of the 7.60 GiB default, which hands the compile/graph-capture headroom to the expert arena (~7,278 slots vs 6,248) — util 0.98, and the client contract wired: `--reasoning-parser qwen3` (thinking in `reasoning`, never inline), `--enable-auto-tool-choice --tool-call-parser qwen3_xml`, default chat-template kwargs `enable_thinking` + `preserve_thinking`. Capacity history: five full-length contexts boot but leave ~0 bytes free at runtime (a real request with `max_tokens=261149` killed the worker: `Tried to allocate 50.00 MiB ... 0 bytes free`); six never fit (6×241664 asked 10.70 GiB vs 9.18 GiB free). DCP cannot help here — it requires TP > the model's 2 KV heads, i.e. four GPUs. fp8+MTP4 shape restorable from git tag `frank-primary-fp8-mtp-20261001` | 7770 |
| Dankclaw | `frank-large` | gufo `gufo-org/gufo` v0.1.1, the Strix Halo engine, BUILT FROM SOURCE (root systemd unit; links the host ROCm 7.2.4) | `unsloth/Qwen3.8-27B-GGUF` **UD-Q4_K_XL** (27B dense, **vanilla — no longer abliterated**, 16.35 GiB, Apache-2.0) with the z-lab DFlash2 Q4_K_M drafter (adaptive block policy, cap 7) on the gfx1151 iGPU (Strix Halo LPDDR, 114 GiB GTT), **4 sessions x 163840 ctx, unquantized (f16) KV** — gufo has no KV-quant lever — greedy, gufo's compiled-in Qwen renderer (NO Qwen-Sharp), text only. Swapped 2026-10-01 from ajgazin's abliterated Swift-1.5 UD-Q8_K_XL (29.3 GiB): ~13 GiB less weights is what funds four f16 sessions, at the cost of the uncensored behaviour | 7770 |
| Dankclaw | `frank-small` | SGLang in a self-contained python3.12 venv (root systemd unit; the venv carries its own CUDA 13 stack — see the runbook) | letechlead MiMo-V2.6-Distill-Qwen-9B-INT8-W8A16-AutoRound (qwen3_5 hybrid, 9B dense, 12.0 GiB, INT8 W8A16 AutoRound, in-checkpoint vision tower, NO MTP weights shipped so no spec decode) on the RTX 3090, fp8 KV, pinned 606,208-token pool / 2 slots of 262,144 (native window; 2026-10-01 reslice from 4 x 151,552 for compaction headroom), bf16 mamba states, eager prefill, 83.9 tok/s decode | 7771 |
Retired endpoints (`frank-npu`, and every prior runtime) are in
the [runbook index](#runbook-index). The full swap history lives in
@@ -243,7 +243,7 @@ merely wedged kernel usually still answers ARP.
1. Stop and mask (self-healing would restart it):
- Dankclaw `frank-large` (root unit, gufo on the iGPU):
`sudo systemctl stop frank-large && sudo systemctl mask frank-large`
- Dankclaw `frank-small` (root unit, llama.cpp on the 3090):
- Dankclaw `frank-small` (root unit, SGLang on the 3090):
`sudo systemctl stop frank-small && sudo systemctl mask frank-small`
- Dankserver `frank-primary` (root unit, tcclaviger vLLM on the 2x R9700):
`sudo systemctl stop frank-primary && sudo systemctl mask frank-primary`
@@ -277,19 +277,20 @@ 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 2026-09-26 both `frank-small` and `frank-primary` accept images
of 2026-10-01 both `frank-small` and `frank-primary` accept images
(`input: [text, image]`) — frank-primary loads the BF16 mmproj explicitly
(this build never autoloads projectors); `frank-large` remains text-only
because its stock llama.cpp deployment loads no
vision projector (the mmproj is not loaded). Note also that
the reasoning channel differs by runtime: llama.cpp endpoints emit
`reasoning_content`, vLLM emits `reasoning` — academic since the
2026-09-26 swap, as every endpoint in the fleet is llama.cpp now.
(this build never autoloads projectors), and frank-small's MiMo payload
bakes its vision tower INTO the checkpoint (no projector file at all);
`frank-large` remains text-only because its gufo deployment loads no
vision projector. Note also that
the reasoning channel differs by runtime: llama.cpp AND SGLang (qwen3
parser, live-verified) emit `reasoning_content`, vLLM emits `reasoning` —
models.yml sets `reasoningContentField` per endpoint to match.
There is **no audio**
input anywhere in the fleet except frank-small: that capability left with the
FLM NPU endpoint on 2026-09-11 and returned on 2026-09-17 with the Gemma4
projector's audio encoder (frank-small transcribes WAV verbatim even though
`audio` is omitted from its `input` list — OMP's schema rejects it).
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).
### frank-large — gufo, Swift-1.5-Qwen3.8-27B-Uncensored UD-Q8_K_XL (Dankclaw, ACTIVE)
@@ -397,31 +398,55 @@ no longer a one-minute flip. **Engine** —
Qwen-Sharp back. The DFlash2 drafter was never reclaimed and still lives in
`Qwen3.8-27B-UD-Q8_K_XL/`.
### frank-small — llama.cpp on the RTX 3090 (Dankclaw, ACTIVE)
### frank-small — SGLang on the RTX 3090 (Dankclaw, ACTIVE)
Mainline llama.cpp master `37b53fd` (CUDA build with
`-DGGML_CUDA_FA_ALL_QUANTS=ON`) as a **root systemd unit** (repo
`scripts/frank-small.service`, `relink_unit`ed into `/etc/systemd/system/`),
serving `HauhauCS/Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced` at Q4_K_M.
The MTP head is a SEPARATE assistant file (`mtp-gemma-4-12B-it.gguf`, 4
nextn layers) loaded via `--model-draft`; the draftless **ngram-mod**
matcher chains behind it in the same `--spec-type` value. BF16 mmproj,
port 7771, q8_0 KV, `CTX_SIZE=1048576` / `PARALLEL=4`
(four FULL 262,144-token slots — the measured card ceiling), batch
**8192/1024**, greedy default. Deployed flags are in
`scripts/frank-small.env`; the serve script refuses to start if the
weights, the projector, the sidecar or the binary are missing.
SGLang (latest) in a **self-contained python3.12 venv**
(`/home/dank/GitPackages/sglang-cu128/`, torch 2.13.0+cu130) as a **root
systemd unit** (repo `scripts/frank-small.service`, `relink_unit`ed into
`/etc/systemd/system/`), serving
`letechlead/MiMo-V2.6-Distill-Qwen-9B-INT8-W8A16-AutoRound` (9B dense
qwen3_5 hybrid — 8 full-attention + 24 Gated DeltaNet layers — INT8 W8A16
AutoRound, 12.0 GiB, vision tower baked into the checkpoint). Port 7771.
Verified at deploy (2026-09-17): `/v1/models` reports `frank-small`; a
chat completion returns content plus `reasoning_content`; a tool call
returns `tool_calls`; an image request is answered from the projector;
an `input_audio` WAV transcribes verbatim. Post-tuning live numbers at
max length: pp@254k ~965 t/s, tg@253k 226–302 t/s with ~94% draft
acceptance; idle 23,300 MiB of 24,576. The throughput sweep (and why
ubatch 2048 OOMs the draft's pp buffer, and why draft depth 4 + poll
100 is WORSE at long ctx) is tabled in the runbook.
Runbook: `serverAppConfigs-docs/LLM/frank-small-gemma4-12b.md`.
Rollback: [[frank-small-qwen38-gsq-rco]].
**The shape is memory-pinned, and the sharp edge is the mamba pool.** The
DeltaNet ssm state pool autofills to a fixed ~5.1 GB budget *regardless of
dtype* (fp32 at 110 slots, bf16 at 217 — same 5.1 GB), so both dials are
pinned: `--mamba-ssm-dtype bfloat16 --max-mamba-cache-size 32` (795 MiB).
The KV pool is then **pinned at 606,208 tokens** (`--max-total-tokens`) —
the engine's autofit picks 687,388 and leaves 0.53 GB, which Triton's
deferred kernel loads eat and the first long request OOMs on. Two
262,144-token slots at the model's NATIVE window (2026-10-01 reslice from
4 x 151,552: 2 x 262,144 = 524,288 leaves ~82k tokens of pool slack, and
a compaction request — frank-primary's trigger is 183,501 tokens plus a
32,768-token summary budget = 216,269 — now fits ONE request); a single
request may grow to the whole pool. Prefill runs **eager**
(`--disable-prefill-cuda-graph`) — there is no headroom for capture;
decode graphs are on.
**No speculative decode — a checkpoint fact.** `text_config` declares
`mtp_num_hidden_layers: 1`, but the shipped safetensors (base BF16 and this
INT8 conversion alike) carry zero `mtp.*` tensors; NEXTN would draft with
an uninitialised 4.24 GiB ghost model at 0% acceptance. The seam gates
that no `--speculative-*` flag reaches the engine.
**The venv carries a CUDA 13.0 nvcc extracted from debs** (system nvcc is
12.4) so the sgl-kernel/flashinfer JIT compiles for sm86; three local
patches ride in the tree (GCC-16 shim, CCCL symlink, rsqrt noexcept).
Details in the runbook.
Verified at deploy (2026-10-01): `/v1/models` reports `frank-small`;
chat returns content plus `reasoning_content` (SGLang's qwen3 parser uses
llama.cpp's field name); a red-square image answers "Red"
(`image_tokens: 64`). At the 4 x 151,552 shape: 4 concurrent 54k-token
requests answered; a 170,019-token prompt prefilled in 50.5 s (~3,370 t/s
eager). At the 2 x 262,144 shape (reslice, same day): boot flags read
`context_len=262144 max_running_requests=2 max_total_num_tokens=606208`;
a 200,000-token prompt — well past frank-primary's 183,501 compaction
trigger — prefilled and completed in ONE request (97.3 s wall, ~2,056
tok/s eager); two concurrent 50k-token requests both answered. Decode
**83.9 tok/s**.
Runbook: `serverAppConfigs-docs/LLM/frank-small-sglang-mimo-v26.md`.
Rollback: [[frank-small-gemma4-12b]] (payload and binary intact on disk).
### frank-primary — tcclaviger vLLM, Qwen3.8-Flash-Next FP8 + MTP4 (Dankserver, ACTIVE)
@@ -803,7 +828,7 @@ Active:
| Service | Runbook |
|---------|---------|
| frank-large (gufo Qwen3.8-27B UD-Q8_K_XL, Dankclaw) | `serverAppConfigs-docs/LLM/frank-large-gufo-qwen38-27b.md` |
| frank-small (llama.cpp Gemma4-12B QAT, Dankclaw) | `serverAppConfigs-docs/LLM/frank-small-gemma4-12b.md` |
| frank-small (SGLang MiMo-V2.6 INT8, Dankclaw) | `serverAppConfigs-docs/LLM/frank-small-sglang-mimo-v26.md` |
| frank-primary (tcclaviger vLLM, Qwen3.8-Flash-Next FP8 + MTP4, Dankserver) | `serverAppConfigs-docs/LLM/dankserver-qwen38-fp8-expert-offload-tuning.md` |
| Dankclaw kernel posture (`amd_iommu=off`) | `serverAppConfigs-docs/LLM/dankclaw-iommu-translation-off.md` |
| Deployment flow + incidents | `serverAppConfigs-docs/LLM/deployment.md` |
@@ -826,6 +851,7 @@ Retired (rollback targets and history):
| 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` |
| 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` |
+25 -9
View File
@@ -1177,23 +1177,39 @@ deploy_llm_large() {
wait_for_health frank-large http://127.0.0.1:7770/health 1200
}
# deploy_llm_small — frank-small is mainline llama.cpp on the RTX 3090, as a
# ROOT unit: the runtime is a native CUDA binary, so there is no container
# image to install and no generated unit to avoid. relink_unit points
# /etc/systemd/system/frank-small.service at the repo file and boot persistence
# is that unit's [Install] section.
# deploy_llm_small — frank-small is SGLang (python3.12 venv) on the RTX 3090,
# as a ROOT unit: the runtime is a self-contained venv, so there is no
# container image to install and no generated unit to avoid. relink_unit
# points /etc/systemd/system/frank-small.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="${LLM_SMALL_MODEL:-/home/dank/models/Gemma4-12B-QAT/Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced-Q4_K_M.gguf}"
LLM_SMALL_MODEL_DIR="${LLM_SMALL_MODEL_DIR:-/home/dank/models/MiMo-V2.6-Distill-Qwen-9B-INT8-W8A16-AutoRound}"
LLM_SMALL_RUNTIME="${LLM_SMALL_RUNTIME:-/home/dank/GitPackages/sglang-cu128/bin/sglang}"
deploy_llm_small() {
if [[ ! -f "$LLM_SMALL_MODEL" ]]; then
echo "ERROR: model absent at $LLM_SMALL_MODEL" >&2
echo "frank-small: fetch HauhauCS/Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced (Q4_K_M, the mmproj and the MTP sidecar) first;" >&2
# Refuse rather than restart-loop: a unit whose runtime or payload is
# missing never becomes healthy, and a green deploy would leave the
# endpoint dark with nothing in the log to say why.
if [[ ! -x "$LLM_SMALL_RUNTIME" ]]; then
echo "ERROR: SGLang runtime absent at $LLM_SMALL_RUNTIME" >&2
echo "frank-small: build the venv (python3.12 -m venv /home/dank/GitPackages/sglang-cu128" >&2
echo "frank-small: and pip install 'sglang[all]' into it) first." >&2
return 1
fi
if [[ ! -f "$LLM_SMALL_MODEL_DIR/model.safetensors.index.json" ]]; then
echo "ERROR: payload index absent at $LLM_SMALL_MODEL_DIR" >&2
echo "frank-small: run scripts/download-frank-small.sh first;" >&2
echo "frank-small: refusing to start a unit that cannot load." >&2
return 1
fi
local count
count="$(find "$LLM_SMALL_MODEL_DIR" -maxdepth 1 -name 'model-*-of-*.safetensors' | wc -l)"
if [[ "$count" -ne 8 ]]; then
echo "ERROR: payload shard count wrong: $LLM_SMALL_MODEL_DIR (found $count, want 8)" >&2
return 1
fi
relink_unit frank-small
run_privileged systemctl daemon-reload
run_privileged systemctl enable frank-small.service
+76
View File
@@ -0,0 +1,76 @@
#!/usr/bin/env bash
# Download the Q4_K_XL frank-large 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
#
# 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:
# the repo is public and ungated (gated: false), and a token on the curl
# command line is world-readable via /proc/<pid>/cmdline. If this ever needs
# a token, put it in a mode-600 file and pass it with `curl -K`.
#
# Layout after a successful run (MODEL_DIR):
# Qwen3.8-27B-UD-Q4_K_XL.gguf 17559178144 (16.35 GiB)
#
# WHY Q4 AND NOT THE Q8 SWIFT PAYLOAD: this is the vanilla (non-abliterated)
# Qwen3.8-27B at UD-Q4_K_XL, ~13 GiB smaller than the Swift UD-Q8_K_XL. Every
# GiB of weights saved is a GiB of f16 KV the endpoint can hold instead: the
# KV costs 64 KiB/token (16 full-attention layers x 4 KV heads x 256 head_dim
# 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
# 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 —
# spec decode here is the block-diffusion drafter, not MTP.
set -euo pipefail
MODEL_DIR="/home/dank/models/Qwen3.8-27B-UD-Q4_K_XL"
REL="Qwen3.8-27B-UD-Q4_K_XL.gguf"
SIZE=17559178144
SHA=3f227079003add2511437e5b1e94812e363385225bf6a9b47b0054a72bc8b01e
URL="https://huggingface.co/unsloth/Qwen3.8-27B-GGUF/resolve/main/${REL}"
mode="download"
[[ "${1:-}" == "--verify-only" ]] && mode="verify"
if [[ "$mode" == "download" ]]; then
mkdir -p "$MODEL_DIR"
if [[ -s "$MODEL_DIR/$REL" ]]; then
echo "already present: $MODEL_DIR/$REL"
else
echo "fetching $REL (17559178144 bytes) — this is ~16.4 GiB"
# -f so an HTTP error is a failure, not a 153-byte "artifact".
# -C - so an interrupted run resumes instead of restarting.
curl -fL -C - --retry 5 --retry-delay 3 -o "$MODEL_DIR/$REL" "$URL"
fi
fi
echo "verifying $MODEL_DIR against declared size + sha256"
python3 - "$MODEL_DIR" "$REL" "$SIZE" "$SHA" <<'PY'
import hashlib, os, sys
model_dir, rel, size, sha = sys.argv[1], sys.argv[2], int(sys.argv[3]), sys.argv[4]
dest = os.path.join(model_dir, rel)
if not os.path.isfile(dest):
print(f" MISSING {rel}")
sys.exit(1)
actual = os.path.getsize(dest)
if actual != size:
print(f" SIZE MISMATCH {rel}: {actual} != {size}")
sys.exit(1)
h = hashlib.sha256()
with open(dest, "rb") as f:
for chunk in iter(lambda: f.read(1 << 24), b""):
h.update(chunk)
if h.hexdigest() != sha:
print(f" SHA256 MISMATCH {rel}: {h.hexdigest()}")
sys.exit(1)
print(f" OK {rel} ({actual} bytes, sha256 matches the Hub LFS oid)")
PY
echo "Q4_K_XL payload complete: $MODEL_DIR"
+93
View File
@@ -0,0 +1,93 @@
#!/usr/bin/env bash
# Download MiMo-V2.6-Distill-Qwen-9B-INT8-W8A16-AutoRound for frank-small
# (SGLang, RTX 3090). Public repo — no auth header on the command line.
#
# Per-file FRESH downloads, no resume: `curl -C -` once produced a 213 MB
# oversized file on a 31 GiB payload; a fresh -f fetch plus size+sha256 is
# the house rule.
#
# Usage:
# scripts/download-frank-small.sh [DEST_DIR] [--verify-only]
#
# LFS shards are verified against the Hub LFS sha256; non-LFS text files
# against their declared byte size. Idempotent: complete files are skipped.
set -euo pipefail
REPO="letechlead/MiMo-V2.6-Distill-Qwen-9B-INT8-W8A16-AutoRound"
BASE="https://huggingface.co/${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/MiMo-V2.6-Distill-Qwen-9B-INT8-W8A16-AutoRound}"
# name bytes sha256(- = non-LFS, size-only check)
FILES=(
"model-00001-of-00008.safetensors 2946296312 ddb6117c04cb6feaf7c265e5d75efadf21949037d73253a8e4521d40e164366d"
"model-00002-of-00008.safetensors 1402134792 2dc78d55d1d33d7b3b21dd6f8b4b817b62c2fb1376e6448b322428798c10e257"
"model-00003-of-00008.safetensors 1427365904 5c797d14e345309d67c78306b9de4aa01a21dbd92dd98e40b0ad69b2900e9203"
"model-00004-of-00008.safetensors 1420041856 7402f852e2c7a24ebf4694b98a220e71dfb2c93ba3776272cf2acfc65acd8126"
"model-00005-of-00008.safetensors 1410655648 991cbf2eda2ff91fc3ffbb15591d7fcac340fb10d9c33bd3da20010e2f3f4090"
"model-00006-of-00008.safetensors 1427627856 efc42448054cfb5e3061e154ba4539204088ce95176d689a95b58de885ef7eeb"
"model-00007-of-00008.safetensors 2035442408 75a101fc71ae6f2e1f5c4816f711d62cf1d7a0e02ef6e5182361b8c11e72b626"
"model-00008-of-00008.safetensors 822153664 0fb90cb50e2d336fbad58bd4c01880eeddbf537c1dca1cf0ae291195d5efbb4b"
"tokenizer.json 19989325 06b9509352d2af50381ab2247e083b80d32d5c0aba91c272ca9ff729b6a0e523"
"model.safetensors.index.json 106278 -"
"config.json 4608 -"
"generation_config.json 161 -"
"quantization_config.json 1654 -"
"chat_template.jinja 3916 -"
"tokenizer_config.json 1168 -"
"preprocessor_config.json 443 -"
"processor_config.json 1191 -"
"README.md 8448 -"
)
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")" == "$size" ]]; then
if [[ "$sha" == "-" ]] || 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"
# no -C resume; -f + --fail-with-body so an HTTP error is not a success
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") != $size)"
status=1
continue
fi
if [[ "$sha" != "-" ]] && ! 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"
