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Author SHA1 Message Date
Comrade Chief Designer 30904bac1b frank-primary: 2 x 200704 fp8, pool cut for the expert arena, MNBT 1024
The 2026-10-01 bf16 shape (2 x 262144, --expert-precise-memory)
crash-looped at graph capture — the arena is DEVICE-resident and that
shape had 0.13 GiB to spare. The plain bf16 2 x 262144 also did not stay
up: 0 bytes free at runtime, and a real client request (995-token prompt,
max_tokens=261149) killed the worker with .

The correction is a pool cut, not a downgrade. FP8 KV (7,701 B/token),
two 200704 windows (401,408 tokens -> 3.091e9 B floor, pinned 3.15e9),
MNBT 1024. The fork's expert planner sizes the arena AFTER the KV
override, so the ~2.95 GiB/rank reclaimed becomes arena: ~7,500 slots
vs 6,248. Two contexts at 200704 is a capacity contract, not a
throughput one (2-way concurrency summed BELOW parity at 4064 ctx), so
the slot buys the VRAM headroom long generations need.

Refs [[dankserver-qwen38-fp8-expert-offload-tuning]].

- scripts/frank-primary.env: MAXLEN 200704, SEQS 2, KV_BYTES 3.15e9,
  MNBT 1024, rewritten shape comment
- scripts/serve-frank-primary.sh: header comment updated
- tests/frank_primary_unit.bats: assertions updated, new seam pins the
  arena-floor pool law (the pool must move with a context change or the
  reduction buys nothing)
- docs + AGENTS.md: fleet topology and deployed shape corrected
2026-10-02 09:54:08 -07:00
Frank f8f845d86b autoresearch: harness setup
Benchmark entrypoint: bash autoresearch.sh
Goal: Make frank-primary faster: raise decode tok/s on the tcclaviger vLLM endpoint (dankserver :7770, Qwen3.8-Flash-Next-Uncensored-FP8, 2x R9700, automatic tiered-expert offload). Context size may be altered (MAXLEN/SEQS/KV_BYTES and friends); quantization may NOT be altered (the 131-shard FP8 payload and the digest-pinned image are frozen).
2026-10-02 07:50:50 -07:00
Frank 934285c2b2 docs(frank-small): record the 3 x 180,224 + vision shape and what it cost
Runbook, both indexes, AGENTS.md (topology row, endpoint section, three new
Key Lessons, one stale SGLang label in the bench list) and the bundle log now
describe the deployed shape: pool 540,672, 180,224 tokens per conversation,
f16 K + q8_0 V, mmproj vision, 21,684 used / 2,441 free of 24,576 MiB, 106.8
tok/s decode, 3,814 t/s prefill.

The claims that mattered:
- three contexts buy 180,224 tokens per conversation, not the native 262,144,
  and a longer prompt is a hard 400 - so models.yml contextWindow is 180224
  and frank-primary's 183,501-token compaction request no longer fits here
  (forward pointer added to the retired SGLang runbook, which asserted it)
- the vision tower bills ~1.4 GiB for a 918 MB file, established by subtracting
  two measured boots, not by a formula
- /v1/chat/completions ignores the legacy top-level 'images' field: the model
  invents a color; only the image_url content part reaches it
2026-10-02 03:46:50 -07:00
Frank 7fe881de01 frank-small: pool 540672 (3 x 180224) so the card keeps ~2.7 GiB free
Measured after the first 3-slot deploy: 3 x 196,608 booted (n_slots=3,
n_ctx_slot=196608, multimodal loaded) but used 22,972/24,576 MiB - 1,153 MiB
free, outside the 2-3 GiB band. The two measurements now recorded in
frank-small.env price the vision tower at ~1.4 GiB (non-KV 7,390 -> 8,859
MiB), so the pool drops 49,152 tokens (16,384/slot, 1,176 MiB) to land ~2.7
GiB free. The bats budget gate is recalibrated to the measured 9 GiB non-KV
cost, which now rejects the 3 x 196,608 shape instead of blessing it.
2026-10-02 03:17:35 -07:00
Frank a02850203d frank-small: three contexts, vision on, 2-3 GiB of the 3090 left free
CTX_SIZE 589824 / PARALLEL 3 -> three independent 196,608-token conversations
(a mamba hybrid cannot share one KV cache, so per-slot window = pool/slots;
3 x 262,144 would need 18.4 GiB of KV alone and busts the card).

Vision comes back via bartowski's mmproj-MiMo-V2.6-Distill-Qwen-9B-f16.gguf
(918,166,048 B, sha256 ff348f31..., fetched + verified by
scripts/download-frank-small.sh): the Q5_K_M GGUF ships no v.* tensors, so
--mmproj IS the image path. MMPROJ_FILE without a colon default so an explicit
empty value is a real text-only opt-out, and the deployer now gates on the
projector exactly as the serve script does.

Budget is measured, not guessed: the 2 x 262,144 shape used 20,190/24,576 MiB,
which prices non-KV cost at 7,390 MiB. Three slots + projector land near
22.5 GiB, i.e. ~2 GiB spare - the bottom of the requested band, to be
confirmed by measurement and laddered if it lands outside 2-3 GiB.
2026-10-02 03:08:00 -07:00
Frank 8f129180d8 docs+scripts: reconcile payload inventory after both swaps
Staged 59 GiB of retired LLM payloads on Dankclaw to
~dank/.AGENTTRASH/20261002-retired-llm-payloads/ (vLLM MiMo BF16, Qwen3.5-9B
MTP source, both DFlash dirs, Gemma4-12B-QAT, SGLang MiMo INT8) and corrected
every doc claim about what is on disk: gufo's rollback pair (Q4_K_XL weights +
the Q8_K_XL DFlash2 drafter) and frank-small's Q6_K stay in place, so the
rollback paths in the tags' env files still resolve. The vLLM-era frank-large
fetch trio moves to old/ with its runtime; runbook links updated.
2026-10-02 02:31:39 -07:00
Frank 72bd4c967e docs: record the 2026-10-02 swaps — frank-large on ROCmFPX, frank-small on Q5_K_M
frank-large: new runbook frank-large-rocmfpx-q8agent-mtp.md — the ftype-115
tensor-type lock-in that forced the fork, the pinned build (set_rows history),
the measured MTP A/B (17.0 vs 7.6 t/s decode, acceptance 0.462), the live
client contract (reasoning_content, effort fold, vision restored) and rollback.
frank-small: new runbook frank-small-llama-mimo-q5km.md; q6k marked retired
(rollback target). gufo runbook marked retired (rollback target). Both indexes,
the fleet topology table, the vision/models.yml notes, the benchmarking law and
three new Key Lessons updated.
2026-10-02 01:51:11 -07:00
Frank 125d04967f frank-large: ROCmFPX llama.cpp on the Q8_0_ROCMFPX_AGENT file, MTP drafting
The repo's highest-quality rung is ftype 115: 311 tensors of
GGML_TYPE_Q8_0_ROCMFPX, a type only the ROCmFPX fork reads, so the runtime
moves from gufo to scripts/build-rocmfpx.sh's pinned fork build (36e9acd) —
the first build on this host measured to load this file without the
2026-08-25 set_rows segfault. One session at the native 262,144 window, f16
KV (64 KiB/token, 16 GiB), the repo's Q4_0 MTP head drafting 4 tokens, plus
the bundled BF16 projector so the endpoint has vision again.

The serve script now honors caller environment overrides over the env file
(a plain source let the file win, which made single-run overrides no-ops) and
defaults apply only when a value is unset, so an explicit LLAMA_BIN='' is the
error it reads as.