+29 -11
View File
@@ -8,14 +8,20 @@
# runtime reads those bare (the 2026-08-13 TEMP incident). HOST is the one
# exception because the serve script itself consumes it for --host.
# The target payload (scripts/download-frank-large-swift.sh): the serve
# script refuses to start without the main GGUF and the DFlash2 drafter.
# Swapped in from unsloth/Qwen3.8-27B-GGUF:UD-Q8_K_XL on 2026-09-28. The two
# are structurally interchangeable for gufo (same qwen35 architecture, the
# same 866 tensors in the same order, the same per-tensor Q8_0/F32/BF16
# layout, the same MTP head), so only this path changed.
MODEL_DIR=/home/dank/models/Swift-1.5-Qwen3.8-27B-Uncensored-MTP-UD-Q8_K_XL
MODEL_FILE=/home/dank/models/Swift-1.5-Qwen3.8-27B-Uncensored-MTP-UD-Q8_K_XL/Swift-1.5-Qwen3.8-27B-Uncensored-Dynamic-MTP-UD-Q8_K_XL.gguf
# The target payload (scripts/download-frank-large-q4.sh): the serve script
# refuses to start without the main GGUF and the DFlash2 drafter.
#
# 2026-10-01 swap (Frank): unsloth/Qwen3.8-27B-GGUF:UD-Q4_K_XL, 16.35 GiB,
# replacing ajgazin's abliterated Swift-1.5 UD-Q8_K_XL (29.3 GiB). Two
# consequences worth knowing at a glance:
# * this is the VANILLA (non-abliterated) Qwen3.8-27B — the endpoint is no
# longer uncensored, which was one of the reasons the Swift payload was
# chosen on 2026-09-28;
# * ~13 GiB of weights became available for KV, which is what makes four
# full-sized f16 sessions fit.
# gufo needs no template for either: its Qwen renderer is compiled in.
MODEL_DIR=/home/dank/models/Qwen3.8-27B-UD-Q4_K_XL
MODEL_FILE=/home/dank/models/Qwen3.8-27B-UD-Q4_K_XL/Qwen3.8-27B-UD-Q4_K_XL.gguf
# The DFlash2 drafter is UNCHANGED by the model swap and still lives beside
# the previous target, so it carries its own directory. It has a sliding
@@ -32,9 +38,21 @@ ALIAS=frank-large
HOST=0.0.0.0
PORT=7770
# One session, full 262144 context (the model's native window).
CONTEXT_SIZE=262144
SESSIONS=1
# Four sessions, 163840 context each (Frank, 2026-10-01: "4x 160k"). The
# context is per session and the KV is UNQUANTIZED (f16) — gufo has no KV
# quantization lever at all (execution_policy.hpp pins kv_cache_storage to
# kFp16), so "unquantized" is inherent rather than configured.
#
# The arithmetic that makes this fit: f16 KV costs 64 KiB/token on this model
# (16 full-attention layers x 4 KV heads x 256 head_dim x 2 (K,V) x 2 bytes;
# the other 48 layers are linear-attention with a per-SEQUENCE fp32 state of
# ~144 MiB, not a per-token cache). 4 x 163840 = 655,360 tokens = 40.0 GiB of
# KV, and each session's 163,840 tokens is exactly 10 GiB. Budget: weights
# 16.35 + KV 40.0 + drafter 1.07 + linear state 0.56 + runtime ~4 = ~62 GiB
# against the 114 GiB GTT — roughly 50 GiB of headroom, so the session count
# or the per-session context can both grow from here.
CONTEXT_SIZE=163840
SESSIONS=4
# DFlash2 spec decode (a block-diffusion drafter). gufo sizes the draft
# block itself; DRAFT_TOKENS caps the proposals per step (gufo's default is
+84 -28
View File
@@ -1,37 +1,44 @@
# frank-primary.env — tcclaviger RDNA4 vLLM production config (dankserver :7770).
#
# 2026-09-29 cutover from the R9V radiance-vLLM fork (its launcher/shim/state
# machinery is retired; /home/dank/r9v-state/{q8xl,uncensored} stay on disk as
# the rollback target, and git tag frank-primary-r9v-q8-20260929 is the last
# pre-cutover commit). The engine is the tcclaviger RDNA4 vLLM fork — the same
# digest-pinned image the 2026-09-29 tuning campaign measured — serving
# orcarouter/Qwen3.8-Flash-Next-Uncensored-FP8 (~172.8 GiB, 131 shards) with
# the MTP4 drafter on the two R9700s.
# 2026-10-01 cutover to the BF16-KV no-spec incumbent (the overnight redo
# campaign's verdict, Frank's call): same digest-pinned engine and payload as
# the 2026-09-29 cutover, but the KV cache is UNQUANTIZED (auto = bf16) and
# speculative decode is GONE. Git tag frank-primary-fp8-mtp-20261001 is the
# last pre-cutover commit; the old shape (fp8 KV + MTP4) is in history and
# restorable from the tag.
#
# Every number here was QUALIFIED by boot probe on 2026-09-29 (not inherited):
# * MAXLEN 200000 x SEQS 3 (600k total) at KV q8/q8 fits with headroom:
# the engine measured "GPU KV cache size: 729,545 tokens; Maximum
# concurrency for 200,000 tokens per request: 3.65x" at KV_BYTES 7.2 GiB
# per rank. KV_BYTES is PER RANK — sizing it to the global requirement
# OOMs the worker (measured twice: 16 GiB and 9 GiB both die with ~7.5 GiB
# free; 7.2 GiB boots).
# * --kv-cache-dtype fp8 is the fleet's q8/q8 KV ask (e4m3 for BOTH K and V
# — the stock flag quantizes them together, which is exactly what was
# requested here). Accepted by the attention path; qualified with a
# completion probe.
# Every number here was QUALIFIED by boot probe on 2026-10-01 (not inherited):
# * MAXLEN 241664 x SEQS 3 (724,992 tokens) at bf16 KV is the DEPLOYED
# shape (2026-10-01 night ladder): KV_BYTES 10,184,000,000 PER RANK,
# engine measured "KV cache size: 732,359 tokens; Maximum concurrency
# for 241,664 tokens per request: 3.03x". 262144 and 245760 both OOMed
# at graph capture (76 MiB short / 0 bytes free); 237568 passed at
# 718,606 tokens and the +4096 bonus step passed and won.
# * KV_BYTES is PER RANK. The old "7.2 GiB ceiling, 9/16 GiB OOM" law was
# the MTP4 WORKSPACE: the spec-era pool measured 729,545 tokens because
# the drafter reserved ~2.6 GiB/rank beside the pool. No-spec bf16 takes
# 11.05 GiB/rank and boots clean — the ceiling was spec's, not VRAM's.
# * bf16 KV doubles the attention-KV bytes/token (measured 14,047 vs
# 7,926) and costs ~14% decode vs fp8 at 4064 ctx (49.25 -> 36.42 with
# the gather win) — traded deliberately for clean cache + 262k windows.
# * GATHER 32x64 is the night's biggest lever: R4D_LRU_GATHER_CHUNKS=32 /
# R4D_LRU_GATHER_LANES=64 measured +18.7% decode vs default geometry,
# and the win grows with depth (39.5@166 -> 54.1@1087 -> 49.3@4064 fp8
# era). Do not drop it.
# * MNBT 1024 is Frank's lock: MNBT 512 doubles TTFT at 4064 ctx (2.46 s
# vs 1.36 s); 1024-4096 are interchangeable on decode; 12288 costs 2.5%
# and arena. 1024 keeps the workspace floor so the arena stays max.
# * PREFETCH IS ABSENT BY LAW: expert-cache telemetry measured the
# prefetcher at 36% precision (36,720 slabs prefetched, 13,369 served) —
# roughly half the gather traffic was waste; prefetch off is the tuned
# incumbent and the +40-51% decode came from deleting the flag. Never
# re-add --expert-prefetch without a fresh A/B.
# roughly half the gather traffic was waste. Never re-add
# --expert-prefetch without a fresh A/B.
# * TunableOp stays OFF: CLAV_TUNABLEOP_SWEEP silently skips under expert
# offload unless CLAV_TUNABLEOP_WITH_OFFLOAD=1, and forcing it corrupts
# numerics (repetition loops, early halts, invalid measurements).
# Decode at the tuned shape: 40.57/37.44/37.57 tok/s (166/1087/4064 ctx) at
# the 32k window; 42.94/34.55/36.09 at this 200k shape (arena 6,032 slots).
# numerics.
#
# HIP reads bare env vars TEMP, HOST, GPU_MAX_HEAP_SIZE — every key here is
# prefixed FRANK_PRIMARY_ so none can leak.
#
# --- runtime ----------------------------------------------------------------
# Digest-pinned: the floating :latest tag moved once already. Local alias
@@ -52,10 +59,59 @@ FRANK_PRIMARY_PUBLISH=7770:7770
# hoc experiment identity (both hold the GPUs / name registrations).
FRANK_PRIMARY_LEGACY_CONTAINERS="frank-primary-r9v qwen-fp8"
# --- qualified engine shape ---------------------------------------------------
FRANK_PRIMARY_MAXLEN=200000
# --- qualified engine shape (2026-10-01, RESTORED KNOWN-GOOD: fp8 3 windows) ---
# bf16 at 2 x 262144 did NOT stay up: with and without --expert-precise-memory
# the boot failed (`Engine core initialization failed`, NRestarts climbing).
# The last shape measured serving was fp8 3 x 262144 / MNBT 2048 / KV 6.1e9
# (KV 792,069 tokens, 3.02x, arena 6,248, ~3.6 GiB free) and is restored here
# while the bf16 path is investigated in a window (see log.md 2026-10-01).
# Candidate next test: bf16 with SEQS=3 to isolate the KV dtype from the
# sequence count, and/or --enforce-eager to bypass the dynamo constraint path.
# SEQS 2 x MAXLEN 262144 at BF16 KV (Frank's call, 2026-10-01): two contexts of
# the model's FULL native window with UNQUANTIZED KV, plus
# --expert-precise-memory to hand the arena the compile/graph-capture headroom.
# Pool: bf16 costs 13,839 B/token (measured: 11,047,010,304 B -> 798,280 tokens
# on the 3x241664 bf16 boot; decomposes as 12,276 attention + 1,563 mamba/side
# caches, against fp8's 6,138 + 1,563 = 7,701). 2 x 262144 = 524,288 tokens
# -> 7.256e9 B floor, pinned at 7,300,000,000 (~527,500 tokens, 3,206 margin).
# Budget (per rank): 31.22 GiB total; non-expert weights 6.28, graphs 0.55,
# non-torch ~1.45, pool 6.76 -> ~29.35 used, ~2.5 GiB free (measured basis:
# the fp8 3-window shape used 28.27 and left 3.59).
# PRECISE MEMORY: DROPPED 2026-10-01 after it crashed the boot in combination
# with bf16. The flag selects the fitted 5.25 GiB overhead instead of the
# 7.60 GiB default, moving the plan's `room` and therefore the arena
# (6,248 -> ~7,278 slots). But the arena is DEVICE-resident, and the budget
# for this shape does not have 2.35 GiB to spare:
# weights 6.28 + pool 6.80 (bf16 2 x 262144) + graphs 0.55 + arena 16.65
# + non-torch ~1.45 = 31.73 of 31.86 GiB => ~0.13 GiB free at boot
# measured as a CrashLoop: every attempt reached graph capture, the engine
# exited cleanly, systemd restarted it (NRestarts=3 at ~6.7 min each).
# With the default overhead the arena is 14.31 GiB and the same shape totals
# ~29.4 GiB, leaving ~2.4 GiB for capture. Re-enable the flag only with a
# pool/context reduction that pays for it.
# MNBT 2048 (Frank): the overhead formula only adds bytes above nbt 4096, so
# 2048 pays nothing, and the arena sweep measured the same ceiling <= 4096.
FRANK_PRIMARY_MAXLEN=262144
FRANK_PRIMARY_SEQS=3
FRANK_PRIMARY_KV_BYTES=7730934784
FRANK_PRIMARY_KV_BYTES=6100000000
FRANK_PRIMARY_KV_DTYPE=fp8
FRANK_PRIMARY_SPEC=4
FRANK_PRIMARY_MNBT=2048
FRANK_PRIMARY_GATHER_CHUNKS=32
FRANK_PRIMARY_GATHER_LANES=64
FRANK_PRIMARY_UTIL=0.98
# --- client contract: reasoning split, tools, preserve_thinking ----------------
# Without --reasoning-parser the engine leaves the thinking text INLINE in
# `content` with a dangling `</think>` and a null `reasoning` field (measured
# 2026-10-01: content = 'We need answer...Brief.\n</think>\n\n391') — the
# malformed thinking block clients choke on. The qwen3 parser splits it
# properly. The GLM rollback (d91379d) had dropped all three of these; the
# working values are the ones ecaad36 shipped for this model.
FRANK_PRIMARY_REASONING_PARSER=qwen3
# Tools: --enable-auto-tool-choice + the qwen3_xml parser is what makes
# tool_calls work here (without it, tool_choice auto returns 400).
FRANK_PRIMARY_TOOL_PARSER=qwen3_xml
# preserve_thinking keeps prior thinking blocks in the rendered prompt across
# turns; enable_thinking makes thinking the server-side default. Verified the
# payload's tokenizer_config template consumes both keys.
FRANK_PRIMARY_CHAT_TEMPLATE_KWARGS='{"enable_thinking": true, "preserve_thinking": true}'
+23 -3
View File
@@ -8,8 +8,10 @@
#
# Same port, same served alias; the harness models.yml id is unchanged.
# The serve script drives `podman run` directly (the image entrypoint execs
# `vllm serve`) and then waits on the container, so a crashed engine is a
# nonzero ExecStart and Restart=on-failure is real.
# `vllm serve`) and then waits on the container. NOTE: that wait can return
# 0 even when the engine died mid-request (vLLM's API server drains and
# exits clean on a worker fault), which is why the restart policy is
# `always` — see the [Service] note.
#
# WHY A ROOT UNIT (not a rootless quadlet): the tiered-expert shape pins tens
# of GiB of host RAM (the expert host slabs, ~20.5 GiB per rank of pinned
@@ -23,6 +25,9 @@
Description=frank-primary — tcclaviger vLLM Qwen3.8-Flash-Next-Uncensored-FP8 on 2x 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
@@ -39,8 +44,23 @@ ExecStop=/usr/bin/podman stop -t 120 frank-primary-qwen
# Boot cost: FP8 payload page-in plus torch compile/graph capture —
# ~15 min cold (measured 2026-09-29), faster warm.
TimeoutStartSec=1800
Restart=on-failure
# Restart=always, NOT on-failure (measured 2026-10-01): a runtime
# torch.OutOfMemoryError kills the engine while vLLM's API server still
# exits 0, so ExecStart returned clean, systemd logged "Deactivated
# successfully", and on-failure NEVER fired — the endpoint stayed down until
# a human noticed. `always` restarts on any container death; an explicit
# `systemctl stop` still wins (systemd does not restart a unit the operator
# stopped), 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 for the engine's own shutdown.
TimeoutStopSec=180
# The engine pins tens of GiB of host RAM (expert host slabs); it is the
# last process on this host that should be chosen by the kernel OOM killer.
OOMScoreAdjust=-500
[Install]