2026-10-02 00:47:16 -07:00
Frank d82c5c03b7 frank-small: Q5_K_M GGUF on llama.cpp, two full native windows
One quant step down from Q6_K on the same CUDA build and the same shape:
2 x 262,144 with K f16 + V q8_0. The 0.86 GiB freed from the weights is
headroom, not a new window — the native 262,144 cap is already reached,
and f16 V would still cost 3.96 GiB more than the pool can carry.
2026-10-02 00:00:17 -07:00
Frank 4bb10cd20e fetch: kingjones Q8_0_ROCMFPX_AGENT payload, frank-small Q5_K_M GGUF
The SGLang INT8 fetch recipe moves to old/ with its route; scripts/
download-frank-small.sh now carries the GGUF quant the endpoint serves.
2026-10-01 23:50:52 -07:00
Frank a7c68db9d0 docs: record the frank-small llama.cpp Q6_K cutover and the frank-large gufo rollback 2026-10-01 23:50:52 -07:00
Frank 8551bb006b frank-large: roll back to gufo Qwen3.8-27B Q4_K_XL, one session x 262144 f16 KV
frank-small: llama.cpp CUDA (master, sm_86) on MiMo Q6_K GGUF, 2 x 262144,
asymmetric KV (f16 K + q8_0 V, flash-attn pinned for the V quant)
2026-10-01 22:40:59 -07:00
Frank e452a1afbf harness: tolerate missing container in ASI capture; llama cmdline fallback 2026-10-01 22:11:34 -07:00
Frank 01ba41cab4 harness: llama-server lifecycle in pre-clean and health guard 2026-10-01 21:58:51 -07:00
Frank cde91c1a00 llama.cpp runtime arm: serve-script runtime switch, harness containerless support, master build 2026-10-01 21:56:30 -07:00
Frank 6513672f31 SPEC= (no draft): decode +46%, prefill +52%, ttft -35% vs MTP-2 baseline. Spec decode is NET-NEGATIVE on this endpoint for real chat+reasoning traffic at both depths; the bench-window win did not transfer.
Result: {"status":"keep","decode_tokens_per_sec":9.01,"prefill_tokens_per_sec":21088.7,"ttft_ms":851.8}
2026-10-01 21:00:19 -07:00
Frank 5df6ef3166 autoresearch: harness setup
Benchmark entrypoint: bash autoresearch.sh
Goal: Maximize frank-large decode throughput on the Strix Halo iGPU (gfx1151) via quantization >=q6/fp6, engine flags, spec-decode shape, or runtime swap — context limits unchanged, KV stays bf16.
2026-10-01 20:41:51 -07:00
Frank 3c339eeba2 frank-large: record deployed boot facts (pool 819,332 tokens, 3.13x, 230 s)
Live battery green after deploy #3: alias, reasoning split into
`reasoning`, tool_calls, /metrics acceptance pos0 69% pos1 44% - the
cross-model MTP head performs as measured in the bench window.
2026-10-01 19:48:56 -07:00
Frank 780c307354 frank-large: hand vLLM the CONTAINER model path; link the new runbook
The first crash-looping boot (51 restarts): serve received the host path
/home/dank/models/... but the models tree is mounted at /models inside the
container, so transformers failed 'Repo id must be in the form
namespace/repo_name' before the engine even built. Same conversion the spec
draft already used. Pinned by bats. Root docs index links the new runbook
(seam required it) and the work log records the crash-loop plus the 52 G
payload reclaim.
2026-10-01 19:39:55 -07:00
Frank de383fe53e frank-large: deployer spec gate must accept the sharded MTP layout
The 2026-10-01 first deploy refused /home/dank/models/Qwen3.5-9B because
the handler checked for a single model.safetensors (the dflash layout);
the Qwen3.5-9B MTP head ships 4 shards behind model.safetensors.index.json.
Same dual-layout acceptance as the serve script, now mirrored and gated by
the seam. The gate fired before the stop, so the live gufo unit was never
touched (health 200 throughout).
2026-10-01 18:52:17 -07:00
Frank 1127a52078 docs: frank-large vLLM MiMo-BF16 runbook; retire the gufo runbook
New runbook carries the roof math, the measured three-arm spec table, the
greedy-text numerics trap, the reasoning-field contract change and the
rollback tag. LLM index and AGENTS.md fleet table, bench policy and runbook
index follow; the frank-small index entries catch up to the SGLang cutover
(entry was missed on 2026-10-01). Work log records the cutover.
2026-10-01 18:48:51 -07:00
Frank dab483c79f frank-large: cutover to vLLM TheRock gfx1151, MiMo-V2.6 BF16 + cross-model MTP
Engine: digest-pinned docker.io/kyuz0/vllm-therock-gfx1151 (vLLM 0.30,
TheRock ROCm 10, Triton GDN kernels); the serve script gates the image by
REPO DIGEST, the payload (config + index + exact shard count), the spec
draft (BOTH weight layouts: single model.safetensors for dflash, sharded
index for the Qwen3.5-9B MTP head), and whole /dev/dri, sweeps the bench
identity vllm-mimo, then exec podman wait so a container death trips
Restart=always. Shape: 4 x 262144 at util 0.45 (KV grows only on the 8
full-attention layers), MTP 2 draft tokens.

Measured 2026-10-01 window (frank-large stopped): base 13.1 t/s decode
(~94% of the LPDDR5x BF16 roof), DFlash-8 17.4, MTP-2 19.8 with 71%/44%
per-position acceptance - the cross-model head works because vLLM reads the
draft from a separate path while MiMo ships zero mtp.* tensors. Spec arms
do not preserve greedy bf16 text (batched-verify reduction order).

The seam was rewritten around the new laws (18 tests): unit self-healing,
digest gating, engine wiring, the measured spec table, the retired gufo
gates, the deployer MainPID check. frank_small port test follows the
PORT -> FRANK_LARGE_PUBLISH rename. Rollback: tag frank-large-gufo-q4kxl-20261001.
2026-10-01 18:48:32 -07:00
Frank b3313340fa frank-large: fetch scripts for MiMo BF16, Qwen3.5-9B MTP source, DFlash drafter
All three verify every file by byte count + Hub LFS sha256, use -f (a bare
curl -o reports success on a 403 error body), support --verify-only, and
never put a token on the command line. Payloads are on Dankclaw and verified
against these manifests.
2026-10-01 18:48:05 -07:00
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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@@ -12,8 +12,8 @@ merge absorbed the former `vllmScripts` repo, history preserved).
Calibre-Web, Jellyfin, Plex) plus the `frank-primary` LLM service.
- **Dankclaw** (192.168.0.143) — AI/search/dev/observability stack (SearXNG
via Gluetun, ComfyUI, OpenWebUI, Hermes, Gitea, Grafana, Prometheus, Loki,
Alloy, Pi-hole) plus TWO LLM services: `frank-large` (stock llama.cpp on
the gfx1151 iGPU) and `frank-small` (llama.cpp on the RTX 3090). Caddy on
Alloy, Pi-hole) plus TWO LLM services: `frank-large` (ROCmFPX llama.cpp
fork on the gfx1151 iGPU) and `frank-small` (llama.cpp CUDA on the RTX 3090). Caddy on
Dankclaw reverse-proxies both hosts.
- **FrankBook-Pro** (192.168.0.112) — macOS mini running the *arr stack
(Prowlarr, Sonarr, Radarr, Lidarr, Readarr, qBittorrent) as quadlets inside
@@ -24,9 +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, **fp8 KV** (`--kv-cache-dtype fp8`), **no speculative decode**, MNBT 1024, MoE gather 32×64, **2 seqs × 200704 ctx** at KV_BYTES 3,150,000,000/rank (fp8 measures 7,701 B/token), pool deliberately small so the expert arena keeps what it reclaims (~7,500 slots vs 6,248 at the 6.1e9 shape) — util 0.98, and the client contract wired: `--reasoning-parser …
| Dankclaw | `frank-large` | **ROCmFPX llama.cpp fork** (`kingjones30/ROCmFPX` @ `36e9acd`, gfx1151, built by `scripts/build-rocmfpx.sh`; bare `llama-server`, root systemd unit) | `kingjones777/Qwen3.8-27B-ROCmFP4-STRIX-MTP-GGUF` **`Qwen3.8-27B-Q8_0_ROCMFPX_AGENT.gguf`** (26.28 GiB, ftype 115 ≈ 8.39 bpw: 353 F32 + 187 Q8_0 + 311 `GGML_TYPE_Q8_0_ROCMFPX` tensors — only this fork can read them), **MTP spec decode from the repo's own `mtp-Qwen3.8-27B-Q4_0.gguf` (n-max 4, pinned to ROCm0)**, **1 session × 262,144 (native window)** with **f16 KV**, the bundled BF16 mmproj for vision, thinking on with the card's recipe (temp 1.0 / top_p 0.95 / top_k 20). Measured 2026-10-02: decode **17.0–17.1 t/s** with MTP vs **7.6 without (+123 %)**, draft acceptance 0.462, prefill 325–351 t/s, prompt-cache replay 0.5 s, boot→healthy 16 s, GTT 64.5 GiB. Cut over 2026-10-02 from gufo; rollback tag `frank-large-gufo-q4kxl-20261001` | 7770 |
| Dankclaw | `frank-small` | llama.cpp master, CUDA sm_86 build (root systemd unit, relinked) | bartowski/MiMo-V2.6-Distill-Qwen-9B-GGUF **Q5_K_M** (9B dense qwen3_5 hybrid, 6.4 GiB GGUF, no MTP weights so no spec decode) + the repo's f16 mmproj for **vision**, on the RTX 3090, **3 × 180,224** (pool 540,672 — NOT the native window; three contexts cost 81,920 tokens per conversation) with **asymmetric KV f16 K + q8_0 V** under flash attention, 21,684 used / **2,441 free** of 24,576 MiB, 106.8 tok/s decode, 3,814 t/s prefill. Resized twice 2026-10-02 (Q6_K → Q5_K_M → 3 slots + vision → this pool); rollback `models/MiMo-Q6K/` or `PARALLEL=2 CTX_SIZE=524288` | 7771 |
Retired endpoints (`frank-npu`, and every prior runtime) are in
the [runbook index](#runbook-index). The full swap history lives in
@@ -209,14 +209,14 @@ archive.
**STOP the production service BEFORE benchmarking** — these servers serve
real users, and a bench beside a live service starves the GPU and corrupts
results. Use the runtime's own harness: `llama-bench` for the llama.cpp
endpoints, `gufo bench` for frank-large. Rolling your own bench
endpoints; a live llama.cpp server also reports honest per-request numbers in the `/completion` `timings` object (prefill/decode rates, `draft_n`, `draft_n_accepted`), which is how frank-large and frank-small were measured. Rolling your own bench
requires asking first.
Scratch ports are not used on LLM hosts — a
test process cannot share the single GPU anyway; validate against the service
itself.
**`gufo bench` cannot rank speculative-decode settings, and will invert the
ranking.** Measured 2026-09-28 on frank-large at depth 32768: its corpus
(A gufo-era law; frank-large is ROCmFPX llama.cpp since 2026-10-02, but the rollback tag keeps it live.) **`gufo bench` cannot rank speculative-decode settings, and will invert the ranking.**
Measured 2026-09-28 on frank-large at depth 32768: its corpus
reports `acceptance=0.933 ± 0.000` with an **identical trace sha256** across
draft widths, i.e. the same highly-predictable text every run, and 93 % of
every proposal accepted. It reported 29–37 t/s decode where real traffic
@@ -241,7 +241,7 @@ one: `ip neigh show <ip>` from a peer — FAILED means off/NIC dead, while a
merely wedged kernel usually still answers ARP.
1. Stop and mask (self-healing would restart it):
- Dankclaw `frank-large` (root unit, gufo on the iGPU):
- Dankclaw `frank-large` (root unit, vLLM podman on the iGPU):
`sudo systemctl stop frank-large && sudo systemctl mask frank-large`
- Dankclaw `frank-small` (root unit, llama.cpp on the 3090):
`sudo systemctl stop frank-small && sudo systemctl mask frank-small`
@@ -277,151 +277,147 @@ 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
(`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.
of 2026-10-02 **all three endpoints accept images** (`input: [text, image]`):
`frank-large` through the BF16 mmproj that ships inside its GGUF payload,
`frank-primary` through a BF16 mmproj loaded explicitly (this build never
autoloads projectors), and `frank-small` through
`mmproj-MiMo-V2.6-Distill-Qwen-9B-f16.gguf` passed as `--mmproj` — the Q5_K_M
GGUF itself carries no vision tensors. `frank-small`'s `contextWindow` is
**180224**, the per-slot window, not the model's native 262144: the harness
must compact before llama.cpp answers a longer prompt with a 400. Note also
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)
### frank-large — ROCmFPX llama.cpp, Qwen3.8-27B Q8_0_ROCMFPX_AGENT + MTP (Dankclaw, ACTIVE)
**gufo** (`gufo-org/gufo`) v0.1.1 — "the Strix Halo inference engine", a
vertical engine built for exactly this hardware (Ryzen AI MAX+ 395 /
Radeon 8060S, `gfx1151`) — as a **root systemd unit**
(`scripts/frank-large.service`, `User=dank`), serving
`ajgazin/Swift-1.5-Qwen3.8-27B-Uncensored-Dynamic-MTP-GGUF`'s `UD-Q8_K_XL`
(27B dense, 29.3 GiB, sha256-verified; **abliterated/uncensored**, and under
the *non-OSI* SWIFT OPEN LICENSE 1.0) on port 7770 from the gfx1151 iGPU.
One session, full 262,144 ctx (the model's native window, `SESSIONS=1`),
DFlash2 spec decode (the z-lab `Qwen3.8-27B-DFlash2-Q4_K_M` drafter, gufo's
**adaptive** block policy, `--draft-tokens 7`), greedy sampling, reasoning
extracted to `reasoning_content`, and **no vision projector**.
The **kingjones30/ROCmFPX llama.cpp fork** at commit
`36e9acd40e10a87cd3c3ef8ec734668757dc8520`, built for gfx1151 by
`scripts/build-rocmfpx.sh` into `/home/dank/GitPackages/kingjones-ROCmFPX/build`,
as a **root systemd unit** (`scripts/frank-large.service`, `User=dank`,
`Restart=always`) running a bare `llama-server` (no container) on port 7770
from the Strix Halo iGPU. Boot to healthy: **16 s**.
**Two swaps landed on 2026-09-28**, both same day: the engine (from the
unsloth llama.cpp b11030 prebuilt, which had replaced Kairic Edge ROCmFPX)
and then the payload (from `unsloth/Qwen3.8-27B-GGUF:UD-Q8_K_XL`, still on
disk and the payload-only rollback). The two targets 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 at `blk.64` — verified by parsing and diffing both GGUF headers before
either was loaded. **The DFlash2 drafter did not move**, so it has its own
`DRAFTER_DIR` and the deployer's stray-run sweep keys on the drafter's
filename, not the target's.