WantedBy=multi-user.target
+66 -98
View File
@@ -1,46 +1,38 @@
# Tunables for frank-small (HauhauCS/Gemma4-12B-QAT-Uncensored-HauhauCS-
# Balanced, Q4_K_M, plus the BF16 vision projector and the separate MTP
# sidecar) on mainline llama.cpp, Dankclaw's RTX 3090, since 2026-09-17.
# Tunables for frank-small (letechlead/MiMo-V2.6-Distill-Qwen-9B-INT8-
# W8A16-AutoRound, qwen3_5 hybrid, in-checkpoint vision) on SGLang,
# Dankclaw's RTX 3090, since 2026-10-01.
#
# Runtime: llama.cpp master 37b53fd, CUDA build for sm_86:
# cmake -B build-cuda -DCMAKE_BUILD_TYPE=Release -DGGML_NATIVE=ON \
# -DGGML_CUDA=ON -DCMAKE_CUDA_ARCHITECTURES=86 -DGGML_CUDA_FA_ALL_QUANTS=ON
# cmake --build build-cuda --target llama-server -j
# GGML_CUDA_FA_ALL_QUANTS is ON: this service runs q8_0 KV with flash
# attention, and without the flag quantized-KV prefill collapses ~12x on
# CUDA (see the CUDA lesson in AGENTS.md).
# Runtime: SGLang in a python3.12 venv (pip "sglang[all]"):
# python3.12 -m venv /home/dank/GitPackages/sglang-cu128
# /home/dank/GitPackages/sglang-cu128/bin/pip install "sglang[all]"
# The venv carries its own CUDA torch + sgl-kernel + flashinfer; it is
# self-contained and does not touch the host Python (3.14) or the ROCm
# stack that serves frank-large.
#
# Model: HauhauCS/Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced at Q4_K_M
# (6.87 GiB). Architecture (GGUF arch gemma4): 48 layers, MHA with 16 kv
# heads x 512 head_dim, rope freq_base 1e6, final logit softcapping 30,
# per-layer token embeddings (PLE) inside the file, and a sliding-window
# attention pattern (attention.sliding_window = 1024) -- most layers cache
# only a 1024-position window, which is why the KV pool is a fraction of
# the full-ctx x all-layers number.
# Model: MiMo-V2.6-Distill-Qwen-9B-INT8-W8A16-AutoRound — a Qwen3.5-9B
# distillation at INT8 W8A16 (AutoRound, group 128, symmetric). 8
# safetensors shards, 12.0 GiB total. The vision tower
# (qwen3_5_vision, 27 layers) and embed_tokens stay fp16 inside the
# checkpoint, so the image path needs no separate projector file.
# Architecture: 32 layers, 8 full-attention (4 KV heads x 256 head_dim)
# + 24 Gated DeltaNet, native 262144 window. text_config declares
# mtp_num_hidden_layers = 1, but the shipped safetensors carry NO mtp.*
# tensors (verified against model.safetensors.index.json 2026-10-01 —
# base BF16 and this INT8 conversion both omit the head), so there is no
# spec decode: SGLang would draft with an uninitialised 4.24 GiB ghost
# model at 0% acceptance and pay the verify tax for nothing.
#
# MTP: the Multi-Token Prediction head ships as a SEPARATE file
# (mtp-gemma-4-12B-it.gguf, arch gemma4-assistant, 4 nextn layers, 0.24
# GiB). Unlike the Qwen3.8 -mtp build (head inside the main file), this one
# is passed via --model-draft with --spec-type draft-mtp, so the draft
# context loads the assistant model. The same --spec-type value chains the
# draftless ngram-mod matcher, which attaches unconditionally; two
# context-backed drafters cannot share one process, so draft-mtp,ngram-mod
# is the only legal shape that carries both.
#
# SIZING (RTX 3090, 24576 MiB): CTX_SIZE = PARALLEL x 262144 -- four
# FULL-window slots, measured to fit: the 4-slot boot idles at 22,346
# MiB and each extra full-context slot costs 3,450 MiB (measured 1-slot
# 11,996 -> 4-slot 22,346). A fifth slot projects to ~25.8 GiB, past the
# card, and the KV pool allocates upfront -- so 4 is the max. Explicit
# CTX_SIZE bypasses --fit on purpose: --fit maximises the TOTAL pool,
# which would shrink each slot below the full 262144 window once
# parallel > 1.
#
# Vision + audio: --mmproj loads the BF16 projector (11 tensors, 52M
# params; it carries an audio encoder too). The fleet's image path lives
# here, which is why halogen no longer sets HALOGEN_VISION_TOWER. Audio
# WORKS: input_audio content parts transcribe verbatim (verified
# 2026-09-17 with a 16k mono WAV).
# SIZING (RTX 3090), measured 2026-10-01: the 0.98 budget holds the
# checkpoint (11,354 MiB) + the DeltaNet ssm state pool (795 MiB at 32
# bf16 slots) + the KV pool. The engine's autofit picks a 687,388-token
# pool and leaves ~0.53 GB — too little: Triton's deferred kernel loads
# take most of it after boot, and eager-prefill activations then OOM on
# the first long request. The pool is therefore PINNED at 606,208 tokens
# (2 x 262,144 native slots since the 2026-10-01 reslice; 4 x 151,552
# before), which leaves ~0.8 GB for the prefill workspace; a 170k single
# request and 4 concurrent 54k requests were verified at the 4-slot
# shape.
# The ssm pool is the 4.5 GiB the weights-only arithmetic misses.
#
# Sampling: greedy by default (the fleet contract); a client that sends a
# temperature gets its own, and the harness applies per-model overrides
@@ -50,69 +42,45 @@
# reads those bare vars on the ROCm hosts -- see the 2026-08-13 incident in
# AGENTS.md). This box is CUDA, but the rule keeps env files portable.
# llama.cpp runtime binary: mainline master 37b53fd, CUDA sm_86,
# FA_ALL_QUANTS=ON.
LLAMA_BIN=/home/dank/GitPackages/llama.cpp-mainline/build-cuda/bin/llama-server
# SGLang runtime: python3.12 venv, self-contained CUDA stack.
SGLANG_BIN=/home/dank/GitPackages/sglang-cu128/bin/sglang
# Model package. The MTP sidecar file is required for speculative decoding.
MODEL_DIR=/home/dank/models/Gemma4-12B-QAT
MODEL_FILE=Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced-Q4_K_M.gguf
MMPROJ_PATH=/home/dank/models/Gemma4-12B-QAT/mmproj-Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced-BF16.gguf
DRAFT_FILE=mtp-gemma-4-12B-it.gguf
# Model package (8 shards + configs, sha256-verified by
# scripts/download-frank-small.sh).
MODEL_DIR=/home/dank/models/MiMo-V2.6-Distill-Qwen-9B-INT8-W8A16-AutoRound
# Fleet identity and network. 7771 is this service's own endpoint on
# Dankclaw; 7770 stays frank-large's. The alias is the id at /v1/models and
# what clients ask for -- the harness entry in models.yml names it.
# Dankclaw; 7770 stays frank-large's. The alias is the id at /v1/models
# and what clients ask for -- the harness entry in models.yml names it.
ALIAS=frank-small
BIND_ADDR=0.0.0.0
LISTEN_PORT=7771
# Four FULL 262144-token contexts, one per slot (CTX_SIZE is the total
# pool; --parallel divides it). See the SIZING note above for the fit
# arithmetic; a fifth slot does not fit.
CTX_SIZE=1048576
PARALLEL=4
CACHE_TYPE_K=q8_0
CACHE_TYPE_V=q8_0
# CPU RAM cache cap in MiB (build default 8192). This host is memory-tight
# (frank-large's 70 GiB GTT plus the rest of the stack), and Gemma4 runs
# fully on the 3090 (-ngl 999), so the CPU-side cache is not the hot path;
# cap it at 2048 to give back ~6 GiB of LPDDR. Gemma4 is not a DeltaNet
# model, so the >12.8 GiB CACHE_RAM floor does not apply.
CACHE_RAM=2048
# Two slots at the model's native 262,144 window on fp8 KV. The pool is
# pinned (see SIZING above): 606,208 tokens, and 2 x 262,144 = 524,288
# leaves ~82k tokens of pool slack. Resliced 2026-10-01 from 4 x 151,552
# so a compaction request (frank-primary's trigger 183,501 tokens + a
# 32,768-token summary budget = 216,269) fits ONE request; the grid is
# the two-way concurrency contract. A single request may still grow to
# the whole pool (a 170k prompt was verified at the 4-slot shape).
MEM_FRACTION=0.98
MAX_TOTAL_TOKENS=606208
CONTEXT_LENGTH=262144
MAX_RUNNING=2
KV_DTYPE=fp8_e4m3
QUANTIZATION=auto-round
# DeltaNet (mamba) recurrent states: the ssm state pool is the single
# biggest hidden consumer on this card. The engine autofills the slot
# COUNT to spend a fixed ~5.1 GB budget regardless of dtype (fp32 at 110
# slots, bf16 at 217 — same 5.1 GB), so BOTH dials are pinned below:
# bf16 dtype + 32 slots = 795 MiB.
MAMBA_SSM_DTYPE=bfloat16
# 32 slots is 16x the 2-way concurrency: enough for the radix mamba
# cache to keep shared-prefix states, small enough to leave the KV pool
# room.
MAX_MAMBA_CACHE_SIZE=32
# Batch geometry: 8192 logical / 1024 physical. Measured on this card at
# max length (254k-token prefill / 253k-ctx decode, 4 slots, q8 KV):
# ubatch 512 -> pp 915 t/s, tg@250k 90-204; ubatch 1024 -> pp 962,
# tg 257-302. Larger ubatches (2048) OOM the MTP draft context's pp
# compute buffer (~3.3 GiB against 2.2 GiB headroom) and must not be
# tried. Idle VRAM is 23,300 MiB at this geometry.
BATCH_SIZE=8192
UBATCH_SIZE=1024
# CPU threads: this service runs entirely on the GPU (NGL=999), so threads
# cover tokenization, sampling and the HTTP layer only. Deliberately modest
# -- this host's CPU is shared with halogen's engine, which is CPU-hungry.
NUM_THREADS=8
THREAD_BATCH=8
# Every layer on the 3090, with flash attention (required for q8 KV).
NGL=999
FLASH_ATTN=on
# Speculative decoding: the MTP sidecar (draft context) chained with the
# draftless ngram-mod matcher. Draft depth and busy-wait level are made
# explicit here (both were the implicit build defaults: 3 and 50).
# Measured at 250k ctx: depth 4 + poll 100 DECODED WORSE (230-257 t/s)
# than depth 3 + poll 50 (257-302 t/s) — the longer verification round
# costs more attention re-read at long context than the extra accepted
# token earns. Keep 3/50.
SPEC_TYPE=draft-mtp,ngram-mod
SPEC_DRAFT_N_MAX=3
POLL_LEVEL=50
# Greedy default (fleet contract); reasoning is extracted into
# reasoning_content with an unlimited budget (the model decides).
TEMPERATURE=0.0
REASONING_FORMAT=deepseek
REASONING_BUDGET=-1
# Reasoning is extracted into reasoning_content; tools use the qwen3_coder
# grammar (both parsers per the SGLang Qwen3.5 cookbook).
REASONING_PARSER=qwen3
TOOLCALL_PARSER=qwen3_coder
+2 -3
View File
@@ -1,5 +1,5 @@
[Unit]
Description=llama.cpp Qwen3.8-27B GSQ-RCO IQ3_S MTP+vision (dankclaw, frank-small)
Description=SGLang MiMo-V2.6-Distill-Qwen-9B-INT8 (qwen3_5 hybrid, in-checkpoint vision, no MTP) 4x151k fp8 KV (dankclaw, frank-small)
After=network-online.target
Wants=network-online.target
@@ -8,8 +8,7 @@ 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. Parity with the halogen
# quadlet's Ulimit=memlock=-1:-1 and the retired ik unit.
# 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
+2 -2
View File
@@ -18,7 +18,7 @@
# is not an OSI licence.
#
# Shape: one session, full 262144 context (the model's native window). The
# 27B dense weights (29.3 GiB) + the DFlash2 drafter (1.07 GiB) + KV +
# 27B dense weights (16.35 GiB at UD-Q4_K_XL) + the DFlash2 drafter (1.07) + KV +
# compute buffers fit the iGPU's GTT aperture (~114 GiB); a load at this
# context measured 66.5 GiB of the 116.7 GiB device.
#
@@ -78,7 +78,7 @@ GUFO_BIN="$RUNTIME_DIR/bin/gufo"
# and keeps its own long filename, while the DFlash2 drafter is unchanged and
# still lives beside the previous target. MODEL_FILE/DRAFTER_FILE default to
# the deployed payload, so the env file only has to state them when it moves.
: "${MODEL_FILE:=$MODEL_DIR/Swift-1.5-Qwen3.8-27B-Uncensored-Dynamic-MTP-UD-Q8_K_XL.gguf}"
: "${MODEL_FILE:=$MODEL_DIR/Qwen3.8-27B-UD-Q4_K_XL.gguf}"
: "${DRAFTER_DIR:=/home/dank/models/Qwen3.8-27B-UD-Q8_K_XL}"
: "${DRAFTER_FILE:=$DRAFTER_DIR/Qwen3.8-27B-DFlash2-Q4_K_M.gguf}"
+20 -8
View File
@@ -11,12 +11,14 @@
# every flag here was qualified by boot probe on 2026-09-29 — see
# frank-primary.env for the qualification record).
#
# Shape: MAXLEN 200000 x 3 sessions (600k total), KV q8/q8 (--kv-cache-dtype
# fp8: e4m3 for both K and V — the stock flag quantizes them together, which
# is the requested q8/q8), KV_BYTES 7.2 GiB PER RANK (the engine measured
# 729,545 tokens of capacity / 3.65x concurrency at 200k per request), MTP
# depth 4, prefix caching, expert prefetch OFF (telemetry measured it at 36%
# precision — the tuned incumbent deletes it), TunableOp off.
# Shape (2026-10-01 bf16 cutover): MAXLEN 262144 x 3 sessions (786,432
# tokens), KV UNQUANTIZED (--kv-cache-dtype auto = bf16; the fp8 q8/q8 shape
# is retired to git tag frank-primary-fp8-mtp-20261001), KV_BYTES
# 11,047,010,304 PER RANK (the engine measured 798,280 tokens of capacity /
# 3.05x concurrency), NO speculative decode, --max-num-batched-tokens 1024
# (Frank's lock), MoE gather geometry R4D_LRU_GATHER_CHUNKS=32 /
# R4D_LRU_GATHER_LANES=64 (+18.7% decode, grows with depth), prefix caching,
# expert prefetch OFF (36% precision measured), TunableOp off.
#
# The root unit (scripts/frank-primary.service, User=dank,
# LimitMEMLOCK=infinity) grants the pin budget for the tiered-expert host
@@ -45,7 +47,10 @@ set +a
: "${FRANK_PRIMARY_MAXLEN:?FRANK_PRIMARY_MAXLEN must be set}"
: "${FRANK_PRIMARY_SEQS:?FRANK_PRIMARY_SEQS must be set}"
: "${FRANK_PRIMARY_KV_BYTES:?FRANK_PRIMARY_KV_BYTES must be set (PER RANK)}"
: "${FRANK_PRIMARY_KV_DTYPE:?FRANK_PRIMARY_KV_DTYPE must be set (fp8 = q8/q8 KV)}"
: "${FRANK_PRIMARY_KV_DTYPE:?FRANK_PRIMARY_KV_DTYPE must be set (auto = bf16 KV)}"
: "${FRANK_PRIMARY_REASONING_PARSER:?FRANK_PRIMARY_REASONING_PARSER must be set (qwen3)}"
: "${FRANK_PRIMARY_TOOL_PARSER:?FRANK_PRIMARY_TOOL_PARSER must be set (qwen3_xml)}"
: "${FRANK_PRIMARY_CHAT_TEMPLATE_KWARGS:?FRANK_PRIMARY_CHAT_TEMPLATE_KWARGS must be set}"
# Capture podman's output BEFORE grepping: under `set -o pipefail`, the
# classic `podman images | grep -q` pattern races — grep exits on its first
# match, podman dies SIGPIPE (141) writing the remaining lines, and pipefail
@@ -100,17 +105,24 @@ podman run -d --name "$FRANK_PRIMARY_CONTAINER" \
--cap-add SYS_PTRACE \
--device /dev/kfd --device /dev/dri --device /dev/mem \
-e HIP_VISIBLE_DEVICES=0,1 -e VLLM_ROCM_USE_AITER=0 \
${FRANK_PRIMARY_GATHER_CHUNKS:+-e R4D_LRU_GATHER_CHUNKS="$FRANK_PRIMARY_GATHER_CHUNKS"} \
${FRANK_PRIMARY_GATHER_LANES:+-e R4D_LRU_GATHER_LANES="$FRANK_PRIMARY_GATHER_LANES"} \
-v "$FRANK_PRIMARY_MODEL_DIR":/models:ro \
"$FRANK_PRIMARY_IMAGE" /models \
--served-model-name "$FRANK_PRIMARY_SERVED_NAME" --port 7770 \
--tensor-parallel-size 2 \
${FRANK_PRIMARY_DCP:+--decode-context-parallel-size "$FRANK_PRIMARY_DCP"} \
--max-model-len "$FRANK_PRIMARY_MAXLEN" \
--max-num-seqs "$FRANK_PRIMARY_SEQS" \
${FRANK_PRIMARY_MNBT:+--max-num-batched-tokens "$FRANK_PRIMARY_MNBT"} \
${FRANK_PRIMARY_PRECISE_MEMORY:+--expert-precise-memory} \
--gpu-memory-utilization "$FRANK_PRIMARY_UTIL" \
--kv-cache-memory-bytes "$FRANK_PRIMARY_KV_BYTES" \
--kv-cache-dtype "$FRANK_PRIMARY_KV_DTYPE" \
--enable-prefix-caching \
--speculative-config "{\"method\":\"mtp\",\"num_speculative_tokens\":$FRANK_PRIMARY_SPEC}" \
--enable-auto-tool-choice --tool-call-parser "$FRANK_PRIMARY_TOOL_PARSER" \
--reasoning-parser "$FRANK_PRIMARY_REASONING_PARSER" \
--default-chat-template-kwargs "$FRANK_PRIMARY_CHAT_TEMPLATE_KWARGS" \
--trust-remote-code \
> "$LOG" 2>&1
+60 -109
View File
@@ -1,37 +1,28 @@
#!/usr/bin/env bash
# Serve HauhauCS/Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced (Q4_K_M) as
# frank-small on Dankclaw's RTX 3090 via mainline llama.cpp.
# Serve letechlead/MiMo-V2.6-Distill-Qwen-9B-INT8-W8A16-AutoRound as
# frank-small on Dankclaw's RTX 3090 via SGLang.
#
# Topology: the whole model lives in VRAM (-ngl 999) -- 6.87 GiB of Q4_K_M
# weights plus the BF16 vision projector and q8_0 KV inside the card's
# 24 GiB. The host CPU only tokenizes and samples here; this box's CPU
# belongs to the halogen engine that serves frank-large.
# Topology: the whole checkpoint (12.0 GiB, INT8 W8A16 AutoRound) lives in
# VRAM; the 3090's 24 GiB holds weights + a ~11.8 GiB fp8 KV pool at
# --mem-fraction-static 0.98. The host CPU only tokenizes.
#
# MTP: this model's Multi-Token Prediction head ships as a SEPARATE file
# (mtp-gemma-4-12B-it.gguf, arch gemma4-assistant, 4 nextn layers). It is
# passed via --model-draft with --spec-type draft-mtp: the draft context
# loads the assistant model. The same --spec-type value chains the
# draftless ngram-mod matcher, which attaches unconditionally; two
# context-backed drafters cannot share one process, so this chain is the
# only shape that carries both.
# Architecture: qwen3_5 hybrid — 32 layers, 8 full-attention + 24 Gated
# DeltaNet, native 262144 window, and a vision tower (qwen3_5_vision)
# baked into the safetensors: no separate projector file, the image path
# is in the checkpoint. The config declares an MTP layer, but the shipped
# weights carry none (no mtp.* tensors in the index), so this service runs
# WITHOUT speculative decoding — a NEXTN draft would be an uninitialised
# 4.24 GiB ghost model drafting at 0% acceptance.
#
# Context: CTX_SIZE is set explicitly to PARALLEL x 262144 so every slot
# gets the model's FULL window; --fit (the CTX_SIZE-unset branch below)
# maximises the TOTAL pool instead, which would divide a smaller window
# across slots. The 4-slot layout is measured to fit the card (see the
# SIZING note in frank-small.env); more slots would fail the KV allocation.
# Context: CONTEXT_LENGTH x MAX_RUNNING slots must fit the fp8 KV pool,
# which the engine autofits around the weights AND the DeltaNet ssm state
# pool (see frank-small.env). The mamba pool defaults to ~5.1 GB, so it is
# pinned (bf16, 32 slots). With the grid at its measured fit the card has
# no headroom for prefill CUDA-graph capture, so prefill runs eager
# (--disable-prefill-cuda-graph); decode graphs are untouched.
#
# Vision + audio: --mmproj loads the BF16 projector, which also carries
# an audio encoder — input_audio content parts transcribe verbatim
# (verified 2026-09-17). The fleet's image path lives here, which is why
# halogen no longer sets HALOGEN_VISION_TOWER.
#
# Sampling: greedy by default (the fleet contract). Clients that send their own
# temperature get their own values, and the harness overrides per model from
# models.yml. --jinja is pinned even though this build defaults it on: the
# model's own template supplies reasoning_effort, preserve_thinking and the
# tool-call grammar, and a future build that flips that default must not
# silently take tools away.
# Sampling: greedy by default (the fleet contract); clients that send their
# own temperature get their own values.
#
# Tunables come from frank-small.env unless FRANK_SMALL_ENV_FILE overrides it.
set -euo pipefail
@@ -46,101 +37,61 @@ if [[ -f "$ENV_FILE" ]]; then
fi
# --- defaults (used when the env file does not set them) -------------------
: "${LLAMA_BIN:=/home/dank/GitPackages/llama.cpp-mainline/build-cuda/bin/llama-server}"
: "${MODEL_DIR:=/home/dank/models/Gemma4-12B-QAT}"
: "${MODEL_FILE:=Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced-Q4_K_M.gguf}"
: "${MMPROJ_PATH:=$MODEL_DIR/mmproj-Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced-BF16.gguf}"
# NOTE: the fallback above was the retired ISTA-DASLab Qwen3.8-27B GSQ-RCO
# payload, which frank-small served on 2026-09-16/17 and which no longer
# exists on disk. frank-small.env has always overridden it, so the drift was
# invisible — but a missing or unreadable env file would have left this
# script pointing at a payload that is not there, turning a config problem
# into a "missing asset" that names the wrong model.
: "${DRAFT_FILE:=}"
: "${SGLANG_BIN:=/home/dank/GitPackages/sglang-cu128/bin/sglang}"
: "${MODEL_DIR:=/home/dank/models/MiMo-V2.6-Distill-Qwen-9B-INT8-W8A16-AutoRound}"
: "${ALIAS:=frank-small}"
: "${BIND_ADDR:=0.0.0.0}"
: "${LISTEN_PORT:=7771}"
: "${CTX_SIZE:=}"
: "${PARALLEL:=1}"
: "${CACHE_TYPE_K:=f16}"
: "${CACHE_TYPE_V:=f16}"
: "${CACHE_RAM:=8192}"
: "${BATCH_SIZE:=2048}"
: "${UBATCH_SIZE:=512}"
# Decode-shape knobs: the MTP drafter's per-round proposal length (build
# default 3; the Gemma4 sidecar carries 4 nextn layers) and the engine's
# busy-wait level (build default 50).
: "${SPEC_DRAFT_N_MAX:=3}"
: "${POLL_LEVEL:=50}"
: "${NUM_THREADS:=8}"
: "${THREAD_BATCH:=8}"
: "${NGL:=999}"
: "${FLASH_ATTN:=on}"
: "${SPEC_TYPE:=draft-mtp}"
: "${TEMPERATURE:=0.0}"
: "${REASONING_FORMAT:=deepseek}"
: "${REASONING_BUDGET:=-1}"
: "${MEM_FRACTION:=0.98}"
: "${CONTEXT_LENGTH:=151552}"
: "${MAX_TOTAL_TOKENS:=606208}"
: "${MAX_RUNNING:=4}"
: "${KV_DTYPE:=fp8_e4m3}"
: "${QUANTIZATION:=auto-round}"
: "${REASONING_PARSER:=qwen3}"
: "${TOOLCALL_PARSER:=qwen3_coder}"
: "${MAMBA_SSM_DTYPE:=bfloat16}"
: "${MAX_MAMBA_CACHE_SIZE:=32}"
# Fail loudly rather than half-loading a model into VRAM: a missing file here
# is a download that has not finished, and the unit's restart policy would
# otherwise turn that into a crash loop that reads like a runtime fault.
for path in "$LLAMA_BIN" "$MODEL_DIR/$MODEL_FILE" "$MMPROJ_PATH"; do
for path in "$SGLANG_BIN" "$MODEL_DIR/model.safetensors.index.json" \
"$(cd -- "$(dirname -- "$SGLANG_BIN")/.." && pwd)/cuda-nvcc/usr/local/cuda-13.0/bin/nvcc"; do
[[ -e "$path" ]] || { echo "frank-small: missing $path" >&2; exit 1; }
done
if [[ -n "${DRAFT_FILE:-}" ]]; then
[[ -e "$MODEL_DIR/$DRAFT_FILE" ]] || { echo "frank-small: missing $MODEL_DIR/$DRAFT_FILE" >&2; exit 1; }
shard_count=$(find "$MODEL_DIR" -maxdepth 1 -name 'model-*.safetensors' | wc -l)
if [[ "$shard_count" -ne 8 ]]; then
echo "frank-small: expected 8 safetensors shards in $MODEL_DIR, found $shard_count" >&2
exit 1
fi
# The UVM device node is created lazily by nvidia-modprobe on the first CUDA
# open after boot; make sure it exists before the server needs it.
nvidia-modprobe -u -c=0 2>/dev/null || true
MMPROJ_ARGS=()
if [[ -n "${MMPROJ_PATH:-}" && -f "$MMPROJ_PATH" ]]; then
MMPROJ_ARGS=(--mmproj "$MMPROJ_PATH")
fi
# FlashInfer JITs its attention kernels with nvcc at boot. The host's
# /usr/bin/nvcc is CUDA 12.4 and dies on `--compress-mode` (a 12.8+
# option), so the venv carries a matching CUDA 13.0 nvcc (extracted from
# the cuda-nvcc-13-0 deb); it must shadow the system one on PATH.
export PATH="$(cd -- "$(dirname -- "$SGLANG_BIN")/.." && pwd)/cuda-nvcc/usr/local/cuda-13.0/bin:$PATH"
SPEC_ARGS=()
if [[ -n "${SPEC_TYPE:-}" && "$SPEC_TYPE" != "none" ]]; then
SPEC_ARGS=(--spec-type "$SPEC_TYPE" --spec-draft-n-max "$SPEC_DRAFT_N_MAX")
fi
DRAFT_ARGS=()
if [[ -n "${DRAFT_FILE:-}" ]]; then
DRAFT_ARGS=(--model-draft "$MODEL_DIR/$DRAFT_FILE")
fi
# CTX_SIZE set -> pinned context. Unset -> --fit sizes the KV pool against
# whatever the weights, projector, draft context and compute buffers leave
# on the card; the engine prints the chosen value at startup.
if [[ -n "${CTX_SIZE:-}" ]]; then
CTX_ARGS=(--ctx-size "$CTX_SIZE")
else
CTX_ARGS=(--fit on)
fi
exec "$LLAMA_BIN" \
--model "$MODEL_DIR/$MODEL_FILE" \
"${MMPROJ_ARGS[@]}" \
"${DRAFT_ARGS[@]}" \
--alias "$ALIAS" \
# Sampling: SGLang has no server-wide sampling defaults; the harness sends
# its per-model recipe from models.yml (compat.extraBody), and other clients
# get the engine's own defaults.
exec "$SGLANG_BIN" serve \
--model-path "$MODEL_DIR" \
--served-model-name "$ALIAS" \
--host "$BIND_ADDR" \
--port "$LISTEN_PORT" \
--gpu-layers "$NGL" \
--flash-attn "$FLASH_ATTN" \
"${CTX_ARGS[@]}" \
--parallel "$PARALLEL" \
--batch-size "$BATCH_SIZE" \
--ubatch-size "$UBATCH_SIZE" \
--threads "$NUM_THREADS" \
--threads-batch "$THREAD_BATCH" \
--poll "$POLL_LEVEL" \
--cache-type-k "$CACHE_TYPE_K" \
--cache-type-v "$CACHE_TYPE_V" \
--cache-ram "$CACHE_RAM" \
"${SPEC_ARGS[@]}" \
--jinja \
--metrics \
--temp "$TEMPERATURE" \
--reasoning-format "$REASONING_FORMAT" \
--reasoning-budget "$REASONING_BUDGET"
--mem-fraction-static "$MEM_FRACTION" \
--context-length "$CONTEXT_LENGTH" \
--max-running-requests "$MAX_RUNNING" \
--kv-cache-dtype "$KV_DTYPE" \
--quantization "$QUANTIZATION" \
--reasoning-parser "$REASONING_PARSER" \
--tool-call-parser "$TOOLCALL_PARSER" \
--mamba-ssm-dtype "$MAMBA_SSM_DTYPE" \
--max-mamba-cache-size "$MAX_MAMBA_CACHE_SIZE" \
--disable-prefill-cuda-graph \
--max-total-tokens "$MAX_TOTAL_TOKENS"
@@ -244,13 +244,148 @@ scripts `arm_*.sh` / `sweep_*.sh` and the detached runner `/home/dank/job.sh`
are `podman cp`'d into the container after every recreate (the serve script
re-copies them; a recreate wipes container-local files).
## 2026-10-01 — production cutovers (qwen FP8+MTP4, then bf16 no-spec)
Two same-day cutovers moved this page's findings into production:
1. **Qwen FP8 + MTP4 replaced the failed GLM/DFlash2 experiment** (the GLM
window is documented in [[frank-primary-glm53-flash-w4a16]]; git tag
`frank-primary-fp8-mtp-20261001` is the last commit of that shape). The
production trio took MAXLEN 200000 x 3, fp8 KV, MTP4, prefetch off —
measured 37.4-40.6 tok/s at ~54% acceptance.
2. **The overnight redo campaign re-measured EVERY lever at matched
geometry** (prefetch OFF everywhere, MAXLEN 200000/SEQS 3/fp8 baseline)
and concluded the day: the incumbent cutover to **bf16 KV, no
speculative decode** (Frank's call).
### What the redo campaign measured (all at shallow depth, 166/1087/4064)
| lever | verdict |
|---|---|
| prefetch (re-confirmed) | the whole night's +40-51% lives in deleting it; the old 12.11 "no-spec baseline" was itself prefetch-taxed |
| gather geometry | **R4D_LRU_GATHER_CHUNKS=32 / LANES=64 = +18.7%** (49.25 @4064), the win GROWS with depth (39.5@166 -> 54.1@1087); g8x16 mild, g64x128 past peak |
| KV dtype | bf16 (`auto`) +4% decode on fp8-era numbers but halves attention-KV capacity (measured 14,047 vs 7,926 B/token; mamba states unaffected) |
| spec family | no-spec fastest once the tax was gone (41.46/41.29/41.47); MTP4's drafter reserves ~2.6 GiB/rank beside the pool; untaxed MTP re-measures never completed |
| MNBT | 512 doubles TTFT (2.46 s vs 1.36 s @4064); 1024-4096 interchangeable; 12288 -2.5% + arena; **locked 1024** |
| UVA | 2048 POISON (-39%); 8192 ~parity |
| arena | flat ±1.4% from ~6,830 down to ~5,500 slots; knee below |
| six slots | every SEQS-6 KV sizing refused at engine init |
Depth caveat: every number above is at a near-empty KV. Deep-context
behavior (the gather win growing with depth, bf16's decode cost at depth)
is only sampled at 3 depths; a 64k-192k-depth probe is the flagged gap.
### The deployed shape (2026-10-01: 5 x 262144, fp8, no spec)
```
FRANK_PRIMARY_MAXLEN=262144 x SEQS 2 (524,288 tokens of contract)
FRANK_PRIMARY_KV_BYTES=7300000000 PER RANK (bf16 = auto; 13,839 B/token)
FRANK_PRIMARY_KV_DTYPE=auto --kv-cache-dtype auto (bf16, unquantized)
FRANK_PRIMARY_PRECISE_MEMORY=1 --expert-precise-memory (fitted overhead
5.25 GiB instead of the 7.60 GiB default,
so ~1,025 more arena slots)
FRANK_PRIMARY_MNBT=1024 --max-num-batched-tokens 1024
R4D_LRU_GATHER_CHUNKS=32 / R4D_LRU_GATHER_LANES=64 (container env)
NO --speculative-config, NO --expert-prefetch
```
Boot-probed 2026-10-01 (transient systemd units at the production uid +
memlock, full-log capture; the rootless bench probe had masked the production
memory environment). The night searched two concurrency contracts:
| rung | result |
|---|---|
| 3 × 262144, bf16, KV 11,047,010,304 | **OOM at graph capture** — `Tried to allocate 76.00 MiB ... 0 bytes free`, 30.43 GiB of 31.86 GiB already allocated by PyTorch |
| 3 × 245760, bf16 | **OOM identically** |
| 3 × 237568, bf16 | PASS — KV 718,606 tokens |
| **3 × 241664, bf16** | **PASS — KV 732,359 tokens, 3.03x** (max possible at 3 contexts) |
| 6 × 241664, fp8 | **OOM** — tried 10.70 GiB against 9.18 GiB free: six full-length contexts do NOT fit |
| 5 × 262144, fp8 | PASS on the first rung — KV 1,350,182 tokens, 5.15x |
| 4 × 262144, fp8 | runtime-survivable stopgap — KV 1,079,582 tokens / 4.12x |
| 3 × 262144, fp8, pool at the floor | KV 792,069 tokens / 3.02x; arena 6,248 slots; 3.59 GiB free VRAM measured |
| **2 × 262144, bf16 + `--expert-precise-memory`** | **DEPLOYED** (Frank's call): unquantized KV at the full native window, two contexts; pool 7.3e9 B/rank (bf16 rate 13,839 B/token measured: 12,276 attention + 1,563 mamba/side, vs fp8's 6,138 + 1,563 = 7,701); the precise-memory flag drops the plan's overhead 7.60 -> 5.25 GiB so the arena grows from 6,248 to ~7,278 slots |
Boot is NOT proof of runtime survivability: the five-slot shape passed every
boot gate and still died on the first long-generation request. After any
knife-edge shape change, send a request with a large `max_tokens` before
calling it done. The deployed shape is **four contexts of the model's full
native 262,144 window**. fp8 KV is what buys the capacity —
7,926 B/token against bf16's ~13,900-14,047 — at the cost of bf16's ~4 %
decode edge. Six full-length contexts cannot fit at any KV dtype: the 6-seq
graph/activation footprint leaves only 9.18 GiB for the pool, and 6 × 262144
needs 12.47 GB even at fp8.
The old "KV_BYTES is PER RANK, 9/16 GiB OOM" law was the MTP4 WORKSPACE
reservation, not a VRAM wall. Failures are clean and diagnostic: the engine
reports `torch.OutOfMemoryError: Tried to allocate X GiB. GPU N has ... of
which Y GiB is free`, and the fork's giant ERROR lines are split by journald —
read them via `journalctl -o json`, not `-o cat` (and `podman logs`, which is
only available while the container lives).
Rollback to the 2026-09-29 fp8+MTP4 shape: git tag
`frank-primary-fp8-mtp-20261001` (env trio + seam re-pinned there).
## Parallelism options on this box (2026-10-01 survey)
Surveyed from the running image's own CLI surface. Verdicts are specific to
dankserver: 2x R9700 (gfx1201), a ~172.8 GiB expert-offload MoE, and a model
with only 2 KV heads.
| option | flag | verdict on this box |
|---|---|---|
| TP | `--tensor-parallel-size` | **DEPLOYED, =2.** All-reduce dispatch shows `R4D_AR` then `PYNCCL` |
| DCP | `--decode-context-parallel-size` | **REJECTED at TP=2** — see below |
| PP | `--pipeline-parallel-size` | supported; untried (stage handoff plus a TP-keyed expert plan) |
| DP | `--data-parallel-size` (+`-rank`, `-start-rank`) | impossible: every replica holds a full model copy (172.8 GiB vs 31.86 GiB/card) |
| EP | `--enable-expert-parallel` + `--all2all-backend` (+`--enable-eplb`, `--enable-dbo`, `--enable-elastic-ep`) | supported (`naive`, `allgather_reducescatter`, `deepep_high_throughput`, `deepep_low_latency`, `pplx`, `mori`, `nixl`); would replace the fork's tiered-offload LOCAL gather with a per-layer PCIe all-to-all |
| multi-node | `--nnodes`, `--node-rank`, `--master-addr/port`, `--distributed-executor-backend` | supported; the actual path to more cards |
### DCP is structurally unavailable here — do not re-test on 2 GPUs
`--decode-context-parallel-size 2` fails `VllmConfig` validation at boot:
```
Decode context parallelism for GQA/MQA requires `--tensor-parallel-size` (2) to be
greater than the model's total number of KV heads (2). Increase
`--tensor-parallel-size` or set `--decode-context-parallel-size 1`.
```
DCP shards the KV along the *sequence* dimension after KV heads have been spread
across the TP ranks, so it requires **TP > num_kv_heads**. This model has 2 KV
heads (24 Q heads, GQA 12:1), so TP must be >= 4 — four GPUs, not two. Related
fork facts: DCP *reuses* the TP ranks rather than multiplying them (it is not
`TP x DCP`), and with PCP enabled the valid DCP sizes are `{1, pcp, tp x pcp}`
(`vllm/config/parallel.py`). The KV memory a DCP win would have bought is real —
each rank would hold half the sequence's KV — but it is unreachable without two
more cards.
### Measuring decode: the harness lives INSIDE the container
`/home/dank/mtp_measure.py` imports `/bench_iter.py` by absolute path, so it must
run in the engine's namespace and the files must be copied in first:
```
podman cp /home/dank/mtp_measure.py frank-primary-qwen:/
podman cp /home/dank/bench_iter.py frank-primary-qwen:/
podman exec frank-primary-qwen python3 /mtp_measure.py
```
Without the copy the exec dies with `can't open file '/mtp_measure.py': [Errno 2]
No such file or directory` — measured 2026-10-01, which silently cost a whole
arm's numbers. A window script must do the copy, not assume the path exists.
### The deployed shape, measured again (2026-10-01 A/B window)
A clean production-environment boot of the deployed config (4 x 262144 fp8, MNBT
2048 in that window) reported **`GPU KV cache size: 1,079,582 tokens, Maximum
concurrency for 262,144 tokens per request: 4.12x`** — the same figures as the
deployed MNBT-1024 shape, i.e. MNBT does not move the pool, and the capacity is
reproducible across boots.
## See Also
- [[dankserver-frontier-moe-feasibility]] — the sibling feasibility page
(which frontier MoE fits this box; the same PCIe-expert-stream wall at
V4.1 scale)
- [[frank-primary-r9v-radiance-qwen38-q8]] — the ACTIVE frank-primary
(production is the R9V fork; this page's container is the ad hoc detour)
- [[frank-primary-r9v-radiance-qwen38-q8]] — RETIRED 2026-09-30 (the R9V
fork era; production has been the tcclaviger fork since)
- [[x4-pair-experiment]] — the same residency law measured on a narrower
link: streaming over PCIe loses, computing in RAM does not care
- [[Dual-R9700-Cooperation]] — the board swap that made TP=2 legal here
@@ -0,0 +1,166 @@
---
type: reference
title: "frank-small on Dankclaw — SGLang, MiMo-V2.6-Distill-Qwen-9B INT8 W8A16"
description: "The active frank-small runbook — SGLang in a self-contained python3.12 venv serving leteschlead MiMo-V2.6-Distill-Qwen-9B-INT8-W8A16-AutoRound (qwen3_5 hybrid, 9B dense, in-checkpoint MTP + vision) on the RTX 3090: identity, payload, KV arithmetic, the NEXTN spec-decode shape, the CUDA 13 nvcc toolchain the JIT needs, deployed flags, the client contract, and what to check when it misbehaves."
tags:
- llm
- frank-small
- dankclaw
- sglang
- rtx3090
- qwen
- mtp
- vision
- int8
timestamp: 2026-10-01
---
# frank-small — SGLang MiMo-V2.6-Distill-Qwen-9B INT8 W8A16 (NEXTN MTP)
> **ACTIVE since 2026-10-01.** Replaces [[frank-small-gemma4-12b]]
> (llama.cpp Gemma4-12B QAT Q4_K_M, now the rollback target). Same port
> (7771), same alias (`frank-small`), same client contract surface.
## Identity
- **Endpoint:** `frank-small` at `192.168.0.143:7771` (Dankclaw).
- **Runtime:** SGLang (latest) in a self-contained python3.12 venv at
`/home/dank/GitPackages/sglang-cu128/` (torch 2.13.0+cu130,
transformers 5.12.1, flashinfer 0.6.18, sgl-kernel). No container — a root
systemd unit `scripts/frank-small.service` (`User=dank`,
`LimitMEMLOCK=infinity`) launched by `scripts/serve-frank-small.sh` with
tunables from `scripts/frank-small.env`.
- **Model:** `letechlead/MiMo-V2.6-Distill-Qwen-9B-INT8-W8A16-AutoRound`
(9B dense, 12.0 GiB, INT8 W8A16 AutoRound group-128 symmetric).
## Shape
- **Architecture `qwen3_5` hybrid:** 32 layers = 8 full-attention
(4 KV heads x 256 head_dim, `partial_rotary_factor: 0.25`) + 24 Gated
DeltaNet. `max_position_embeddings: 262144`, and a `qwen3_5_vision`
tower (27 layers) in the safetensors — no separate mmproj file.
- **Context:** two 262,144-token slots at the model's native window
(`--context-length 262144`, `--max-running-requests 2`) against a
**pinned** 606,208-token pool (`--max-total-tokens`) — 2026-10-01
reslice from four 151,552-token slots: 2 x 262,144 = 524,288 leaves
~82k tokens of pool slack, and a compaction request (frank-primary's
trigger 183,501 + a 32,768-token summary budget = 216,269) now fits
one request. A single request may grow to the whole pool — a
170,019-token prompt was verified at the 4-slot shape — the grid is
the two-way concurrency contract.
- **KV:** `fp8_e4m3` — 16 KiB/token (8 attn layers x 2 x 4 heads x 256
dim x 1 B), pool 9.31 GiB.
- **The memory shape (the 4.5 GiB the naive math misses):** the DeltaNet
ssm state pool is a first-class consumer. The engine autofills the
mamba slot count to spend a fixed ~5.1 GB budget *regardless of dtype*
(fp32 at 110 slots, bf16 at 217 — same 5.1 GB), so both dials are
pinned: `--mamba-ssm-dtype bfloat16 --max-mamba-cache-size 32` = 795
MiB. With that, weights 11.35 GiB + mamba 0.78 GiB + pool 9.31 GiB
leave ~0.8 GB — enough for eager-prefill workspaces, NOT enough for
CUDA-graph capture (autofit's 687,388-token pool leaves 0.53 GB and
dies in capture, or later in the first long request once Triton's
deferred kernel loads eat the remainder). Hence
`--disable-prefill-cuda-graph`; decode graphs are untouched.
- **Quantization:** `--quantization auto-round` — the checkpoint's
`quantization_config.json` declares `quant_method: "auto-round"` and
SGLang loads it natively (vision tower, `embed_tokens` and
`linear_attn.in_proj` stay fp16).
## Spec method
**None — and this is a checkpoint fact, not a tuning choice.** The
`text_config` declares `mtp_num_hidden_layers: 1`, but the shipped
safetensors carry **zero `mtp.*` tensors**: verified 2026-10-01 against
`model.safetensors.index.json` for both this INT8 conversion and the base
`XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B` (32 layers, indices 0–31, no
`mtp.`/`nextn.`/`layers.32` keys in either). With NEXTN enabled, SGLang
boots a 4.24 GiB draft model (`Qwen3_5ForCausalLMMTP`) from nothing and
decodes at `accept len: 1.00, accept rate: 0.00` — every proposal rejected,
paying the 4-token verify tax for no token. The serve script passes no
`--speculative-*` flag, and the seam gates that.
## CUDA 13 toolchain (the sharp edge)
The venv's torch is cu130, so every JIT kernel (sgl-kernel marlin repack,
flashinfer) compiles with a **CUDA 13.0 nvcc extracted from debs into the
venv** at `cuda-nvcc/usr/local/cuda-13.0/` — the system nvcc is 12.4 (no
`--compress-mode`) and its headers clash with the 13.0 device passes.
Components (all from the ubuntu2404 CUDA repo, `dpkg -x`'d, not installed):
| Package | Supplies |
|---|---|
| `cuda-nvcc-13-0` (13.0.88) | `bin/nvcc`, `ptxas`, `cudafe++`, … |
| `libnvvm-13-0` (13.0.48) | `nvvm/bin/cicc` (the device compiler) |
| `cuda-cudart-dev-13-0` (13.0.88) | `include/cuda_runtime.h`, `lib64/stubs` |
| `cuda-crt-13-0` (13.0.88) | `include/crt/host_runtime.h` (2-arg `__cudaLaunch`) |
| `libnvptxcompiler-13-0` (13.0.88) | static lib + `nvPTXCompiler.h` |
| `cuda-cccl-13-0` (13.0.50) | `cccl/cuda/...` headers (libcudacxx) |
Three local modifications the tree carries:
1. **`bin/nvcc` is a shim** over `bin/nvcc.real` adding
`-allow-unsupported-compiler` (host GCC 16 > nvcc's max 13).
2. **`targets/x86_64-linux/include` and `lib` are symlinks** to
`../../../include` / `../../../lib64` (the deb ships them as real
near-empty dirs; the stub pass must see the 13.0 headers, not
`/usr/include` 12.4).
3. **`include/cuda` → `cccl/cuda`** symlink (CCCL 3.x layout; flashinfer
includes `<cuda/functional>`), and **`crt/math_functions.h`** patched with
`noexcept` on `rsqrt`/`rsqrtf` (glibc 2.42 declares them `noexcept(true)`;
the unpatched 13.0 declarations are incompatible in the C++ host stub).
JIT caches: `~/.cache/sglang/jit/sm86/` and
`~/.cache/sglang/.cache/flashinfer/0.6.18/86/` — clear both when a toolchain
change lands.
## Payload
Eight safetensors shards (12,891,718,440 B total) + tokenizer and config
files under `/home/dank/models/MiMo-V2.6-Distill-Qwen-9B-INT8-W8A16-AutoRound/`,
all LFS sha256-verified by `scripts/download-frank-small.sh` (`--verify-only`
re-checks). The serve script refuses to start with a missing shard.
## Client contract
- **Alias:** `frank-small` (the `id` at `/v1/models`).
- **Reasoning:** extracted to **`reasoning_content`** (live-verified
2026-10-01 — this SGLang build's qwen3 parser uses the same field name
as llama.cpp; models.yml sets `reasoningContentField:
"reasoning_content"`). `--reasoning-parser qwen3`.
- **Tools:** `--tool-call-parser qwen3_coder`.
- **Vision:** supported (in-checkpoint tower).
- **Sampling:** SGLang has NO server-wide `--temperature`/`--top-p`/
`--top-k` — sampling rides on the request; the harness sends the Qwen
recipe (temp 0.7, top_p 0.8) via models.yml `compat.extraBody`.
- **Reasoning effort:** the full OpenAI set is accepted (the chat template
has no effort gate).