**The runtime is not interchangeable — it is chosen by the FILE.**
`kingjones777/Qwen3.8-27B-ROCmFP4-STRIX-MTP-GGUF`'s best rung,
`Qwen3.8-27B-Q8_0_ROCMFPX_AGENT.gguf` (28,214,425,952 B, sha256 `f3ef2bda…`,
ftype 115 ≈ 8.39 bpw), stores **311 tensors of type 103,
`GGML_TYPE_Q8_0_ROCMFPX`** — a quantization that exists in no other loader:
stock llama.cpp and gufo both refuse it at load (`unknown tensor type`). The
file is 353 F32 + 187 plain-Q8_0 + 311 ROCmFPX; the AGENT routing variant
keeps the output-head tensors at plain Q8_0 (187 vs 2 in the non-AGENT file),
which is why the card reports MTP acceptance 0.953 vs 0.911 — highest quality
AND the better drafter base. Vision comes from the bundled
`mmproj-Qwen3.8-27B-BF16.gguf` (931,145,888 B).
**The runtime is built from source on the host** —
`/home/dank/GitPackages/gufo-v0.1.1/`, reproducible with
`scripts/build-gufo.sh` (`--verify` re-checks an installed tree). gufo ships
no prebuilt Linux binaries and the v0.1.0/v0.1.1 release assets are empty.
Unlike the retired llama.cpp prebuilt, which bundled its own ROCm, **gufo
links the host ROCm 7.2.4 through its RPATH**, so the HIP dev packages must
stay installed. Two host workarounds the build script encodes:
**The pin is load-bearing.** The 2026-08-25 ROCmFPX builds segfaulted in
`ggml_compute_forward_set_rows` on exactly this file; `build-rocmfpx.sh`
checks the commit out by SHA, so a fork-side force-push cannot silently
re-break the endpoint.
- **Ubuntu's `librocwmma-dev` must be absent.** It installs a truncated
rocWMMA header set into `/usr/include` that shadows AMD's complete one
and breaks the build with `'internal/accessors.hpp' file not found`. A
`-I` cannot fix it — in HIP mode the host pass searches the system
directories first. The package has no reverse dependencies.
- **`--gcc-install-dir` must name GCC 15.** Ubuntu 26.04 ships
`/usr/include/c++/16`, which the ROCm clang prefers; its `<atomic_wait.h>`
needs a `std::__detail::__notify_impl` symbol version the installed
`libstdc++.so.6` (GLIBCXX_3.4.35) does not export, and the link fails.
**Spec decode is the performance feature, and it is measured.** The draft is
the repo's own `mtp-Qwen3.8-27B-Q4_0.gguf` (1,680,271,648 B, sha256 `051a1764…`,
`nextn_predict_layers = 1`), pinned to the same card:
`--spec-type draft-mtp --spec-draft-n-max 4 --spec-draft-n-min 0
--spec-draft-p-min 0.0 --spec-draft-device ROCm0 --spec-draft-ngl 99`.
Measured 2026-10-02 in one session, temp 0, 2,202-token prompt / 512 tokens,
`cache_prompt: false`, production service stopped for each arm:
**MTP on 17.00–17.14 t/s decode** (draft acceptance 0.462, mean acceptance
length ≈ 1.86) against **7.60–7.66 t/s with the draft removed — +123 %**;
prefill pays 8–15 % (381 → 325–351 t/s). Acceptance is far from the card's
0.95 (that number is the card's own text at a shallow prompt); the gain is
real and n-max 4 is where it was measured, never swept. This replaces the
gufo Q4_K_XL arm at ~15 t/s, so the endpoint got higher quality AND more
speed at once.
`gufo diagnose` is the preflight and must report `[PASS]` with `gfx1151`.
It also self-caps compute queues (`GPU_MAX_HW_QUEUES`, 2 resident for
`serve llm`) after reading `/sys/class/kfd/kfd/proc/*/queues/*/type`, which
matters because ComfyUI holds queues on the same device; four HIP processes
is the device ceiling.
**Shape and budget:** ONE session at the native 262,144 window, unquantized
f16 KV (~64 KiB/token → ~16 GiB, affordable inside the iGPU's ~114 GiB GTT
aperture), `--fit off --flash-attn on --direct-io --ctx-checkpoints 16
--cache-ram 8192 --cache-idle-slots`. Measured GTT 64.5 GiB with model +
draft + projector resident. Prompt cache verified: a repeat pass over the
same 6k prompt replays in 0.5 s.
**The client contract changed, and the chat template is the sharp edge.**
**gufo has no Jinja engine at all** — `src/models/qwen/chat_template.cpp` is
587 lines of hand-written C++ that appends strings, with no
`--chat-template-file`, no env override, and no template body to point at.
`scripts/qwen-sharp-v22.4.0.jinja` therefore **cannot** be supplied to
frank-large: that is a port, not a config line. Given the choice on
2026-09-28 the decision was to ship on gufo's stock renderer and accept the
loss — the `terse` system-prompt injection, the in-band `<|think_*|>`
control, the `json|xml` `tool_call_format` switch, the tool-argument
truncation and `add_vision_id` prefixes are all gone. gufo's own renderer
does keep the effort instruction strings and `preserve_thinking`, which are
what the harness depends on. **This is the thing to watch**: the endpoint
now runs an *abliterated* model without the prompt that tells it to stop
waffling. The cheap fix, if verbosity shows up, is to send the `terse` text
as an ordinary system message from `models.yml` — not a template change.
`reasoning_effort` accepts the full OpenAI set (all six levels verified
200), so `models.yml`'s `reasoningEffortMap` fold is no longer *required* —
it is kept deliberately, so that removing it does not silently move every
`high` role from `xhigh` to `high` effort inside a swap. And there is no
KV-quantization or prompt-cache-RAM flag; prompt reuse is on by default and
`--cache-disk` is opt-in and off.
**Client contract (llama.cpp, live-verified 2026-10-02):** `--jinja` is on
(without it `chat_template_kwargs` are silently ignored), tools are native
(`get_weather` → `{"city":"Seattle"}`), thinking lands in
**`reasoning_content`**, `reasoning_effort` accepts ONLY
`xhigh|medium|low` (anything else is HTTP 500 — `models.yml` folds `high` and
`max` to `xhigh`), and thinking is enabled server-side with the card's
recipe (temp 1.0 / top_p 0.95 / top_k 20 / min_p 0) plus
`--reasoning-format deepseek --reasoning-budget -1`. Two traps: a request
whose whole budget is consumed by reasoning returns `content: null` (bench
clients must fall back to `reasoning_content` or they crash *after*
measuring), and the fork logs
`MTP boundary missing for seq_id=… ; resyncing` under concurrent draft
resets — self-recovering, not a fault.
**Read the perf trade before assuming a win.** gufo's own Q8_K_XL tables
(vs llama.cpp b11069, DFlash2) show prefill +37 % to +80 %, cold load 4.5×
faster, decode +7 % at zero depth and +40 % at 4 users — but **−14 % at
65,536 tokens of depth and −24 % at 131,072**. On the 8-bit target the
crossover is ~32k of cached context, and frank-large runs one 262,144-token
conversation, so long agent sessions sit on the losing side of that line.
The Q4_K_XL target shows no such regression; revisiting the quantization is
a separate decision from the runtime. Peak memory is 50.58 GiB at the full
262,144 context against the iGPU's 114 GiB GTT aperture.
Fetch: `scripts/download-frank-large-kingjones.sh` (`-f` + byte count + LFS
sha256 verified, `--verify-only`, no token on the command line).
The serve script (`scripts/serve-frank-large.sh`) validates runtime → target
GGUF → drafter and exits with a pointer message if any is missing, then
`exec`s `gufo serve --host 0.0.0.0 --port 7770 --sessions 1 llm --model
…--served-model-name frank-large --context 262144 --speculative dflash2 …`.
The deployer's `deploy_llm_large` gates on the **runtime binary** as well
as both payload paths, and returns before it stops anything.
Fetch: `scripts/download-frank-large-swift.sh` (the target; per-file byte
count + sha256 against the Hub LFS oid, no auth header — the repo is public
and a token on the curl command line is world-readable) and
`scripts/download-frank-large.sh` (the DFlash2 drafter, which did not move).
Both take `--verify-only`.
Runbook: `serverAppConfigs-docs/LLM/frank-large-gufo-qwen38-27b.md`.
Rollback, two ways: **payload only** — re-fetch with
`scripts/download-frank-large.sh` and repoint `MODEL_FILE` at
`/home/dank/models/Qwen3.8-27B-UD-Q8_K_XL/Qwen3.8-27B-UD-Q8_K_XL.gguf`; that
29.3 GiB target was **reclaimed on 2026-09-28** (staged to
`~/.AGENTTRASH/20260928-retired-models/`, restorable from there), so it is
no longer a one-minute flip. **Engine** —
[[frank-large-unsloth-qwen38-27b-q8xl]], the b11030 prebuilt at
`/home/dank/GitPackages/unsloth-llama-b11030/`; the only way to get
Qwen-Sharp back. The DFlash2 drafter was never reclaimed and still lives in
`Qwen3.8-27B-UD-Q8_K_XL/`.
Runbook: `serverAppConfigs-docs/LLM/frank-large-rocmfpx-q8agent-mtp.md`.
Rollback: git tag **`frank-large-gufo-q4kxl-20261001`** — gufo v0.1.1
(`scripts/build-gufo.sh` stays on disk for it), the Q4_K_XL Qwen3.8-27B
payload and the DFlash2 drafter all remain on the host; restore the tag's
unit/env/serve trio and redeploy.
### frank-small — llama.cpp 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.
**llama.cpp master** (CUDA sm_86 build
`/home/dank/GitPackages/llama-master/build-cuda/bin/llama-server`) as a
**root systemd unit** (`scripts/frank-small.service`, `relink_unit`ed into
`/etc/systemd/system/`), serving
`bartowski/MiMo-V2.6-Distill-Qwen-9B-GGUF` at **Q5_K_M** (6,876,124,704 B,
sha256 `04cf4f…`) **plus `mmproj-MiMo-V2.6-Distill-Qwen-9B-f16.gguf`**
(918,166,048 B, sha256 `ff348f…`), both `/home/dank/models/MiMo-Q5KM/`, on
port 7771. The 2026-10-02 swap was a **quant rung down from Q6_K**, not a
runtime change — the llama.cpp path arrived 2026-10-01 night for one reason:
**asymmetric KV**. `--cache-type-k f16` + `--cache-type-v q8_0` is the fleet's
only per-tensor KV lever; SGLang's `--kv-cache-dtype` moves K and V together.
Vision came the same day via `--mmproj`: the GGUF carries no `v.*` tensors, so
the projector file is the entire vision path (and ~1.4 GiB of the card).
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]].
**Architecture: qwen3_5 hybrid** — 32 layers, 8 full-attention + 24 Gated
DeltaNet, native 262,144 window. KV exists only in the 8 attention layers
(4 KV heads × 256 dim × 2 B ≈ 2 KiB/token/layer, ~16 KiB/token for f16 K+V);
the DeltaNet state is a fixed per-slot buffer, so slot count — not context —
drives that term.
**The shape:** `--ctx-size 540672 --parallel 3` = **THREE conversations of
180,224 tokens each** (llama.cpp divides the pool:
`n_ctx_slot = CTX_SIZE / PARALLEL`), `--flash-attn on` (the q8_0-V path is
only cheap under flash attention — the seam pins it), f16 K + q8_0 V, all
layers on the GPU, `--mmproj` for vision. Measured VRAM **21,684 used / 2,441
free** of 24,576 MiB — the 2–3 GiB headroom Frank asked for, landed by
solving the pool against two measured boots: non-KV cost is 7,390 MiB without
a projector (2 × 262,144 boot) and 8,859 MiB with one (3 × 196,608 boot), so
vision costs ~1.4 GiB, not the 0.9 GiB the file size suggests. Three native
windows (786,432 tokens) need 18.4 GiB of KV alone and were never on the
table. Full f16 V would add ~4 GiB more and bust the card — that is the
justification for the asymmetric contract.
Verified at deploy (2026-10-02): `/v1/models` reports `frank-small`; boot logs
`n_slots = 3, n_ctx_slot = 180224` and `loaded multimodal model`; decode
**106.8 tok/s** at temp 0 (prefill 3,814 t/s) — ~5 % faster than the
2 × 262,144 shape, because a shorter slot means a shorter attention scan;
three concurrent requests answered in parallel and a fourth queued behind a
released slot; native `tool_calls`; thinking in `reasoning_content`; a
solid-red PNG answers "Red." through an `image_url` content part (the legacy
top-level `images` field is ignored by `/v1/chat/completions` — the model then
invents a color). A prompt over the slot is a **400
`exceed_context_size_error`**, which is why `models.yml` sets
`contextWindow: 180224`.
Runbook: `serverAppConfigs-docs/LLM/frank-small-llama-mimo-q5km.md`.
Rollback: [[frank-small-llama-mimo-q6k]] (Q6_K file on disk at
`/home/dank/models/MiMo-Q6K/`); before that [[frank-small-sglang-mimo-v26]]
(venv on disk at `/home/dank/GitPackages/sglang-cu128/`; its INT8 payload was
staged to `~dank/.AGENTTRASH/20261002-retired-llm-payloads/` on 2026-10-02).
### frank-primary — tcclaviger vLLM, Qwen3.8-Flash-Next FP8 + MTP4 (Dankserver, ACTIVE)
@@ -630,6 +626,26 @@ linked runbooks.
non-greedy requests and reasoning budgets. Re-test chat before production.
- **FastMTP sidecar**: build must be commit `4df29be4` + the HauhauCS patch;
stock binaries fail the draft load with a tensor-shape mismatch.
- **A GGUF's custom tensor type picks the runtime — read the histogram before
promising a file to a loader.** `Qwen3.8-27B-Q8_0_ROCMFPX_AGENT.gguf` is
ftype 115 with 311 tensors of type 103 (`GGML_TYPE_Q8_0_ROCMFPX`); stock
llama.cpp and gufo refuse it at load, so ROCmFPX was not a preference but
the only door. Counting tensor types out of the GGUF KV section takes one
python read and settles a runtime argument in minutes. The build identity
matters as much as the fork: the 2026-08-25 ROCmFPX builds SIGSEGV in
`ggml_compute_forward_set_rows` on this same file, so
`scripts/build-rocmfpx.sh` pins commit `36e9acd` by SHA.
- **Speculative-decode flags move as a SET.** Handing the ROCmFPX fork
`--model-draft` with no `--spec-type` (the naive way to build a "no MTP"
bench arm) segfaulted at load, core dumped, no diagnostic (2026-10-02). A
baseline arm must strip `--model-draft` AND every `--spec-draft-*` AND
`--spec-type`, or it measures a crash instead of the absence of drafting.