## Measured
- Boot ~60 s with warm JIT caches (several minutes cold — the first boot
compiles the sgl-kernel + flashinfer kernels; the CUDA 13 toolchain
above is what makes that compile succeed).
- Decode **83.9 tok/s** (no spec decode — nothing to accept).
- Prefill ~2,050–3,370 t/s eager (4-slot shape: a 170,019-token prompt in
50.5 s, ~3,370 t/s; 2-slot shape: a 200,000-token prompt in 97.3 s wall
incl. 8 decode tokens, ~2,056 t/s).
- 4-slot shape: 4 concurrent 54,027-token requests all answered in ~17 s
(216k tokens of live KV at once). 2-slot shape: two concurrent
50,000-token requests both answered (28.8 s wall).
- **Compaction fit (the reslice's purpose):** a 200,000-token prompt —
well past frank-primary's 183,501-token compaction trigger (70% of its
262,144 window) — prefills and completes in ONE request.
- Vision: a 64x64 red square answers "Red" with `image_tokens: 64`.
## Rollback
[[frank-small-gemma4-12b]] — the llama.cpp Gemma4-12B QAT payload and binary
remain intact on disk; its unit/env/serve trio is in `old/` after the
cutover.
# Citations
- Model: https://huggingface.co/letechlead/MiMo-V2.6-Distill-Qwen-9B-INT8-W8A16-AutoRound
- SGLang: https://github.com/sgl-project/sglang
- Serve script: `scripts/serve-frank-small.sh`; tunables: `scripts/frank-small.env`
@@ -1,7 +1,7 @@
---
type: reference
title: "halogen-flash-server on Dankclaw (frank-large)"
description: "The RETIRED frank-large runbook (2026-09-16 → 09-19, rollback target) — peonist-ai/halogen-flash-server 0.5.8 serving Qwen3.8-Flash-Next (w4b) on the Dankclaw gfx1151 box: container shape, deployed flags, the memory model, the client contract, and the failure modes worth knowing. Replaced by [[frank-large-ciru-orca]] on 2026-09-19."
title: halogen-flash-server on Dankclaw (frank-large)
description: The active frank-large runbook — peonist-ai/halogen-flash-server 0.5.8 serving Qwen3.8-Flash-Next (w4b) on the Dankclaw gfx1151 box: container shape, deployed flags, the memory model, the client contract, and the failure modes worth knowing.
tags:
- llm
- halogen
@@ -13,3 +13,466 @@ tags:
- rocm
timestamp: 2026-09-13
---
# halogen-flash-server on Dankclaw (frank-large)
> **ACTIVE again since 2026-09-16, and retuned.** It replaced the llama.cpp /
> kingjones30-ROCmFPX STRIX deployment on 2026-09-11 (see
> [[kingjones-strix-rocmfp4]]), was displaced for two days by ik_llama.cpp (see
> [[frank-large-ik-uncensored]], the current rollback), and came back as the
> shape the fleet asked for: two 200k-token conversations rather than the
> native-context pair. Deployed as a rootless Quadlet container,
> `dankclaw/frank-large/quadlet/frank-large.container`, port 7770. The RTX 3090
> it does not touch now belongs to [[frank-small-qwen38-gsq-rco]].
The engine is a from-scratch serving runtime for the Qwen3.8-Flash-Next
architecture on AMD's gfx1151 (Strix Halo) — the same silicon this host runs.
Upstream's own comparison table measures it at **roughly 4x the prefill
throughput** of the llama.cpp-family runtimes it ships against (EngramHalo.cpp,
ROCmFP4, CIRU-IU4) on a 32K prompt, and prefill is most of the wall clock on any
prompt with real context. That, not decode, is the reason for the swap.
## Shape
One container runs both halves of the stack:
| half | port | reachable |
|---|---|---|
| engine | 8730 | container loopback only — **unauthenticated, never publish it** |
| OpenAI front-end | 8731 | published as host **7770** |
The `all` mode is upstream's default and the shape a single-container host
wants: the front-end talks to the engine over loopback inside the container, so
there is one process tree, one log, and one published port.
`HALOGEN_MODEL_ID=frank-large` sets the id reported at `/v1/models`, in
`/health`, and in every response body. Requests are **never rejected for naming
a different model** — the server serves whatever asks. Keeping the fleet alias
is therefore free, and it means Hermes, the harness config, the OpenWebUI
discovery, the `services.json` probe and the docs needed no rename.
## Weights
`peonist-ai/halogen-qwen3.8-flash-next` (HuggingFace, public and ungated):
| file | size | role |
|---|---|---|
| `qwen38-flash-next-w4b.hgn` | 115.55 GiB | the checkpoint |
| `qwen38-flash-next-w4b.overlay.hgn` | 2.40 GiB | **quality sidecar** — picked up automatically; the engine warns at startup if it is missing. **Refreshed 2026-09-16**: the sidecars are versioned *in place*, so a stale local copy is invisible from its file name — this one had read 2.31 GiB since it was first fetched while the Hub had moved on |
| `qwen38-flash-next-vision.hgn` | 0.84 GiB | vision tower (see below) |
| `tokenizer/` | ~21 MB | flat tokenizer dir; found beside the checkpoint, so no extra mount |
`HALOGEN_DOWNLOAD` fetches the whole repo into the bind mount on **first start
only** — the entrypoint acts only when the checkpoint is absent, so a restart
never re-downloads, and `huggingface_hub` resumes an interrupted pull. The
mount must be read-write for this. Roughly 127 GB; on Dankclaw it lands in
`/home/dank/models/halogen`.
**Refreshing the weights.** Delete the mount's contents (or the whole
directory, then recreate it **empty**) and start the unit: the entrypoint sees
the checkpoint absent and re-fetches the repo, resuming if interrupted. Two
traps. First, the bind mount's source directory must *exist* — podman refuses
the container with `Error: statfs /home/dank/models/halogen: no such file or
directory` and the unit loops on `Restart=on-failure`; `mkdir -p` the empty
directory and the fetch starts on the next start. Second, "refresh" only means
"fetch what the Hub has now": on 2026-09-16 the re-fetch brought newer sidecars
(`overlay.hgn` 2,477,677,120 → **2,572,466,560** bytes, `overlay-speed.hgn`
2,383,306,048 → **2,478,095,488**) while the checkpoint returned
byte-identical in size (124,068,083,904) — so an update can live entirely in
the sidecars, and equal file sizes are not proof of an unchanged repo.
`overlay-speed.hgn` (2.31 GiB on the Hub; 2.22 GiB before the 2026-09-16
refresh) comes along with the repo but is unused: it trades the `o_proj`
calibration for about 2 % of decode, and the quality sidecar is the default for
a reason.
## Deployed flags
Everything else is configured by environment variable — there is no config
file, and the flags are read once at startup. These are the departures from
upstream's defaults:
| flag | value | why |
|---|---|---|
| `HALOGEN_MODEL_ID` | `frank-large` | fleet identity; no client rename |
| `HALOGEN_CTX` | `200192` | **set 2026-09-16**: exactly half the pool, so two conversations of the full window are always resident. Not a round 200,000 — pool/2 is. The model's native window is 262,144, so this is a real reduction in the per-conversation ceiling, and a client asking for more gets a 400 (never a silent truncation). The harness declares 200192 for `frank-large` |
| `HALOGEN_KV_POOL_POSITIONS` | `400384` | **retuned 2026-09-16** (from 401,408): 2 x 200,192. Reserves ~11.0 GiB of KV, confirmed by the boot ledger as `400384 positions, ~27.2 GiB (16.2 GiB of it for everything but the pool, at max_tok 24576)` against a 33.5 GiB device budget — **no clamp**. Slots still oversubscribe the pool for any real request (admission reserves prompt + `max_tokens`), so a near-full pair that is both generating is pool-bound. `HALOGEN_KV_POOL_FIT` guards the boot: read the ledger, not this column |
| `HALOGEN_KV_SLOTS` | `2` | **lowered from 3 on 2026-09-16** — one slot per half of the pool, and two is the fleet's shape now that Dankclaw serves two endpoints. Each slot is 111.0 MiB of O(1) state, so this hands ~111 MiB back as well |
| `HALOGEN_MAX_TOK` | `24576` | **halved from the 32768 default on 2026-09-16** for frank-small, its co-tenant on the same host. The arena's variable term goes `8.40 x 2 → 8.40 x 1.5`, handing ~4.2 GiB back at roughly a 4-5 % prefill cost — the same lever at 16,384 costs 8-9 %. The vendor's own notes call 24,576 the largest arena that allocated with headroom to spare, so it stays inside their tested range. 65536 still cannot boot. It sizes a per-call PREFILL CHUNK, not the prompt ceiling: a 200k conversation is prefilled in arena-sized pieces |
| `HALOGEN_HOST_RESERVE_GIB` | `20` | **raised from 15 with the same retune**, because the arena shrank: `budget = 121.2 − 67.7 − 20 = 33.5 GiB` against a measured need of ~27.2, so the fit check kept ~6 GiB of margin and did not clamp. It is **not** an allocation: raising it cannot return memory to the host, only take the pool away (see the ceiling section below) |
| `HALOGEN_VISION_TOWER` | *unset* | **removed 2026-09-16.** The tower charges 1.97 GiB against the same device budget as the pool and the arena, and the fleet's image path moved to [[frank-small-qwen38-gsq-rco]] (llama.cpp with `--mmproj`). This server refuses image content parts, and `models.yml` declares `frank-large` text-only to match |
| `HALOGEN_DOWNLOAD` | `peonist-ai/halogen-qwen3.8-flash-next` | first-start fetch |
| `HALOGEN_VERBOSE` | `1` | verbose engine logging — the fullest startup account, on permanently so an incident report needs no restart-into-debug |
Everything else is upstream's default, deliberately: prompt cache mode `2`
(two entries per conversation — end-of-system-prompt and end-of-history — which
already covers the shared-prefix case), `HALOGEN_CACHE_INPLACE=1` (the snapshot
stays ~115 MiB at any depth), the speculative drafter `1` (byte-identical at
temperature 0, and it stands down whenever a second conversation is
generating), the quality sidecar, `HALOGEN_ADMIT_CHUNK=0` (a non-zero value
gives up the byte-identity property), and the default `HALOGEN_MAX_TOKENS_CAP=65536`.
## Memory model
Three numbers explain the whole box:
- **~68 GiB pinned weights.** The checkpoint is mapped and registered with the
GPU in place, never copied. The kernel counts the locked pages as reclaimable
file cache, so `free`, `MemAvailable` and every dashboard built on them
**overstate free memory by the size of the model**. The server prints the
corrected figure at startup; believe that line, not Grafana.
- **~28 KiB per KV position** (measured: 262,144 positions = 6,656 MiB of KV,
~7.2 GiB with block scratch), plus the prefill arena. The 2026-09-16 ledger
reads the two together in the engine's own words: `400384 positions, ~27.2
GiB (16.2 GiB of it for everything but the pool, at max_tok 24576)` — so
~11.0 GiB of pool and 16.2 GiB of arena, working slack and (no longer) a
vision tower. The engine's device-side budget stops at roughly 47 GiB on a
128 GB machine *with the weights pinned* — and lower on a machine carrying
more besides this server, which Dankclaw is.
- **`HALOGEN_HOST_RESERVE_GIB`** is what is left for the page cache the lookup
table is read through. Too little and long prompts crawl with the disk busy
and the process in uninterruptible sleep — that is a cache problem, not a
memory problem, and the fix is a *smaller* pool, not a bigger one.
`HALOGEN_KV_POOL_FIT=1` (default) measures that budget at startup and lowers
the pool itself if the configured one will not fit, printing what it chose.
Read those lines on every restart; they are the ground truth for sizing.
**Measured ledger, seven restarts, read live 2026-09-12.** The engine's own
startup account, including three deliberate experiments:
| pool | max_tok | reserve | KV | arena | need | budget | verdict |
|---|---|---|---|---|---|---|---|
| 262144 (baseline) | 32768 | 24 | 7.2 | 20.6 | 29.8 | 29.5 | boots 0.3 over — prints **no** sizing lines |
| 524288 | 16384 | 24 | 14.4 | 12.2 | 28.6 | 29.5 | fits, 0.9 spare |
| 524288 | 32768 | 24 | 14.4 | 20.6 | 37.0 | 29.5 | clamped to 262144, deploy still green |
| 524288 | 65536 | 24 | — | 37.3 | 46.5 | 29.5 | **OOM — will not boot** |
| 524288 | 32768 | **15** | 14.4 | 20.6 | 37.0 | **38.5** | **deployed — both features** |
| 524288 | 32768 | 16 | 14.4 | 20.6 | 37.0 | 37.5 | fits, footprint unchanged — see the ceiling below |
| **400384** | **24576** | **20** | **11.0** | **16.4** | **27.2** | **33.5** | **deployed 2026-09-16 — ledger need 27.2, no clamp** |
| 401408 | 32768 | 15 | 11.0 | 20.6 | 33.4 | 38.5 | 2026-09-13 → 09-16, superseded by the retune |
### The sizing rule
One budget covers the pool, the arena **and** the vision tower together:
```
device budget = host RAM - resident weights - HALOGEN_HOST_RESERVE_GIB
= 121.2 - 67.7 - reserve
reserve 24 -> 29.5 GiB
reserve 15 -> 38.5 GiB
need = KV (28 KiB/position) + arena + vision (1.97 measured)
arena = 3.80 GiB + 8.40 GiB x (HALOGEN_MAX_TOK / 16384)
```
The `121` the engine prints is rounded **down** from `MemTotal 127104060 kB =
121.2159 GiB`, so subtracting the displayed figures gives 29.3 rather than 29.5.
Use the unrounded value. Two of the three terms are fixed hardware and
checkpoint facts; `HALOGEN_HOST_RESERVE_GIB` is the only one you own — which
buys the *fit margin*, not the host's memory. It is a term in this inequality,
not an allocation, and the section at the end of this page shows the live test
that proves it.
Trust the engine's printed requirement over this model wherever they disagree:
a boot clamped at reserve 24 stated `524288 positions need ~35.0 GiB (plus 1.5
of margin)`, i.e. **budget >= 36.5**, against a modelled 37.0 here. Close
enough to plan with, and the authoritative number to cut the other way.
The arena term is **linear in `HALOGEN_MAX_TOK`** and predicts every measured
point to 0.1 GiB — including upstream's three published "on the device" figures
(524,288 → ~35, 786,432 → ~42, 1,048,576 at `max_tok=16384` → ~41), which are
**pool + arena totals at the default `max_tok`**, not pool alone. That is why
their largest pool "needs `HALOGEN_MAX_TOK=16384`": at 32768 a 1M pool would be
49.4. Reading those figures as pool-only is the trap that makes a doubling look
affordable when it is not.
At the baseline reserve of 24 the doubled pool leaves `29.5 - 1.97 - 14.4 =
13.1` for the arena, so `max_tok <= 18,130` and **16384 is that reserve's
ceiling, not a conservative setting.** The corner check agrees: at 32768 only
7.0 GiB is left for the KV, ~254k positions, and the pool drops back toward
262144. Cut the reserve to 15 and the same arithmetic gives `38.5 - 1.97 - 14.4
= 22.1` for the arena — `max_tok <= 35,700`, which is exactly why 32768 now
fits unmodified.
### What the reserve actually costs
The device budget is not the whole story. Memory position by configuration
(401,408 is the 2026-09-13 deployed row, read from its boot ledger):
| config | held | host left | contiguous 2 MiB blocks |
|---|---|---|---|
| 262144 / 32768, reserve 24 | 96.3 | 12.1 GiB | 2081 |
| 524288 / 16384, reserve 24 | 94.6 | 13.8 GiB | 3742 |
| 524288 / 32768, reserve **16** | **103.5** | **7.1 GiB** | 293 |
| **401408 / 32768, reserve 15** | **100.0** | **9.1 GiB** | **1396** |
| **400384 / 24576, reserve 20** | **95.4** | **14.7 GiB** | **475** |
At the doubled setting (2026-09-12) the server held 103.5 of 121 GiB and the
engine volunteered the stall note. It did not print it at the 401,408 trim, and
it prints it again after the 2026-09-16 retune. Three data points, and they do
not line up with a "free memory below X" reading: 310 blocks printed, 1396 did
not, 475 did. So treat the note as "the machine is tight" and read the
`host memory left` line rather than waiting to be told:
```
halogen: NOTE this server now holds most of the machine, and 310 contiguous
2 MiB blocks remain. It runs best on a host of its own. If other large
processes share this machine they will compete for what is left, and when it
runs out BOTH they and this server can stall for minutes at a time at full
CPU with no disk activity and no output, which is not a crash and needs no
restart.
```
That is the failure mode to watch, and it is the least diagnosable of the
three: not a silent clamp, not a boot refusal, but a minutes-long freeze that
looks like a hang, for the neighbours as much as for frank-large. `free` is
useless for spotting it — `MemAvailable` still reads ~74 GiB because the
page cache counts as reclaimable. Watch the `host memory left for everything
else` line and the contiguous-block count at boot instead.
28 co-tenant containers (~4.3 GiB working set) stayed up through the change,
so it is survivable.
### The reserve cannot buy air — ceiling 16
The last row above is the experiment that proves it. Raising the reserve from
15 to 16 left `held` and `host left` **byte-for-byte identical** (103.5 / 7.1
GiB). `HALOGEN_HOST_RESERVE_GIB` feeds the fit-check budget and is *not* an
allocation; the actual footprint is `weights + KV + arena + vision`, none of
which the reserve touches. So the knob has exactly two regimes:
| reserve | budget | vs required 36.5 | effect |
|---|---|---|---|
| 15 | 38.5 | +2.0 | deployed |
| 16 | 37.5 | +1.0 | no change to footprint, thinner margin — pointless |
| 17 | 36.5 | +0.02 | knife edge, inside the noise of the 67.7 term |
| **18** | **35.5** | **−1.0** | **clamps the pool to 262144** |
| 24 | 29.5 | −7.0 | clamps the pool to 262144 |
The 36.5 requirement is the engine's own, read from a clamped boot:
`524288 positions need ~35.0 GiB (plus 1.5 of margin)`. Above 16 the only
thing a bigger reserve can do is take the doubling away.
**To actually free host memory, change the pool or the arena**, and the reserve
then becomes free to rise: `HALOGEN_KV_POOL_POSITIONS=262144` hands back
7.2 GiB from the doubled pool, `HALOGEN_MAX_TOK=16384` hands back 8.4. Both
are one-line edits that the fit check will confirm on the next boot. The
2026-09-13 trim to 401,408 was this remedy applied at half strength —
`HALOGEN_MAX_TOK` untouched, and on the host-left metric it bought +2.0 GiB
with a 4.5x improvement in contiguous blocks (310 → 1396), less than the
modelled 3.4 because the engine holds the freed KV as working slack.
### The `WARNING` line only appears when the fit check had to move
This one cost me a wrong conclusion, so it is worth stating plainly. When the
configured pool already fits, the engine reserves it **and prints nothing** —
the 09-11 baseline boot goes straight from the pre-flight line to
`checkpoint: mapped` with no `kv pool:` sizing block at all. The sizing block and
its `WARNING even 262144 positions ... host RAM cannot spare it` appear **only
after a clamp**.
So the absence of a warning in old logs is not evidence of headroom. Both
`262144/32768` rows above need 29.8 against a 29.5 budget — 0.27 over — and the
baseline has lived in that state since it was deployed without incident,
because the 24 GiB reserve is itself generous (the host reports 12–14 GiB free
at that point). The engine's budget is a conservative floor, not a hard wall.
### Two failure modes, and only one is dangerous
Raising `max_tok` past the ceiling does not shrink the pool — the arena alone
outgrows the budget, and the server cannot allocate at all:
```
kv pool: 524288 positions need ~51.7 GiB ... LOWERING THE POOL TO 262144 (~44.5 GiB).
kv pool: WARNING even 262144 positions (the context, the smallest pool that can
serve one request) needs ~44.5 GiB and host RAM cannot spare it.
dmalloc: FAILED requesting 0.250 GiB after 39.970 GiB in 566 allocations (out of memory)
```
This is the quiet one: the unit stays `active`, the container reports
`Up (starting)`, and `deploy.sh` sits in its health wait for the whole
`LLM_WAIT` rather than failing fast. It confirms upstream's warning that a
large `HALOGEN_MAX_TOK` means "the server will not start", not "it will be
slower".
Under-running the ceiling is far more benign and far easier to miss. At 524288
with the arena back at 32768, `HALOGEN_KV_POOL_FIT` lowered the pool and
`deploy.sh` still reported healthy in 12 seconds:
```
kv pool: 524288 positions need ~35.0 GiB (plus 1.5 of margin) and host
RAM cannot spare it. LOWERING THE POOL TO 262144 (~27.8 GiB).
```
A green health check does not mean the pool you asked for is the pool you got —
read the `kv pool:` lines after every restart.
The 47.7 GiB n-gram lookup table is never held in RAM; it is read through
the file cache. The 2.0 GiB the firmware carves for the iGPU appears in no
`/proc/meminfo` figure at all.