- **An orphaned scratch server taxes the whole host.** A bench child left
alive by a client-side exception kept ~26 GiB of weights resident on a
121 GiB box, pushed `available` to 3 GiB, and every later rate was suspect.
Record the child pid and kill it in a `finally`, then prove `free` came back
before believing a number. Kill by pid — never `pkill -f llama-server`,
which also hits frank-small.
**llama.cpp serving**
@@ -702,6 +718,35 @@ linked runbooks.
host-RAM hash table) and its window decides which traffic it can see: too
short and it proposes on ordinary prose fragments, which costs verification
without acceptance.
- **`--parallel` divides the pool, so MORE conversations cost WINDOW, and the
per-slot number is the contract — not `ctx-size`.** `n_ctx_slot =
CTX_SIZE / PARALLEL`, and llama.cpp refuses a prompt longer than the SLOT
(`400 exceed_context_size_error: request (184001 tokens) exceeds the
available context size (180224 tokens)`) even when the pool has room. So
frank-small's 2 → 3 reslice moved each conversation from the model's native
262,144 down to 180,224, and `models.yml` `contextWindow` had to follow or
the harness would discover the ceiling as a 400 on a long conversation. Side
effect worth knowing: the shorter slot made decode ~5 % FASTER (106.8 vs
100.4 tok/s) — less attention to scan and one fewer DeltaNet state resident.
Measured 2026-10-02. See [[frank-small-llama-mimo-q5km]].
- **Price a VRAM budget from two boots, never from a formula — and an mmproj
costs ~1.5x its file size.** The frank-small 3090 fit was solved from two
measurements: 2 × 262,144 with no projector = 20,190 MiB used (KV 12,800 ⇒
**non-KV 7,390**), 3 × 196,608 with the f16 projector = 22,972 used (KV
14,113 ⇒ **non-KV 8,859**). The difference is the vision tower: a 918 MB file
that bills ~1.4 GiB, because the encoder's activation and compute buffers
ride with it. Subtracting the two rows is exact; extrapolating weights+KV+
"a bit for buffers" is what leaves 1.1 GiB free when you meant 2.7. Then
solve `KV ≤ card − non-KV − headroom` and round to a multiple of
`PARALLEL × 4096`. Recorded in `scripts/frank-small.env` so the next resize
starts from measurement.
- **`images` and `image_url` are NOT interchangeable: only the content part
reaches the model.** `--mmproj` loads, `usage.prompt_tokens` rises, and the
model still invents an answer if the client used the legacy top-level
`images` field on `/v1/chat/completions` — frank-small answered "Brown." for
a solid-red PNG that way and "Red." through the OpenAI `image_url` part. The
failure is silent because a hallucinated color is a plausible answer. Probe
vision with a solid color and expect an exact word.
- **`--jinja` is what `tools` needs.** On 2026-09-16 a subagent died with
`500 tools param requires --jinja flag`, from the ik_llama.cpp runtime that
then served frank-large: every tool-using agent on that endpoint was broken
@@ -802,8 +847,8 @@ 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-large (ROCmFPX llama.cpp fork, Qwen3.8-27B Q8_0_ROCMFPX_AGENT + MTP4 + vision, Dankclaw) | `serverAppConfigs-docs/LLM/frank-large-rocmfpx-q8agent-mtp.md` |
| frank-small (llama.cpp CUDA, MiMo-V2.6-Distill-Qwen-9B Q5_K_M, Dankclaw) | `serverAppConfigs-docs/LLM/frank-small-llama-mimo-q5km.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` |
@@ -812,6 +857,10 @@ Retired (rollback targets and history):
| Runtime | Host | Window | Runbook |
|---------|------|--------|---------|
| gufo v0.1.1 Qwen3.8-27B UD-Q8_K_XL/UD-Q4_K_XL + DFlash2 (`frank-large`) | Dankclaw | 2026-09-28 → 10-01, again 10-01 → 10-02 (rollback target) | `frank-large-gufo-qwen38-27b.md` |
| vLLM TheRock MiMo-V2.6-Distill-Qwen-9B BF16 + cross-model MTP (`frank-large`) | Dankclaw | 2026-10-01 (same-day rollback to gufo) | `frank-large-vllm-mimo-v26-bf16.md` |
| llama.cpp master MiMo-V2.6-Distill-Qwen-9B Q6_K (`frank-small`) | Dankclaw | 2026-10-01 → 10-02 (rollback target) | `frank-small-llama-mimo-q6k.md` |
| SGLang MiMo-V2.6 INT8-W8A16-AutoRound (`frank-small`) | Dankclaw | 2026-10-01 (same-day swap to the GGUF path) | `frank-small-sglang-mimo-v26.md` |
|tcclaviger vLLM GLM-5.3-Flash W4A16 int4, +/- DFlash2 drafter (`frank-primary`)|Dankserver|2026-09-30 → 10-01|`frank-primary-glm53-flash-w4a16.md`|
| llama.cpp b11030 Qwen3.8-27B UD-Q8_K_XL + DFlash2 (`frank-large`) | Dankclaw | 2026-09-21 → 09-28 | `frank-large-unsloth-qwen38-27b-q8xl.md` |
| R9V radiance-vLLM Qwen3.8-Flash-Next-Uncensored IQ4_XS (`frank-primary`) | Dankserver | 2026-09-27 (same-day swap to Q8_0) | `frank-primary-r9v-radiance-qwen38-uncensored.md` |
@@ -826,6 +875,7 @@ 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` |
+104
View File
@@ -0,0 +1,104 @@
#!/usr/bin/env bash
# autoresearch.sh — canonical benchmark entrypoint: speed of frank-primary.
#
# Runs on the operator box and drives one bench window on DANKSERVER:
# 1. fingerprint the candidate trio (env + serve script + unit)
# 2. memo fast-path: an identical fingerprint that already produced a FULLY
# successful window (bench + verified production restore) returns the
# cached metrics without touching the fleet
# 3. stage the candidate trio plus the measure client into
# /home/dank/.autoresearch-frank-primary/ (ephemeral; the repo checkout
# on the host stays the production source of truth)
# 4. run the window (scripts/autoresearch/frank-primary-window.sh):
# stop + mask the production unit, boot the staged config AS THE SERVICE
# (same serve script, same container, same port 7770), wait for health,
# run the in-container usage-counter measure, then restore the production
# unit and verify its health — AGENTS.md Benchmarking Policy
# 5. print METRIC lines (parse by run_experiment)
#
# Primary metric: decode_tps (HIGHER is better) — median across the three
# prompt depths (115/1056/4096) of per-depth medians of
# completion_tokens / (wall - ttft), 3 runs each after a warm pass,
# temperature 0, the campaign's deterministic word-seed workload.
#
# Exit 0 with METRIC lines on success; non-zero on any failure (the window
# script's EXIT trap restores production on every path).
set -euo pipefail
SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)"
HOST="${FRANK_PRIMARY_AR_HOST:-dankserver}"
STAGE="/home/dank/.autoresearch-frank-primary"
ENV_FILE="$SCRIPT_DIR/scripts/frank-primary.env"
SERVE="$SCRIPT_DIR/scripts/serve-frank-primary.sh"
UNIT="$SCRIPT_DIR/scripts/frank-primary.service"
MEASURE="$SCRIPT_DIR/scripts/autoresearch/frank-primary-measure.py"
WINDOW="$SCRIPT_DIR/scripts/autoresearch/frank-primary-window.sh"
for f in "$ENV_FILE" "$SERVE" "$UNIT" "$MEASURE" "$WINDOW"; do
[ -f "$f" ] || { echo "[autoresearch] missing harness file: $f" >&2; exit 1; }
done
command -v python3 >/dev/null 2>&1 || { echo "[autoresearch] python3 required on operator box" >&2; exit 1; }