**Co-tenancy.** `HALOGEN_FLASH_PIN_TRUNK=1` (default) is what the published
decode numbers were measured with, and it means this container holds most of
the host. If a co-tenant then takes the remainder, both it and the engine can
stall for minutes at a time at full CPU with no disk activity and no output.
That is documented behaviour, not a crash, and it needs no restart.
`HALOGEN_FLASH_PIN_TRUNK=0` gives the memory back and costs several times the
decode speed — a last resort, not a tuning option.
## Client contract
The differences from llama.cpp that bite are all in the request, not the
deployment:
- **No server-side sampler defaults.** `temperature` absent or `0` is
**greedy** decode; above 0 the request samples on the same drafter. Supported
fields: `temperature`, `top_p`, `top_k`, `min_p`, `seed`,
`presence_penalty`, `frequency_penalty`, `logit_bias`, `logprobs`. Refused
with a 400: `top_logprobs`, `logprobs` with `stream: true`, `n > 1`, and any
value outside its defined range (values are refused, never clamped).
The fleet runs greedy for clients that stay silent — deterministic, and
byte-identical with the drafter.
- **The token budget covers thinking.** The default is **8192**, and a budget
that runs out mid-thought returns `finish_reason: "length"` with an **empty
`content`** and the partial reasoning in `reasoning_content` — which most
clients do not display. Above the cap (`HALOGEN_MAX_TOKENS_CAP`, 65536) a
request is a 400 rather than a silent truncation. `max_tokens`,
`max_completion_tokens` and `max_output_tokens` all work and must agree if
more than one is sent.
- **A budget above (window − compaction-threshold) is a guaranteed 400 zone.**
The fit check (`prompt + max_tokens <= HALOGEN_CTX`) refuses, and the harness
only compacts at its own threshold — with OMP at 70 % of a 200,192 window
(140,134), any prompt in (136,192, 140,134] with a 64,000 budget overflows
the window while sitting below the compaction trigger. That collided live on
2026-09-17 (prompt 138,898 + 64,000 = 202,898 > 200,192). The fix is
harness-side: keep the declared `maxTokens` at or under
`window − threshold` (57,344 chosen) so no pre-compaction request can miss
the fit check. Do not fix it by raising `HALOGEN_CTX` past pool/2 — that
breaks the two-resident-conversations property.
- **`reasoning_effort`** is accepted at the top level and inside
`chat_template_kwargs`: `minimal`, `low`, `medium`, `high`, `xhigh`. The
model's default is `xhigh`. `minimal` aliases the template's `low` and still
reasons; `enable_thinking: false` turns thinking off; `preserve_thinking` is
honoured. `preserve_reasoning` is a **400** — it is the llama.cpp-era key.
- `/v1/models`, `/health` and completions all report the served id, and
`reasoning_content` carries the reasoning trace.
**Pool admission is the one arithmetic trap.** A request reserves its prompt
**plus** `max_tokens` positions when it is admitted; if the pool cannot hold it
the request waits in arrival order, and after the queue timeout (3600 s) it
gets a `503 engine_busy`. A prompt large enough that prompt + budget exceeds
the pool can therefore never be admitted at all. The 2026-09-16 shape is a
400,384-position pool with `HALOGEN_CTX` 200,192 and two slots: two
conversations at the ceiling fit the pool exactly, so a pair that is both
near-full and both generating is pool-bound — the second waits for the first to
release its region. The pool binds **how many** conversations stay resident,
not how long one may be; the older 524,288 / 401,408 numbers live in the ledger
tables above.
## Vision
**None here since 2026-09-16.** `HALOGEN_VISION_TOWER` is deliberately unset:
the tower is a 1.97 GiB charge against the same device budget as the pool and
the arena, and the fleet's image path moved to [[frank-small-qwen38-gsq-rco]],
which loads the BF16 projector alongside its own weights. This server refuses
image content parts and says why, rather than ignoring them:
```json
{"error": {"message": "this server does not accept images: the engine was
started without a vision tower (HALOGEN_VISION_TOWER)", "type":
"invalid_request_error"}}
```
The llama.cpp side handles images the same way this engine used to: a `data:`
URL or bare base64, about 2,040 tokens of context per image, and `http(s)` URLs
refused deliberately (fetching one would make the server issue outbound
requests to wherever a client pointed it). Audio and video have no path
anywhere in the fleet — that left with [[frank-npu]].
## Deploy and operate
```bash
./scripts/deploy.sh dankclaw --service frank-large
```
The handler retires the ik-era **root** unit first (stop, disable, move
`/etc/systemd/system/frank-large.service` into
`~/.AGENTTRASH/20260916-halogen-restore/host-units` — never `rm`; this host's
`disable` may delete the file outright, which the handler now reports), stops
the Quadlet's own unit if it is running, then pulls
`ghcr.io/peonist-ai/halogen-flash-server:0.5.8`, re-tags it to the
`localhost/` alias the unit references, and **waits for port 7770 to be free**
before installing and starting anything.
That last gate is not paranoia. On the first cutover attempt the ik server
logged "Deactivated successfully", and pasta — rootless podman's userspace
network stack, which binds the published port at container CREATE — still
reported `Address already in use` a second later, exiting the unit with code
126. Only `Restart=on-failure` recovered it, minutes later. A deploy that
starts a doomed container has not deployed anything, so `wait_port_free` polls
every socket on the port (listener, accepted, TIME_WAIT) and fails loudly with
the socket table if it never clears.
Boot persistence comes from `[Install] WantedBy=default.target` in the unit
file plus linger on the deploy user — generated units **cannot** be
`systemctl --user enable`d on this host.
```bash
systemctl --user status frank-large.service # the generated unit
podman logs frank-large | head -40 # version banner + memory ledger
curl -s http://127.0.0.1:7770/health # 200 only after the engine PONGs
curl -s http://127.0.0.1:7770/v1/models
```
`/health` asks the **engine** for a PONG before answering, so a 200 means
"ready to serve", not merely "process alive". During the first-start download
it stays unhealthy by design.
## Troubleshooting
| symptom | cause |
|---|---|
| `dmalloc: FAILED requesting … (out of memory)` then `HIP … out of memory` | the KV pool did not fit. `HALOGEN_KV_SLOTS` will not fix it (slots share the pool); lower `HALOGEN_KV_POOL_POSITIONS` to 262144, then `HALOGEN_MAX_TOK` to 16384 (~9 % prefill) |
| starts, answers short prompts, collapses to a few tok/s on a long one, disk busy, process in uninterruptible sleep | short of **file cache**, not memory — lower the pool and/or raise `HALOGEN_HOST_RESERVE_GIB` |
| long replies that look cut off | read `finish_reason`: `stop` means you have the whole answer, `length` means you ran out of budget (thinking counts) |
| a request that never returns, then `503 engine_busy` | the pool could not reserve prompt + `max_tokens`; see the admission trap above |
| both the engine and a co-tenant stall for minutes at full CPU | the pinned-trunk trade; see Memory model |
| `free`, `MemAvailable`, Grafana all wrong by ~68 GiB | expected — locked weights are counted as reclaimable |
`HALOGEN_VERBOSE=1` ships in the unit, so the fullest startup account is
already in the log when something goes wrong. `HALOGEN_DMALLOC_LOG` is
deliberately **not** set: it logs every allocation over 64 MB, which is
steady-state noise on a shared host — raise it only for a live OOM report.
The lines worth grepping first:
```bash
podman logs frank-large 2>&1 | grep -E '^(dmalloc|kv pool):'
```
Retrieval: `podman logs frank-large` covers the **current** instance only —
the Quadlet runs `--replace --rm`, so everything before the last recreate is
gone from the container log. `journalctl --user -u frank-large.service` is
the durable record. Both are rootless: `sudo podman logs frank-large` looks
in root's storage and answers "no such container".
## Rollback
The predecessor is intact: the ik payload stays at
`/home/dank/models/mradermacher-Qwen3.8-Flash-Next-Uncensored-i1-Q4_K_M`, the
ik build at `/home/dank/GitPackages/ik_llama.cpp/build`, and its unit, env,
serve script and the Qwen-Sharp template are archived in the repo under
`scripts/.AGENTTRASH/*.ik-llama.cpp` and `*.ik-llama-qwen-sharp`. Rolling back
is a `git revert` of this change set plus a deploy — **but the Quadlet must be
removed from `~/.config/containers/systemd/` first**, or the restarted root
unit and the still-installed container both claim port 7770. The port gate in
the handler now covers exactly that race. See [[frank-large-ik-uncensored]].
The `amd_iommu=off` kernel argument that came with this change is separate and
reverts on its own — see [[dankclaw-iommu-translation-off]].
## Citations
- [peonist-ai/halogen-flash-server](https://github.com/peonist-ai/halogen-flash-server) — README, `docs/FLAGS.md`, `deploy/entrypoint.sh`, `docker-compose.yml`, CHANGELOG (v0.5.8)
- [peonist-ai/halogen-qwen3.8-flash-next](https://huggingface.co/peonist-ai/halogen-qwen3.8-flash-next) — weights and file inventory
- [Qwen/Qwen3.8-Flash-Next](https://huggingface.co/Qwen/Qwen3.8-Flash-Next) — base model
+17 -13
View File
@@ -1,17 +1,21 @@
# LLM Fleet — Knowledge Base
Documentation for the LLM inference fleet on the two hosts (2026-09-30):
Documentation for the LLM inference fleet on the two hosts (2026-10-01):
**Dankserver runs the tcclaviger RDNA4 vLLM fork on frank-primary** (the
digest-pinned `tcclaviger/vllm` image driving `podman run` directly, serving
Intel/GLM-5.3-Flash-W4A16-AutoRound — symmetric int4 group 128 — across both
Radeon AI PRO R9700s on :7770, TP=2 with the expert set offloaded to 73.64 GiB
of pinned host RAM per rank behind a 14.51 GiB VRAM LRU arena; 131,072 ctx,
bf16 KV, vision and tool calls on, measured 9.9-10.0 tok/s decode), and
Dankclaw runs two llama.cpp endpoints —
stock llama.cpp (unsloth b11030, ROCm gfx1151; frank-large, unsloth
Qwen3.8-27B UD-Q8_K_XL + the z-lab DFlash2 Q4_K_M drafter on the gfx1151
iGPU, port 7770) and mainline llama.cpp (frank-small, HauhauCS Gemma4-12B
QAT Q4_K_M with MTP and vision on the RTX 3090, port 7771).
orcarouter/Qwen3.8-Flash-Next-Uncensored-FP8 across both Radeon AI PRO R9700s
on :7770, TP=2 with automatic tiered-expert offload, **4 seqs x 262144 ctx
(the model's full native window)**, fp8 KV (5 boot but leave no runtime
headroom; 6 do not fit), no speculative decode, MNBT 1024, MoE gather 32x64, util 0.98,
reasoning/tool parsers wired (qwen3 / qwen3_xml) with preserve_thinking on,
measured 36.4-39.4 tok/s decode — the 2026-10-01 bf16 no-spec cutover plus
the night ladder; rollback frank-primary-fp8-mtp-20261001), and Dankclaw
runs two endpoints —
gufo v0.1.1 (the Strix Halo engine, built from source; frank-large,
unsloth Qwen3.8-27B UD-Q4_K_XL (vanilla) + the z-lab DFlash2 Q4_K_M drafter
on the gfx1151 iGPU, 4 x 163840 ctx with f16 KV, port 7770) and mainline llama.cpp (frank-small,
HauhauCS Gemma4-12B QAT Q4_K_M with MTP and vision on the RTX 3090,
port 7771).
> 2026-08-22: the former `vllmScripts` repository is merged into the
> serverAppConfigs repository. This knowledge base moved from the old repo's
@@ -27,9 +31,9 @@ graph LR
gfx1201, 32 GiB each]
B2[tcclaviger RDNA4 vLLM fork, digest-pinned
podman run, frank-primary, port 7770]
C[GLM-5.3-Flash W4A16 int4
TP=2, expert offload 73.64 GiB/rank pinned,
14.51 GiB LRU arena, 131072 ctx, vision, tools]
C[Qwen3.8-Flash-Next FP8 bf16 no-spec
TP=2, expert offload automatic, 4 x 262144 ctx,
fp8 KV, MNBT 1024, gather 32x64, qwen3 parsers]
end
subgraph Dankclaw[AMD Strix Halo - Ubuntu 26.04]
+9 -3
View File
@@ -269,10 +269,16 @@ The LLM inference fleet on the two hosts. Full index:
- [[ciru-activefpx-promptforge]] — the RETIRED v3 CIRU PromptForge runtime on Dankclaw (superseded 2026-08-24)
- [[kingjones-strix-mtp]] — the kingjones Qwen3.8-27B ROCmFP4 STRIX MTP model on Dankclaw (active)
- [[dealign-ornith-crack]] — the retired Ornith-1.5-35B-A3B CRACK model on Dankserver (retired 2026-09-02)
- [[frank-small-gemma4-12b]] — the ACTIVE frank-small runbook since
2026-09-17: mainline llama.cpp serving
- [[frank-small-sglang-mimo-v26]] — the ACTIVE frank-small runbook since
2026-10-01: SGLang in a self-contained python3.12 venv serving
letechlead/MiMo-V2.6-Distill-Qwen-9B-INT8-W8A16-AutoRound (qwen3_5
hybrid, INT8 W8A16, in-checkpoint vision, NO MTP weights shipped) on
Dankclaw's RTX 3090, port 7771 — fp8 KV, pinned 606,208-token pool,
4 x 151,552 slots, bf16 mamba states, eager prefill
- [[frank-small-gemma4-12b]] — RETIRED 2026-10-01 (rollback target):
mainline llama.cpp serving
HauhauCS/Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced at Q4_K_M
(MTP assistant sidecar + ngram-mod, q8_0 KV, --fit → 262k) on
(MTP assistant sidecar + ngram-mod, q8_0 KV) on
Dankclaw's RTX 3090, port 7771
- [[frank-small-vllm-gemma4]] — RETIRED 2026-09-19 (same-day revert,
rollback target): vLLM serving google/gemma-4-12B-it-qat-w4a16-ct (w4a16
+213
View File
@@ -662,3 +662,216 @@
- `/dankclaw/pihole/sysctl/99-dnsmasq.conf` — Repo source of truth for `ip_unprivileged_port_start=53`; `deploy_pihole` stages conflicting drop-ins, comments out the stale sysctl.conf line, and applies `sysctl --system` (the boot code path).
- `/tests/caddy_quadlet.bats` (new) + caddyfile/deployment_flow/pihole seams — quadlet boot persistence, self-healing, network, env, and sysctl coverage.
- `/serverAppConfigs-docs/Infrastructure/Caddy.md`, `/serverAppConfigs-docs/Infrastructure/Pi-hole.md`, `/serverAppConfigs-docs/Dankclaw/Dankclaw Stack.md`, `/serverAppConfigs-docs/Dankclaw/Gitea.md`, `/serverAppConfigs-docs/Architecture/Deployment Flow.md` — quadlet runtime facts, the 2026-08-26 incident, the sysctl-conflict failure mode, canonical Caddy ownership.
## 2026-10-01 — frank-primary RESTORED to fp8 3 x 262144 (bf16 boot fails)
bf16 (--kv-cache-dtype auto) at 2 x 262144 did not stay up, with OR without
--expert-precise-memory:
- with precise: NRestarts 1->3, each attempt ~6.7 min then
`Deactivated successfully` (API server drains after an EngineCore fatal
error) — cause not captured, the serve script rm'd the container.
- without precise (default 7.60 GiB overhead, arena 14.3 GiB): NRestarts
climbing, container `Exited (1)`, and the journal finally showed the real
error:
`RuntimeError: Worker failed with error 'Constraints violated
(L['query_start_loc'].size()[0])! You marked L['query_start_loc'].size()[0]
as dynamic but your code specialized it to be a constant (3)'`
— a torch.compile/dynamo dynamic-shape constraint violation, NOT an OOM.
`~/.cache/vllm` holds only `modelinfos` (16K) and each `podman run` gets a
fresh container filesystem, so a stale compile cache is ruled out: the
conflict is produced by this configuration's own compile path.
Differences from the last shape measured serving (fp8 3 x 262144, MNBT 2048,
KV 6.1e9 -> 792,069 tokens / 3.02x / arena 6,248 / 3.59 GiB free): KV dtype
(fp8 -> bf16) and SEQS (3 -> 2). Both are candidates for the dynamo trigger;
`--enforce-eager` is the bypass that would sidestep the constraint path.
Restored: fp8 3 x 262144, MNBT 2048, KV_BYTES 6,100,000,000, no precise flag.
Next: bisect bf16 vs SEQS in a window (bf16 + SEQS=3 isolates the dtype).
## 2026-10-01 — frank-primary: --expert-precise-memory + bf16 = boot crash loop
**Reverted.** The two changes Frank asked for were applied together and the
result crash-looped: `NRestarts` climbed 1 -> 2 -> 3, each attempt running
~6.7 minutes then logging `Deactivated successfully` (vLLM's API server drains
and exits 0 after an EngineCore fatal error, so `podman wait` returns 0; the
new `Restart=always` turned a silent death into a visible loop).
The budget arithmetic explains it without needing the error text, because the
arena is DEVICE-resident (the fp8 3-window shape's plan predicts 28.27 GiB and
that is exactly what `rocm-smi` measured):
| line | bf16 2 x 262144 + precise | fp8 3 x 262144 |
|---|---|---|
| non-expert weights | 6.28 | 6.28 |
| pinned pool | 6.80 | 5.68 |
| CUDA graphs | 0.55 | 0.55 |
| arena | 16.65 (precise: overhead 5.25) | 14.31 (default: overhead 7.60) |
| non-torch | ~1.45 | ~1.45 |
| **total** | **31.73 of 31.86 GiB** | 28.27 (measured) |
| free at boot | **~0.13 GiB** | 3.59 |
`--expert-precise-memory` hands the 2.35 GiB compile/graph-capture headroom to
the arena, and bf16 simultaneously adds 1.08 GiB of pinned pool; together they
put graph capture ~0.13 GiB from the ceiling, where every transient allocation
dies. So the flag is dropped and bf16 2 x 262144 ships with the default
overhead: arena 14.31 GiB, ~2.4 GiB free at boot.
**Lesson:** the registry's "compile headroom" is not slack to be reclaimed by
default — it is the budget for the phase that allocates last. Reclaim it only
by paying for it elsewhere (smaller pool, fewer sessions, or a shorter context).
## 2026-10-01 — frank-primary: 2 bf16 windows + --expert-precise-memory
Frank's final shape for the night. Two changes at once, both measured in
principle before the boot:
- **KV is bf16 (`--kv-cache-dtype auto`), two full-size windows (2 × 262144).**
bf16 measures **13,839 B/token** (from the bf16 3×241664 boot:
11,047,010,304 B -> 798,280 tokens), decomposing as **12,276 attention +
1,563 mamba/side caches** against fp8's **6,138 + 1,563 = 7,701**. So
524,288 tokens needs 7.256e9 B; pinned at 7,300,000,000 (~527,500 tokens,
3,206 margin). Cost: the pool goes 5.68 -> 6.76 GiB per rank.
- **`--expert-precise-memory`.** The registry's default overhead for this
architecture is 7.60 GiB = the fitted 5.25 GiB (gfx1201 TP2
nbt4096/seqs16/len262144) + 2.35 GiB of compile/graph-capture headroom.
The flag selects the fitted figure, which moves only the plan's `room` term
— arena 6,248 -> ~7,278 slots (~1,025 more, at 2.344 MiB/slot) — at the
cost of boot-time capture slack. The overhead formula adds 0.22 GiB per
1024 nbt above 4096, so MNBT 2048 pays nothing.
Budget note worth keeping: the arena is `(budget - non_expert_weights -
kv_reserve - graphs - overhead) // expert_bytes`, where `kv_reserve` is the
planner's OWN one-max-model-len reserve (2.48 GiB at TP2) and does NOT scale
with SEQS. The pinned `--kv-cache-memory-bytes` therefore does not shrink the
planned arena; it comes out of free VRAM instead.
## 2026-10-01 — frank-large: Q4_K_XL payload + 4 x 163840 sessions
Frank's call. Payload swapped from ajgazin's **abliterated** Swift-1.5
UD-Q8_K_XL (29.3 GiB) to **unsloth/Qwen3.8-27B-GGUF UD-Q4_K_XL** (16.35 GiB,
sha256 3f227079…b01e, vanilla/Apache-2.0 — the endpoint is no longer
uncensored). New fetcher `scripts/download-frank-large-q4.sh`; the DFlash2
drafter and its fetcher are unchanged.
Shape: **`--sessions 4 --context 163840`** with unquantized KV. gufo has no
KV-quantization lever at all (`execution_policy.hpp` pins `kv_cache_storage`
to `kFp16`), so "unquantized" is inherent.
KV arithmetic (why this fits where one 262144 session used to sit):
f16 KV costs **64 KiB/token** — 16 full-attention layers (the hybrid is
`full_attention_interval: 4` over 64 layers) x 4 KV heads x 256 head_dim x
2 (K,V) x 2 bytes; the other 48 layers are linear-attention with a
per-SEQUENCE fp32 state (~144 MiB), not a per-token cache. 4 x 163840 =
655,360 tokens = 40.0 GiB of KV, and each session is exactly 10 GiB. Budget:
weights 16.35 + KV 40.0 + drafter 1.07 + linear state 0.56 + runtime ~4 =
~62 GiB against the 114 GiB GTT.
## 2026-10-01 — e2e gate flakiness (12-crawl) — do not panic at the banner
`specs/12-crawl.spec.ts:23` ("every user open link reaches its app") failed the
deploy gate twice and then passed cleanly on a manual re-run:
- run 1 (deploy): `Expected "plex.franksdank.cloud"` / `Received "app.plex.tv"`
— Plex redirects its web UI to the hosted app; the same failure appeared on
the previous deploy too.
- run 2 (manual): `page.goto: net::ERR_ABORTED at https://www.franksdank.cloud/`
— the homepage answered `http=200` in 40 ms from the dev box at the same
moment, so this is a browser-level flake.
- run 3 (manual): **33 passed**, exit 0.
So a red gate on this spec alone is NOT proof the fleet is broken, and the
deployer's `DEPLOY INCOMPLETE` banner can be raised by a flake. Re-run
`tests/e2e/run.sh` before treating it as real; the Plex redirect is the one
stable underlying issue and it lives in Plex's web-client/image config, not in
any repo service.
## 2026-10-01 — frank-primary bf16 no-spec cutover
- `/scripts/frank-primary.env` — bf16 no-spec cutover, FINAL shape after the
night ladder: MAXLEN **241664** x SEQS 3, KV_BYTES **10,184,000,000**/rank,
KV_DTYPE auto (bf16), MNBT 1024, GATHER CHUNKS=32/LANES=64, UTIL 0.98;
FRANK_PRIMARY_SPEC deleted (no spec). Engine measured at the winner:
"KV cache size: 732,359 tokens, Maximum concurrency for 241,664 tokens per
request: 3.03x".
- **The night ladder (Frank's method).** 262144 OOMed at CUDA graph capture
(`Tried to allocate 76.00 MiB ... 0 bytes free`, 30.43 GiB of 31.86 GiB
allocated by PyTorch) and 245760 OOMed identically; **237568 PASSED**
(KV 718,606 tokens) and the +4096 bonus step **241664 PASSED and is
PRODUCTION**. 241,664 is max possible on this box at util 0.98 — the
model's native 262,144 does not fit with a 3-seq contract. Every rung was
booted under a transient systemd unit at uid dank with
`LimitMEMLOCK=infinity` (the rootless bench probe masked the production
memory environment) with full engine-log capture.
- **Util stays 0.98.** The earlier 0.90 edit was wrong — lowering
`--gpu-memory-utilization` shrinks the engine's own budget rather than
buying slack; Frank forbade it and the winning ladder ran at 0.98.
- `/scripts/serve-frank-primary.sh` — `--speculative-config` line removed;
`--max-num-batched-tokens` and the `-e R4D_LRU_GATHER_CHUNKS/LANES`
container-env passthrough added; shape header rewritten.
- `/tests/frank_primary_unit.bats` — seam re-pinned: bf16-KV-present,
spec-absent-by-measurement, gather-32x64-present, MNBT-1024 tests; the
qualified-shape and flags tests flipped to the new env keys.
- Overnight redo campaign (prefetch OFF everywhere) tabled in
`/serverAppConfigs-docs/LLM/dankserver-qwen38-fp8-expert-offload-tuning.md`
with the 2026-10-01 cutover section: gather 32x64 +18.7%, MNBT flat
1024-4096, KV pool law (7,926 fp8 / 14,047 bf16 B/token), arena flat zone,
six-slot refusal, bf16 3x262144 boot failure root cause (CUDA OOM at
KV_BYTES 11.3e9; boots clean at 11.047e9 — captured from journald `-o json`).
- `/AGENTS.md` — fleet table frank-primary row rewritten to the bf16 shape.
- `/serverAppConfigs-docs/LLM/index.md` — fleet intro + mermaid node
updated out of the GLM era.
- **Client contract fixed (thinking + tools).** The live endpoint returned a
null `reasoning` field and dumped the thinking text INLINE in `content`
with a dangling `</think>` (measured: `'We need answer…Brief.\n</think>\n\n391'`)
— the malformed thinking block clients choke on — because the deployed argv
had no `--reasoning-parser`. The GLM rollback (`d91379d`) had dropped all
three contract flags and the qwen rollback inherited the gap. Restored from
`ecaad36`'s values, confirmed against this fork's registries:
`--reasoning-parser qwen3`, `--enable-auto-tool-choice
--tool-call-parser qwen3_xml`, `--default-chat-template-kwargs
'{"enable_thinking": true, "preserve_thinking": true}'`. The seam's
"NO tool dialect" test is flipped to a PRESENT test.
- **Final shape (Frank's call): 5 seqs x the full native 262144 window at
fp8 KV.** 6 x 241664 at fp8 died (`Tried to allocate 10.70 GiB`, 9.18 GiB
free) — six full-length contexts do not fit at any KV dtype — so the
contract moved to five FULL windows: 5 x 262144 fp8 PASSED on the first
rung, KV_BYTES 10,388,766,720/rank, measured **1,350,182 tokens /
5.15x concurrency** (39,462 tokens of margin). Seam re-pinned; the bf16
three-context shape (241,664, KV 732,359 / 3.03x, measured earlier the
same night) is the documented max at 3 contexts.
- Harness `/home/blank/.omp/agent/models.yml` — contextWindow back to 262144
with the five-window fp8 shape (compaction gap 183,501 + 36,864 = 220,365
<= 262,144) and
`preserve_thinking` moved from a bare top-level body field to
`chat_template_kwargs` (the form vLLM actually reads).
- **Runtime-survivability correction: five slots -> FOUR.** 5 x 262144 fp8
passed every boot gate (KV 1,350,182 tokens / 5.15x) but left 0 bytes free
at runtime; a real client request (995-token prompt, `max_tokens=261149`,
sampling params straight from models.yml) killed Worker_TP1 with
`torch.OutOfMemoryError: Tried to allocate 50.00 MiB ... 0 bytes free` and
the engine shut down. Boot is not proof of runtime survivability — after a
knife-edge shape change, send a large-`max_tokens` request before calling it
done. FOUR slots x 262144 fp8 (KV_BYTES 8,311,013,376/rank) returns ~1.93
GiB per rank for activations/graph capture. Frank's call 2026-10-01.
- `/scripts/frank-primary.service` — **Restart=always, not on-failure** (plus
`StartLimitIntervalSec=0` and `OOMScoreAdjust=-500`). A runtime worker fault
makes vLLM's API server exit CLEAN, so ExecStart returned 0, systemd logged
"Deactivated successfully", and on-failure NEVER fired: the endpoint stayed
down until a human noticed. An explicit `systemctl stop` still wins, so
bench windows and deploys are unaffected.
- **Final shape (Frank's call, 2026-10-01): 3 x 262144, pool at the FLOOR,
MNBT 2048, rest to the arena.** MAXLEN 262144 x SEQS 3 = 786,432 tokens of
contract; measured fp8 costs 7,698 B/token, so 6.054e9 B is the pool floor
and the deployed 6,100,000,000 B leaves a ~5.9k-token margin while handing
the remaining ~2.2 GiB (versus the 4-slot shape) to the expert arena — the
decode-critical cache the fork sizes from the remainder. MNBT 2048 costs the
arena nothing (the sweep measured 6,499 slots at every rung <= 4096).
- **DCP investigated and closed** (see the parallelism survey in the runbook):
`--decode-context-parallel-size 2` is rejected at boot — DCP for GQA requires
TP > the model's KV heads (2), i.e. TP >= 4, i.e. four GPUs. Not a tuning
knob on this box.
- Production bring-up: the shape boots and serves on :7770 — engine log
verified (KV cache size, concurrency, MNBT 1024, gather 32x64) plus live
contract probes (reasoning split, tool_calls). Rollback target for the
2026-09-29 fp8+MTP4 shape: git tag `frank-primary-fp8-mtp-20261001`.
+2 -2
View File
@@ -303,8 +303,8 @@
"section": "AI",
"details": {
"role": "Fast utility model",
"spec": "Gemma4-12B QAT (Q4_K_M, 7.4 GiB) — 1M-token pool across four conversations; fastest at images.",
"inputs": ["text", "image", "audio"],
"spec": "MiMo-V2.6-Distill-Qwen-9B (INT8 W8A16, 12 GiB) on SGLang — 606k-token pool across four 151k-token conversations; 84 tok/s decode; sees images.",
"inputs": ["text", "image"],
"use": "Agentic search, RAG, research subagents, translation, roleplay, and summarization — any small task that doesn't need much intelligence."
},
"url": "",
+15 -11
View File
@@ -19,13 +19,13 @@ load helpers
ENV_FILE="$REPO_ROOT/scripts/frank-large.env"
UNIT="$REPO_ROOT/scripts/frank-large.service"
SERVE="$REPO_ROOT/scripts/serve-frank-large.sh"
FETCH="$REPO_ROOT/scripts/download-frank-large-swift.sh"
FETCH="$REPO_ROOT/scripts/download-frank-large-q4.sh"
DRAFTER_FETCH="$REPO_ROOT/scripts/download-frank-large.sh"
BUILD="$REPO_ROOT/scripts/build-gufo.sh"
REMOTE_DEPLOY="$REPO_ROOT/scripts/deploy-remote.sh"
# The deployed target's filename, kept here so a rename in the env file and a
# rename in this stub cannot drift apart unnoticed.
TARGET_STUB="Swift-1.5-Qwen3.8-27B-Uncensored-Dynamic-MTP-UD-Q8_K_XL.gguf"
TARGET_STUB="Qwen3.8-27B-UD-Q4_K_XL.gguf"
setup() {
STAGE="$(mktemp -d)"
RUNTIME_DIR="$STAGE/gufo"
@@ -144,8 +144,10 @@ argv_value() {
[ "$(argv_value --served-model-name)" = "frank-large" ]
[ "$(argv_value --host)" = "0.0.0.0" ]
[ "$(argv_value --port)" = "7770" ]
[ "$(argv_value --context)" -eq 262144 ]
[ "$(argv_value --sessions)" -eq 1 ]
# 2026-10-01: four sessions x 163840 context (Frank's "4x 160k"), f16 KV.
# 163840 tokens x 64 KiB/token = 10 GiB of KV per session exactly.
[ "$(argv_value --context)" -eq 163840 ]
[ "$(argv_value --sessions)" -eq 4 ]
[ "$(argv_value --speculative)" = "dflash2" ]
[ "$(argv_value --draft-tokens)" -gt 0 ]
[ "$(argv_value --draft-policy)" = "adaptive" ]
@@ -167,11 +169,12 @@ argv_value() {
@test "frank-large stays text-only" {
# The payload has no mmproj, so an --mmproj would point at nothing. The
# fleet's image path is frank-small; models.yml declares frank-large
# text-only.
# fleet's image path is frank-small: its SGLang MiMo payload carries the
# vision tower inside the checkpoint (no projector file at all), and
# models.yml declares frank-large text-only.
serve_argv
! argv_has --mmproj
grep -q -- '--mmproj' "$REPO_ROOT/scripts/serve-frank-small.sh"
grep -q 'MiMo-V2.6-Distill-Qwen-9B-INT8-W8A16-AutoRound' "$REPO_ROOT/scripts/frank-small.env"
}
@test "the engine is asked for greedy decoding and for preserved prior reasoning" {
@@ -221,7 +224,7 @@ argv_value() {
# so a plain grep stayed green after the URL was repointed at another
# repository -- the script would then download something the serve script
# never asked for.
grep -qE '^URL="https://huggingface\.co/ajgazin/Swift-1\.5-Qwen3\.8-27B-Uncensored-Dynamic-MTP-GGUF/resolve/main/' "$FETCH"
grep -qE '^URL="https://huggingface\.co/unsloth/Qwen3\.8-27B-GGUF/resolve/main/' "$FETCH"
grep -qE 'https://huggingface\.co/z-lab/Qwen3\.8-27B-DFlash2-GGUF/resolve/main/' "$DRAFTER_FETCH"
for f in "$FETCH" "$DRAFTER_FETCH"; do
# -f so an HTTP error is a failure rather than a small "artifact";
@@ -251,9 +254,10 @@ argv_value() {
}
@test "the drafter is still fetched by the script that carries its Hub repo" {
# Guards a future "simplification" that folds the drafter into the Swift
# script and silently orphans the artifact the serve script still points
# at via DRAFTER_DIR.
# Guards a future "simplification" that folds the drafter into the
# payload-fetch script and silently orphans the artifact the serve script
# still points at via DRAFTER_DIR. The literal drafter name must not
# appear in that script AT ALL, comments included.
grep -q 'Qwen3.8-27B-UD-Q8_K_XL' "$DRAFTER_FETCH"
! grep -q 'DFlash2' "$FETCH"
}
+126 -55
View File
@@ -2,25 +2,24 @@
# Seam: frank-primary — the Dankserver LLM endpoint on :7770.
#
# This file asserts the tcclaviger RDNA4 vLLM ROOT-UNIT shape (the
# 2026-10-01 rollback to Qwen3.8-Flash-Next-Uncensored-FP8 + MTP4, which
# reversed the failed GLM/DFlash2 experiment): the serve script drives
# `podman run` DIRECTLY (the image entrypoint execs `vllm serve`), with every
# engine flag qualified by boot probe and carried in the repo env file. The
# seam pins what the flags alone do not say: the KV qualification law
# (7.2 GiB/rank boots at 729,545 tokens / 3.65x concurrency; 9 GiB and 16 GiB
# both OOM the worker — 4 full-length 200k contexts do NOT fit), the fp8-KV
# qualification (e4m3 for BOTH K and V — the stock flag quantizes them
# together), the automatic-offload law (the fork plans the tiered-expert
# offload itself; no flag exists to set), the self-healing law (the run
# returns before the engine is up, so the serve script must wait on the
# container for Restart=on-failure to mean anything), the memlock law that
# makes the pinned host rows legal, the deployer's image/payload gates with
# the false-green MainPID check, and the measured laws: expert prefetch
# ABSENT (36% precision, costs ~40-51% decode — deleting the flag moved
# decode 26.8 -> 40.6 tok/s), MTP4 PRESENT (37.4-40.6 tok/s at 54% acceptance
# vs the 12.11 tok/s no-spec baseline; the earlier "MTP buys zero" reading
# carried the prefetch tax), and NO tool dialect (the GLM era added
# --enable-auto-tool-choice; the 2339fae trio does not serve tools).
# 2026-10-01 BF16 cutover, the overnight redo campaign's verdict): the serve
# script drives `podman run` DIRECTLY (the image entrypoint execs
# `vllm serve`), with every engine flag qualified by boot probe and carried
# in the repo env file. The seam pins what the flags alone do not say: the
# KV qualification law (the night ladder: 262144/245760 OOM at graph
# capture; 241664 boots at 732,359 tokens / 3.03x, util 0.98;
# the bf16-KV trade (double the attention-KV bytes/token, ~14% decode cost,
# clean cache + 262k windows), the automatic-offload law (the fork plans
# the tiered-expert offload itself; no flag exists to set), the self-healing
# law (the run returns before the engine is up, so the serve script must
# wait on the container for Restart=on-failure to mean anything), the
# memlock law that makes the pinned host rows legal, the deployer's
# image/payload gates with the false-green MainPID check, and the measured
# laws: expert prefetch ABSENT (36% precision), NO speculative decode (the
# no-spec family measured fastest once the prefetch tax was removed; MTP
# re-measures pending), gather geometry 32x64 PRESENT (+18.7% decode),
# MNBT 1024 (Frank's lock), and the client contract (reasoning parser qwen3,
# tool parser qwen3_xml, preserve_thinking on).
load helpers
@@ -43,7 +42,22 @@ DOWNLOAD="$REPO_ROOT/scripts/download-frank-primary.sh"
# dank session's own hard limit is 8 MiB and cannot be raised without
# restarting user@1000.service).
grep -q '^WantedBy=multi-user.target$' "$UNIT"
grep -q '^Restart=on-failure$' "$UNIT"
# Restart=always, not on-failure: a runtime worker OOM makes vLLM's API
# server exit CLEAN, so ExecStart returns 0 and on-failure never fires
# (measured 2026-10-01 — the endpoint stayed down until a human noticed).
grep -q '^Restart=always$' "$UNIT"
! grep -q '^Restart=on-failure$' "$UNIT"
# Exiting the engine takes as long as vLLM's drain: ExecStop runs
# `podman stop -t 120`, so the stop timeout MUST exceed 120 s or systemd
# kills the stop and records 'Failed with result timeout' (measured
# 2026-10-01). Guard the relationship, not just the literal.
stop_t=$(awk -F= '/^TimeoutStopSec=/{print $2}' "$UNIT")
[ -n "$stop_t" ] && [ "$stop_t" -gt 120 ]
grep -q '^ExecStop=.*podman stop -t 120' "$UNIT"
# StartLimitIntervalSec belongs to [Unit]; a copy in [Service] is an
# 'Unknown key' warning systemd logs on every load.
[ "$(grep -c '^StartLimitIntervalSec=' "$UNIT")" = "1" ]
awk '/^\[Service\]/{in_svc=1} /^StartLimitIntervalSec=/{if(in_svc) exit 1}' "$UNIT"
grep -q '^RestartSec=' "$UNIT"
grep -q '^User=dank$' "$UNIT"
grep -q '^LimitMEMLOCK=infinity$' "$UNIT"
@@ -76,19 +90,34 @@ DOWNLOAD="$REPO_ROOT/scripts/download-frank-primary.sh"
}
@test "the qualified engine shape is in the env file" {
# 2026-09-29 boot probe: 200,000 x 3 seqs at fp8 KV, util 0.98, KV_BYTES
# 7.2 GiB PER RANK boots at "GPU KV cache size: 729,545 tokens" and
# reports max concurrency 3.65x for 200,000-token requests. KV_BYTES is
# PER RANK — sizing it to the global requirement OOMs the worker
# (measured twice: 16 GiB and 9 GiB both die with ~7.5 GiB free). So 4
# full-length 200k contexts do NOT fit: four clients share the ~730k
# token pool and each runs below 200k when all are deep.
grep -q '^FRANK_PRIMARY_MAXLEN=200000$' "$ENV_FILE"
# 2026-10-01 night ladder (Frank's method), then a runtime-survivability
# correction. SEQS=3 bf16 topped out at 241664 (KV 732,359 / 3.03x);
# SEQS=6 fp8 does NOT fit (6 x 241664 asked 10.70 GiB against 9.18 GiB
# free); SEQS=5 fp8 x 262144 BOOTED (KV 1,350,182 / 5.15x) but left ~0
# bytes free at runtime and a real client request (995-token prompt with
# max_tokens=261149) killed the worker with `Tried to allocate 50.00 MiB
# ... 0 bytes free`. FOUR slots at the full native 262144 window is the
# deployed shape: ~1.93 GiB more headroom per rank for
# activations/graphs. UTIL stays 0.98 (lowering it shrinks the engine's
# own budget instead of buying slack).
# FINAL (2026-10-01, Frank): TWO full-size windows with BF16 KV plus
# --expert-precise-memory. bf16 costs 13,839 B/token (measured), so
# 2 x 262144 = 524,288 tokens needs 7.256e9 B; pinned at 7.3e9 (~527.5k
# tokens, 3,206 margin). The precise flag drops the plan's overhead
# 7.60 -> 5.25 GiB, moving the arena from 6,248 to ~7,278 slots.
grep -q '^FRANK_PRIMARY_MAXLEN=262144$' "$ENV_FILE"
grep -q '^FRANK_PRIMARY_SEQS=3$' "$ENV_FILE"
grep -q '^FRANK_PRIMARY_UTIL=0.98$' "$ENV_FILE"
grep -q '^FRANK_PRIMARY_KV_BYTES=7730934784$' "$ENV_FILE"
grep -q '^FRANK_PRIMARY_KV_BYTES=6100000000$' "$ENV_FILE"
grep -q '^FRANK_PRIMARY_MNBT=2048$' "$ENV_FILE"
grep -q '^FRANK_PRIMARY_KV_DTYPE=fp8$' "$ENV_FILE"
grep -q '^FRANK_PRIMARY_SPEC=4$' "$ENV_FILE"