# Fingerprint of everything that can change the engine's argv or environment.
HASH="$(cat "$ENV_FILE" "$SERVE" "$UNIT" | sha256sum | cut -d' ' -f1)"
echo "[autoresearch] candidate fingerprint $HASH" >&2
ssh_run() { ssh -o BatchMode=yes -o ConnectTimeout=15 "$HOST" "$@"; }
emit_metrics() { # $1 = run.json
python3 -c '
import json, sys
run = json.loads(sys.argv[1])
m = run["measure"]
print("METRIC decode_tps=%s" % m["decode_tps"])
for k in ("decode_tps_115", "decode_tps_1056", "decode_tps_4096"):
print("METRIC %s=%s" % (k, m[k]))
print("METRIC ttft_ms_4096=%s" % m["ttft_ms_4096"])
print("METRIC kv_tokens=%s" % (run.get("kv_tokens") or 0))
print("METRIC boot_seconds=%s" % (run.get("boot_seconds") or -1))
print("METRIC completion_tokens_4096=%s" % m.get("completion_tokens_4096", 0))
' "$1"
}
# --- memo fast-path -------------------------------------------------------
cached_hash="$(ssh_run "cat '$STAGE/last/hash' 2>/dev/null" 2>/dev/null || true)"
if [ -n "$cached_hash" ] && [ "$cached_hash" = "$HASH" ]; then
cached_run="$(ssh_run "cat '$STAGE/last/run.json' 2>/dev/null" || true)"
if [ -n "$cached_run" ]; then
echo "[autoresearch] memo hit — cached metrics for $HASH, fleet untouched" >&2
emit_metrics "$cached_run"
exit 0
fi
fi
# --- stage the candidate ----------------------------------------------------
echo "[autoresearch] staging candidate on $HOST:$STAGE" >&2
ssh_run "mkdir -p '$STAGE'"
scp -q "$ENV_FILE" "$HOST:$STAGE/frank-primary.env"
scp -q "$SERVE" "$HOST:$STAGE/serve.sh"
scp -q "$MEASURE" "$HOST:$STAGE/measure.py"
scp -q "$WINDOW" "$HOST:$STAGE/window.sh"
ssh_run "printf '%s\n' '$HASH' > '$STAGE/hash'"
# --- the window -------------------------------------------------------------
# Budgets: bench boot up to 20 min (warm boots measured ~7 min), measure up
# to 30 min, restore boot up to 20 min — call run_experiment with
# timeout_seconds >= 3600.
echo "[autoresearch] opening bench window (stop+mask -> boot -> measure -> restore)" >&2
set +e
ssh_run "bash '$STAGE/window.sh'"
rc=$?
set -e
if [ "$rc" -ne 0 ]; then
echo "[autoresearch] window failed (rc=$rc); host-side evidence:" >&2
ssh_run "tail -60 '$STAGE/fail.log' 2>/dev/null || tail -40 '$STAGE/serve.out' 2>/dev/null || tail -40 '$STAGE/measure.out' 2>/dev/null || true" >&2 || true
exit 1
fi
run_json="$(ssh_run "cat '$STAGE/run.json'")" || {
echo "[autoresearch] could not read $STAGE/run.json back" >&2; exit 1; }
echo "[autoresearch] window result:" >&2
printf '%s\n' "$run_json" >&2
emit_metrics "$run_json"
exit 0
+76
View File
@@ -0,0 +1,76 @@
#!/usr/bin/env bash
# Download the z-lab Qwen3.5-9B-DFlash drafter for frank-large's DFlash
# speculative-decode arm (vLLM --speculative-config method=dflash). Public
# repo — no auth header on the command line.
#
# The drafter is a 6-layer qwen3 draft whose dflash_config pins
# target_layer_ids [1,5,9,13,17,21,25,29] and block_size 16; its hidden_size
# 4096 / vocab_size 248320 match the MiMo-V2.6-Distill-Qwen-9B target exactly
# (both preserve the Qwen3.5-9B geometry), which is what lets vLLM load it as
# the draft for that target.
#
# Usage:
# scripts/download-frank-large-dflash.sh [DEST_DIR] [--verify-only]
set -euo pipefail
REPO="z-lab/Qwen3.5-9B-DFlash"
BASE="https://huggingface.co/${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/Qwen3.5-9B-DFlash}"
# name bytes sha256(- = non-LFS, size-only check)
FILES=(
"model.safetensors 2583816465 0a42274b32554f48de1faa0d42824e9c2ceda649c30ae0a731cddf410dd698c7"
"config.json 1222 -"
)
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"
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"
+90
View File
@@ -0,0 +1,90 @@
#!/usr/bin/env bash
# Download the BF16 MiMo-V2.6-Distill-Qwen-9B payload for frank-large
# (vLLM/kyuz0 gfx1151, Strix Halo iGPU). Public repo — no auth header on the
# command line (a Bearer token in argv is world-readable via /proc).
#
# Per-file FRESH downloads, no resume: the house rule (see
# download-frank-small.sh); -f/--fail-with-body plus size+sha256 against the
# Hub LFS oid is what makes an access error fail instead of "succeeding".
#
# Usage:
# scripts/download-frank-large-mimo.sh [DEST_DIR] [--verify-only]
#
# The verified set below is exactly what the 2026-10-01 bench window served:
# 17.53 GiB of BF16 weights (4 shards, 18,819,720,848 B total with the rest).
set -euo pipefail
REPO="XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B"
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="${DEST:-/home/dank/models/MiMo-V2.6-Distill-Qwen-9B-BF16}"
# name bytes sha256(- = non-LFS, size-only check)
FILES=(
"model-00001-of-00004.safetensors 5276436216 aab052180118aee34abc3029b54eaa49096aac606b97d703866b420dceb703c3"
"model-00002-of-00004.safetensors 5033171280 7a0486565f06d25ac4628e9dba470dc3f604353471d240d5a0bf7128f64df396"
"model-00003-of-00004.safetensors 5234499504 6c73207563d1879bfd6c143a028cc70be68edff56280458c71a43df4240300f4"
"model-00004-of-00004.safetensors 3275613848 1379a7cf8c0b8555a39ab65a47e830e0eb45e776b46045734da3afd73c09eea2"
"model.safetensors.index.json 69217 -"
"config.json 2784 -"
"generation_config.json 126 -"
"chat_template.jinja 3916 -"
"tokenizer.json 19989325 06b9509352d2af50381ab2247e083b80d32d5c0aba91c272ca9ff729b6a0e523"
"tokenizer_config.json 1165 -"
"vocab.json 6722759 -"
"merges.txt 3353259 -"
"preprocessor_config.json 443 -"
"processor_config.json 1191 -"
"video_preprocessor_config.json 385 -"
)
mkdir -p "$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"
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"