# --expert-precise-memory is NOT set: with bf16 2 x 262144 it put the boot
# 0.13 GiB from the 31.86 GiB ceiling (arena 16.65 device-resident) and
# crash-looped at graph capture. The serve script keeps the opt-in flag.
! grep -q '^FRANK_PRIMARY_PRECISE_MEMORY=' "$ENV_FILE"
grep -q '^FRANK_PRIMARY_GATHER_CHUNKS=32$' "$ENV_FILE"
grep -q '^FRANK_PRIMARY_GATHER_LANES=64$' "$ENV_FILE"
! grep -q '^FRANK_PRIMARY_SPEC=' "$ENV_FILE"
grep -q '^FRANK_PRIMARY_MODEL_SHARDS=131$' "$ENV_FILE"
}
@@ -97,20 +126,40 @@ DOWNLOAD="$REPO_ROOT/scripts/download-frank-primary.sh"
grep -q -- '--max-model-len "$FRANK_PRIMARY_MAXLEN"' "$SERVE"
grep -q -- '--kv-cache-memory-bytes "$FRANK_PRIMARY_KV_BYTES"' "$SERVE"
grep -q -- '--kv-cache-dtype "$FRANK_PRIMARY_KV_DTYPE"' "$SERVE"
grep -q -- '--speculative-config \"{\\\"method\\\":\\\"mtp\\\",\\\"num_speculative_tokens\\\":\$FRANK_PRIMARY_SPEC}\"' "$SERVE"
grep -q -- '--max-num-batched-tokens "$FRANK_PRIMARY_MNBT"' "$SERVE"
grep -q -- '-e R4D_LRU_GATHER_CHUNKS="$FRANK_PRIMARY_GATHER_CHUNKS"' "$SERVE"
grep -q -- '-e R4D_LRU_GATHER_LANES="$FRANK_PRIMARY_GATHER_LANES"' "$SERVE"
! grep -q -- '--speculative-config' "$SERVE"
grep -q -- '--tensor-parallel-size 2' "$SERVE"
grep -q -- '--enable-prefix-caching' "$SERVE"
grep -q -- '--trust-remote-code' "$SERVE"
# DCP is opt-in: the flag is passed only when FRANK_PRIMARY_DCP is set
# (DCP reuses the TP ranks when PCP is off, so TP=2 + DCP=2 fits two GPUs).
grep -q -- '--decode-context-parallel-size "$FRANK_PRIMARY_DCP"' "$SERVE"
! grep -q '^FRANK_PRIMARY_DCP=' "$ENV_FILE"
# --expert-precise-memory selects the fitted overhead (5.25 GiB) over the
# default (7.60 GiB = fitted + compile/graph-capture headroom), which only
# moves the plan's `room` term and therefore the expert arena: ~1,025
# more slots at 2.344 MiB each.
grep -q -- '${FRANK_PRIMARY_PRECISE_MEMORY:+--expert-precise-memory}' "$SERVE"
}
@test "the endpoint serves NO tool dialect — tool agents route elsewhere" {
# The 2339fae trio does NOT wire --enable-auto-tool-choice /
# --tool-call-parser (the GLM era added glm47 dialect flags; the rollback
# dropped them). tool_choice "auto" gets a 400 here — tool-using agents
# must route at frank-small or frank-large until a parser is qualified
# for this arm (a behavior change beyond the rollback, not a silent fix).
! grep -q -- '--enable-auto-tool-choice' "$SERVE"
! grep -q -- '--tool-call-parser' "$SERVE"
@test "tools and reasoning are wired — the client contract is served" {
# 2026-10-01: the rollback-era trio served NO tool dialect and left
# thinking inline in `content` with a dangling `</think>` and a null
# `reasoning` field (measured: content 'We need answer...Brief.\n</think>
# \n\n391') — the malformed thinking block clients choke on. The working
# values are the ones ecaad36 shipped for this model and this fork's
# registries confirm: reasoning parser `qwen3`, tool parser `qwen3_xml`.
# preserve_thinking keeps prior thinking blocks across turns.
grep -q '^FRANK_PRIMARY_REASONING_PARSER=qwen3$' "$ENV_FILE"
grep -q '^FRANK_PRIMARY_TOOL_PARSER=qwen3_xml$' "$ENV_FILE"
grep -q -- '--reasoning-parser "$FRANK_PRIMARY_REASONING_PARSER"' "$SERVE"
grep -q -- '--enable-auto-tool-choice' "$SERVE"
grep -q -- '--tool-call-parser "$FRANK_PRIMARY_TOOL_PARSER"' "$SERVE"
grep -q -- '--default-chat-template-kwargs "$FRANK_PRIMARY_CHAT_TEMPLATE_KWARGS"' "$SERVE"
grep -q 'preserve_thinking' "$ENV_FILE"
grep -q 'enable_thinking' "$ENV_FILE"
}
@test "expert offload is AUTOMATIC — the payload cannot fit VRAM and no flag sets it" {
@@ -125,28 +174,50 @@ DOWNLOAD="$REPO_ROOT/scripts/download-frank-primary.sh"
grep -q -- '--ipc=host --ulimit memlock=-1:-1' "$SERVE"
}
@test "MTP4 spec decode is PRESENT BY MEASUREMENT" {
# 2026-09-29 campaign at prefetch OFF: MTP4 measures 40.57/37.44/37.57
# tok/s (166/1087/4064 prompt tokens) at 54% acceptance vs the no-spec
# baseline 12.11 tok/s (dead flat, expert-gather bound) — a measured
# 3.1-3.4x win. MTP3 measured 24.4 (still 2x baseline), MTP6 collapses
# (17.4% acceptance). The earlier "MTP buys zero decode" reading carried
# the prefetch tax and is retired with it. ngram-mod never booted on this
# model (fork bug: PLE inputs prepared only on the MTP path).
grep -q '^FRANK_PRIMARY_SPEC=4$' "$ENV_FILE"
grep -q -- '--speculative-config' "$SERVE"
@test "speculative decode is ABSENT BY MEASUREMENT" {
# The 2026-10-01 overnight redo (prefetch OFF) re-measured the whole
# spec family against no-spec at matched geometry: no-spec measured
# 41.46/41.29/41.47 tok/s while the spec-era incumbent's 37-40 carried
# the prefetch tax, and MTP's 2.6 GiB/rank drafter reservation halves
# the pool (729,545 vs 975,342 tokens). The MTP3/4/6 untaxed re-measures
# never completed; until one shows a real win, no spec is the incumbent.
! grep -q '^FRANK_PRIMARY_SPEC=' "$ENV_FILE"
! grep -q -- '--speculative-config' "$SERVE"
}
@test "fp8 KV is PRESENT — q8/q8 qualified on this arm" {
# --kv-cache-dtype fp8 is e4m3 for BOTH K and V (the stock flag quantizes
# them together; a V-only quant needs a fork patch). The GLM-era MLA
# concern (sparse-triton MLA decode path refusing fp8 KV) does not apply
# to this arm: qwen's attention path accepted the dtype and a completion
# probe qualified it 2026-09-29.
@test "KV dtype is bf16 (auto) — exactness, paid for in pool bytes" {
# --kv-cache-dtype auto = bf16 (unquantized). Frank's call 2026-10-01.
# bf16 costs 13,839 B/token against fp8's 7,701 — decomposed as 12,276
# attention + 1,563 mamba/side (dtype-independent) versus fp8's 6,138 +
# 1,563. That halves the pool capacity per byte, which is why the contract
# is two full-size windows instead of three; in exchange the KV is exact
# (no quantization error) and measured +4% decode at shallow depth, where
# fp8's dequant cost dominates over the extra bytes read.
grep -q '^FRANK_PRIMARY_KV_DTYPE=fp8$' "$ENV_FILE"
grep -q -- '--kv-cache-dtype "$FRANK_PRIMARY_KV_DTYPE"' "$SERVE"
}
@test "gather geometry 32x64 is PRESENT BY MEASUREMENT" {
# R4D_LRU_GATHER_CHUNKS=32 / R4D_LRU_GATHER_LANES=64: the overnight
# sweep's biggest lever, +18.7% decode vs default geometry, and the win
# GROWS with depth (39.5@166 -> 54.1@1087 -> 49.3@4064 in the fp8 era).
# g64x128 is past the peak; g8x16 mild. They are container ENV (the
# fork's knobs), not engine flags — passed through with -e.
grep -q '^FRANK_PRIMARY_GATHER_CHUNKS=32$' "$ENV_FILE"
grep -q '^FRANK_PRIMARY_GATHER_LANES=64$' "$ENV_FILE"
grep -q -- '-e R4D_LRU_GATHER_CHUNKS="$FRANK_PRIMARY_GATHER_CHUNKS"' "$SERVE"
}
@test "MNBT is at Frank's 2048 with the arena intact" {
# MNBT 512 doubles TTFT at 4064 ctx (2.46 s vs 1.36 s); 1024-4096 are
# interchangeable on decode AND identical on arena (the sweep measured
# 6,499 slots at every rung <=4096); 12288 costs 2.5% plus arena.
# 2048 is Frank's setting as of 2026-10-01 — it keeps the workspace floor
# so the expert arena stays max.
grep -q '^FRANK_PRIMARY_MNBT=2048$' "$ENV_FILE"
grep -q -- '--max-num-batched-tokens "$FRANK_PRIMARY_MNBT"' "$SERVE"
}
@test "expert prefetch is absent BY LAW, not by omission" {
# Telemetry (2026-09-29): the prefetcher served 13,369 of 36,720
# prefetched slabs (36% precision) — roughly half the gather traffic was
+74 -61
View File
@@ -1,25 +1,30 @@
#!/usr/bin/env bats
# Seam: the frank-small mainline-llama.cpp root unit on dankclaw.
# frank-small is the RTX 3090 endpoint created on 2026-09-16, when frank-large
# went back to the halogen engine on the iGPU. This seam pins what the flags
# alone do not say: boot persistence for a NATIVE runtime (no generated quadlet
# is involved), the repo-relative paths the unit executes, the separate client
# port, the MTP contract (the head is a separate sidecar file loaded as the
# draft model, chained behind ngram-mod), the vision handoff from frank-large,
# and the KV budget: q8_0 quantized KV whose context --fit sizes to the card.
# Seam: the frank-small SGLang root unit on dankclaw.
# frank-small is the RTX 3090 endpoint; since 2026-10-01 it serves
# letechlead/MiMo-V2.6-Distill-Qwen-9B-INT8-W8A16-AutoRound (qwen3_5 hybrid,
# INT8 W8A16 AutoRound, in-checkpoint vision) via SGLang in a
# python3.12 venv. This seam pins what the flags alone do not say: boot
# persistence for a NATIVE runtime (no generated quadlet is involved), the
# repo-relative paths the unit executes, the separate client port, the
# no-spec-decode gate (the checkpoint ships NO mtp.* tensors, so a NEXTN
# draft would be an uninitialised ghost model), the 8-shard payload gate,
# and the KV budget: fp8 KV at 0.98 utilization whose 4-slot grid must fit
# the card's 24 GiB.
load helpers
UNIT="$REPO_ROOT/scripts/frank-small.service"
SERVE="$REPO_ROOT/scripts/serve-frank-small.sh"
ENV_FILE="$REPO_ROOT/scripts/frank-small.env"
DOWNLOAD="$REPO_ROOT/scripts/download-frank-small.sh"
REMOTE_DEPLOY="$REPO_ROOT/scripts/deploy-remote.sh"
ENV_LARGE="$REPO_ROOT/scripts/frank-large.env"
@test "frank-small unit, serve script and env exist in scripts/" {
@test "frank-small unit, serve script, env and download script exist in scripts/" {
[ -f "$UNIT" ]
[ -f "$SERVE" ]
[ -f "$ENV_FILE" ]
[ -f "$DOWNLOAD" ]
}
@test "frank-small is boot-persistent, self-healing and unprivileged" {
@@ -35,64 +40,67 @@ ENV_LARGE="$REPO_ROOT/scripts/frank-large.env"
grep -q 'FRANK_SMALL_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-small.env' "$UNIT"
}
@test "frank-small offloads every layer to the 3090 with flash attention" {
grep -q 'llama.cpp-mainline/build-cuda/bin/llama-server' "$ENV_FILE"
grep -q '^NGL=999$' "$ENV_FILE"
grep -q -- '--gpu-layers "$NGL"' "$SERVE"
grep -q '^FLASH_ATTN=on$' "$ENV_FILE"
grep -q -- '--flash-attn "$FLASH_ATTN"' "$SERVE"
# Prometheus scrapes this endpoint; without --metrics there is no /metrics.
grep -q -- '--metrics' "$SERVE"
@test "frank-small serves the MiMo-V2.6 checkpoint from the self-contained SGLang venv" {
grep -q '^SGLANG_BIN=/home/dank/GitPackages/sglang-cu128/bin/sglang$' "$ENV_FILE"
grep -q '^MODEL_DIR=/home/dank/models/MiMo-V2.6-Distill-Qwen-9B-INT8-W8A16-AutoRound$' "$ENV_FILE"
grep -q -- '--model-path "$MODEL_DIR"' "$SERVE"
# The AutoRound checkpoint declares its quant method; SGLang must load it
# as auto-round, not re-quantize online.
grep -q '^QUANTIZATION=auto-round$' "$ENV_FILE"
grep -q -- '--quantization "$QUANTIZATION"' "$SERVE"
}
@test "frank-small caps its CPU RAM cache below the build default" {
# Without the flag the 8192 MiB default returns and the env cap is a
# silent no-op; this memory-tight host needs the cap to hold.
grep -q -- '--cache-ram "$CACHE_RAM"' "$SERVE"
}
@test "frank-small drafts with the MTP sidecar chained behind ngram-mod" {
grep -q '^SPEC_TYPE=draft-mtp,ngram-mod$' "$ENV_FILE"
grep -q -- '--spec-type "$SPEC_TYPE"' "$SERVE"
# The Gemma4 MTP head is a separate assistant file (gemma4-assistant, 4
# nextn layers); it loads as --model-draft and shares the target's last
# layers' KV. ngram-mod is draftless, so the chain is legal.
grep -q '^DRAFT_FILE=mtp-gemma-4-12B-it\.gguf$' "$ENV_FILE"
grep -q -- '--model-draft "$MODEL_DIR/$DRAFT_FILE"' "$SERVE"
@test "frank-small runs WITHOUT speculative decoding (no MTP weights shipped)" {
# The config declares mtp_num_hidden_layers=1 but the safetensors index
# carries zero mtp.* tensors (base and INT8 conversion alike, verified
# 2026-10-01). SGLang would draft with an uninitialised 4.24 GiB model
# at 0% acceptance; the serve script must not pass any speculative flag.
! grep -q -- '--speculative-' "$SERVE"
! grep -q '^SPEC_' "$ENV_FILE"
}
@test "frank-small carries the fleet's image path, and only it" {
grep -q '^MMPROJ_PATH=.*mmproj-Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced-BF16\.gguf$' "$ENV_FILE"
grep -q -- '--mmproj "$MMPROJ_PATH"' "$SERVE"
# The vision tower is baked into the safetensors (qwen3_5_vision): no
# separate projector file, and the serve script must not look for one.
! grep -q '^MMPROJ_PATH=' "$ENV_FILE"
! grep -q -- '--mmproj' "$SERVE"
! grep -q '^ENABLE_VISION=1$' "$ENV_LARGE"
}
@test "frank-small's slot grid is full-window and fits the 24 GiB card" {
local parallel cache_k cache_v ctx fixed per_slot
parallel="$(sed -nE 's/^PARALLEL=([0-9]+)$/\1/p' "$ENV_FILE")"
cache_k="$(sed -nE 's/^CACHE_TYPE_K=(.+)$/\1/p' "$ENV_FILE")"
cache_v="$(sed -nE 's/^CACHE_TYPE_V=(.+)$/\1/p' "$ENV_FILE")"
ctx="$(sed -nE 's/^CTX_SIZE=([0-9]+)$/\1/p' "$ENV_FILE")"
[ -n "$parallel" ] && [ -n "$cache_k" ] && [ -n "$cache_v" ] && [ -n "$ctx" ]
# Every slot must be the model's FULL trained window (262144), not a
# divided one -- CTX_SIZE is the total pool and --parallel divides it.
[ $((ctx / parallel)) -eq 262144 ]
[ $((ctx % parallel)) -eq 0 ]
[ "$cache_k" = "q8_0" ] && [ "$cache_v" = "q8_0" ]
# Fit budget from the measured boot arithmetic on the 3090 (24576
# MiB): one full-context slot idles at 11,996 MiB, four at 22,346,
# so each slot costs (22346-11996)/3 = 3450 MiB and the fixed part
# (weights, projector, sidecar draft, compute buffers, CUDA context)
# is 11996-3450 = 8546 MiB. If the config asks for more slots than
# the card holds, this inequality fails before deploy instead of the
# KV allocation failing at boot.
fixed=8546
per_slot=3450
[ $((fixed + parallel * per_slot)) -le 24576 ]
# Quantized KV on CUDA needs the GGML_CUDA_FA_ALL_QUANTS build option,
# without which prefill collapses about 12x (see the CUDA lesson in
# AGENTS.md). The build-cuda tree must carry it.
grep -q '^FLASH_ATTN=on$' "$ENV_FILE"
@test "frank-small's slot grid is fp8 KV and fits the measured card budget" {
local ctx running kv ssmdtype mambasize required
ctx="$(sed -nE 's/^CONTEXT_LENGTH=([0-9]+)$/\1/p' "$ENV_FILE")"
running="$(sed -nE 's/^MAX_RUNNING=([0-9]+)$/\1/p' "$ENV_FILE")"
kv="$(sed -nE 's/^KV_DTYPE=(.+)$/\1/p' "$ENV_FILE")"
ssmdtype="$(sed -nE 's/^MAMBA_SSM_DTYPE=(.+)$/\1/p' "$ENV_FILE")"
mambasize="$(sed -nE 's/^MAX_MAMBA_CACHE_SIZE=([0-9]+)$/\1/p' "$ENV_FILE")"
[ -n "$ctx" ] && [ -n "$running" ] && [ -n "$kv" ]
# fp8 KV is the only dtype whose 16 KiB/token makes four slots fit;
# 64 tokens per MiB of pool.
case "$kv" in fp8*) ;; *) return 1 ;; esac
# The DeltaNet ssm state pool is the hidden fit cost: the engine
# autofills mamba slots to spend a fixed ~5.1 GB budget, so dtype
# alone does not shrink it — the SLOT COUNT must be pinned (bf16,
# bounded). These two gates are what make the measured pool below
# exist; change either and re-measure the pool at boot.
[ "$ssmdtype" = "bfloat16" ]
[ -n "$mambasize" ] && [ "$mambasize" -ge "$running" ] && [ "$mambasize" -le 64 ]
grep -q -- '--mamba-ssm-dtype "$MAMBA_SSM_DTYPE"' "$SERVE"
grep -q -- '--max-mamba-cache-size "$MAX_MAMBA_CACHE_SIZE"' "$SERVE"
# The slot window is inside the model's native 262144 window.
[ "$ctx" -le 262144 ]
# The grid must equal the pinned pool. The engine's autofit picks a
# bigger pool (687,388 tokens) but leaves ~0.53 GB — Triton's
# deferred kernel loads take most of it and eager-prefill activations
# then OOM on the first long request. 606,208 (4 x 151,552) is the
# verified ceiling: 170k single request and 4 concurrent 54k requests
# run against it (2026-10-01). A weights or mamba-flag change moves
# this number; re-measure before trusting the grid.
pinned_pool=606208
required=$((running * ctx))
[ "$required" -le "$pinned_pool" ]
grep -q -- '--max-total-tokens "$MAX_TOTAL_TOKENS"' "$SERVE"
grep -q -- '--disable-prefill-cuda-graph' "$SERVE"
}
@test "frank-small runs on its own port beside frank-large's" {
@@ -106,16 +114,21 @@ ENV_LARGE="$REPO_ROOT/scripts/frank-large.env"
! grep -q '^PORT=7771$' "$ENV_LARGE"
}
@test "the deploy handler installs the root unit and refuses a missing model" {
@test "the deploy handler installs the root unit and refuses a missing payload" {
grep -q 'deploy_llm_small' "$REMOTE_DEPLOY"
grep -q 'relink_unit frank-small' "$REMOTE_DEPLOY"
grep -q 'systemctl enable frank-small.service' "$REMOTE_DEPLOY"
grep -q 'systemctl restart frank-small.service' "$REMOTE_DEPLOY"
grep -q 'Gemma4-12B-QAT' "$REMOTE_DEPLOY"
grep -q 'MiMo-V2.6-Distill-Qwen-9B-INT8-W8A16-AutoRound' "$REMOTE_DEPLOY"
grep -q 'refusing to start a unit that cannot load' "$REMOTE_DEPLOY"
grep -q '127.0.0.1:7771/health' "$REMOTE_DEPLOY"
}
@test "frank-small's serve script refuses to start on a half-finished download" {
# The payload is 8 safetensors shards; the serve script counts them and
# the download script pins each one's LFS sha256.
grep -q 'frank-small: missing' "$SERVE"
grep -q 'expected 8 safetensors shards' "$SERVE"
grep -q 'model-00001-of-00008.safetensors' "$DOWNLOAD"
grep -q 'model-00008-of-00008.safetensors' "$DOWNLOAD"
}