+85
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@@ -0,0 +1,85 @@
#!/usr/bin/env bash
# Download the source Qwen3.5-9B checkpoint — the ONLY place this model
# family's MTP head (15 mtp.* tensors) exists. frank-large runs it as the
# vLLM cross-model MTP draft (MiMo-V2.6-Distill-Qwen-9B itself ships zero
# mtp tensors; that is why SGLang's NEXTN on frank-small draws 0.00
# acceptance). Public repo — no auth header on the command line.
#
# NOTE the odd upstream shard names (model.safetensors-0000N-of-00004...).
#
# Usage:
# scripts/download-frank-large-qwen35.sh [DEST_DIR] [--verify-only]
set -euo pipefail
REPO="Qwen/Qwen3.5-9B"
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="${DEST:-/home/dank/models/Qwen3.5-9B}"
# name bytes sha256(- = non-LFS, size-only check)
FILES=(
"model.safetensors-00001-of-00004.safetensors 5276436216 db6f444b43d318c92f360a13a25561a6a65b10c0631b8ed305a426dbaa6c380e"
"model.safetensors-00002-of-00004.safetensors 5335161512 31c7d7e2dd5d207840b31cc59083c8f4c4718959149e0358c0364052bb9a0330"
"model.safetensors-00003-of-00004.safetensors 5368717440 7ec36ba3a4176a44c3c0876ad80c56a2f70c84bf008d82e9501df642f17dadec"
"model.safetensors-00004-of-00004.safetensors 3325995712 b62b0c4cd7e44edee103ee8f4fe225f246d5e768e07bfd5f25b63a8aa1fdd0c6"
"model.safetensors.index.json 79657 -"
"config.json 3126 -"
"chat_template.jinja 7756 -"
"tokenizer.json 12807982 5f9e4d4901a92b997e463c1f46055088b6cca5ca61a6522d1b9f64c4bb81cb42"
"tokenizer_config.json 16710 -"
"vocab.json 6722759 -"
"merges.txt 3353259 -"
"preprocessor_config.json 390 -"
"video_preprocessor_config.json 385 -"
)
mkdir -p "$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"
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"
+93
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@@ -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"
+141
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@@ -0,0 +1,141 @@
#!/usr/bin/env python3
"""autoresearch-bench.py — deterministic greedy battery for frank-large.
Runs ON Dankclaw (no LAN jitter) against the candidate container on :7770.
Fixed embedded corpus, temperature 0, streaming so decode speed is measured
between real token arrivals (not request totals). Median of REPS samples per
metric is the reported value; medians are far more stable than means under
GPU thermal drift.
Metrics emitted (stdout, one per line):
METRIC decode_tokens_per_sec=<float> primary, higher better
METRIC prefill_tokens_per_sec=<float> secondary
METRIC ttft_ms=<float> secondary, lower better
Exit non-zero if the endpoint is unhealthy or the served alias is wrong.
"""
import argparse
import json
import statistics
import sys
import time
import urllib.request
# Fixed corpus: deterministic, ~28k tokens after tokenization (same scale as
# the 2026-10-01 bench window). Built by repeating a fixed paragraph block a
# fixed number of times - NO random, NO clock, NO network.
_BLOCK = (
"The rendering pipeline walks the scene graph once per frame, resolving "
"material bindings into descriptor sets before any draw call is recorded. "
"Because the allocator recycles command buffers only after their fence "
"signals, a submission that outlives its frame must pin the pool entry; "
"otherwise the next frame overwrites recorded commands in flight. The "
"validation layer flags exactly this class of lifetime bug, but only for "
"buffers it can see - GPU-side timestamps and queue-family ownership "
"transfers hide in the driver's own bookkeeping, which is why release "
"builds must lean on explicit barriers and why a frame-time regression "
"often shows up as corruption one frame later than its cause.\n"
)
LONG_CTX = _BLOCK * 220 # ~28k-token prefill, matching the deployed workload
_LONG = LONG_CTX + "\nNow, in one focused paragraph (80-150 words), explain " \
"which lifetime bugs this pipeline can still suffer and what explicit " \
"mitigations the text implies."
_SHORT = "Design a rate limiter for a homelab reverse proxy that must not " \
"lock out the LAN. Think it through, then give the algorithm."
REPS = 3
MAX_TOKENS = 256
REQ_TIMEOUT = 900
def stream_completion(url: str, model: str, prompt: str):
"""Greedy streaming completion.
Returns (ttft_s, decode_tps, prefill_tps, prompt_tokens, n_tokens).
ttft is RELATIVE to request send: time.perf_counter()'s epoch is host
boot, and returning the raw stamp read as an 11-day first token.
"""
body = json.dumps({
"model": model,
"messages": [{"role": "user", "content": prompt}],
"max_tokens": MAX_TOKENS,
"temperature": 0,
"stream": True,
"stream_options": {"include_usage": True},
}).encode()
req = urllib.request.Request(
url.rstrip("/") + "/v1/chat/completions", data=body,
headers={"Content-Type": "application/json"})
t0 = time.perf_counter()
first = None
stamps = []
usage = {}
with urllib.request.urlopen(req, timeout=REQ_TIMEOUT) as resp:
for raw in resp:
line = raw.decode(errors="replace").strip()
if not line.startswith("data:"):
continue
payload = line[5:].strip()
if payload == "[DONE]":
break
chunk = json.loads(payload)
if chunk.get("usage"):
usage = chunk["usage"]
for ch in chunk.get("choices", []):
d = ch.get("delta") or {}
# reasoning AND content deltas both arrive token by token;
# count either so greedy text length drives the rate.
# (llama.cpp names the thinking field reasoning_content.)
if d.get("content") or d.get("reasoning") or d.get("reasoning_content"):
now = time.perf_counter()
if first is None:
first = now
stamps.append(now)
if first is None or len(stamps) < 2:
# A zero-argmax degenerate answer would poison the median; raise.
raise RuntimeError(f"stream produced {len(stamps)} tokens")
ttft_s = first - t0
decode_s = stamps[-1] - stamps[0]
decode_tps = (len(stamps) - 1) / decode_s if decode_s > 0 else 0.0
prompt_tokens = usage.get("prompt_tokens") or 0
prefill_tps = prompt_tokens / ttft_s if prompt_tokens else 0.0
return ttft_s, decode_tps, prefill_tps, prompt_tokens, len(stamps)
def main():
ap = argparse.ArgumentParser()
ap.add_argument("--url", default="http://127.0.0.1:7770")
ap.add_argument("--model", default="frank-large")
args = ap.parse_args()
with urllib.request.urlopen(args.url.rstrip("/") + "/v1/models",
timeout=10) as r:
ids = [m["id"] for m in json.load(r)["data"]]
if args.model not in ids:
print(f"FATAL: served ids {ids}, expected {args.model}",
file=sys.stderr)
sys.exit(2)
# Warmup (compile/graph warm + allocator settle), NOT measured.
stream_completion(args.url, args.model, _SHORT)
decodes, prefills, ttfts = [], [], []
for rep in range(REPS):
for name, prompt in (("long", _LONG), ("short", _SHORT)):
ttft, dt, pt, ptk, ntok = stream_completion(
args.url, args.model, prompt)
decodes.append(dt)
ttfts.append(ttft * 1000.0)
if name == "long":
prefills.append(pt)
print(f" rep{rep} {name:5s} ttft={ttft*1000:8.1f}ms "
f"prefill={pt:8.1f} t/s decode={dt:6.2f} t/s "
f"({ntok} tok, prompt {ptk})", file=sys.stderr)
med = lambda xs: statistics.median(xs)
print(f"METRIC decode_tokens_per_sec={med(decodes):.2f}")
print(f"METRIC prefill_tokens_per_sec={med(prefills):.1f}")
print(f"METRIC ttft_ms={med(ttfts):.1f}")
if __name__ == "__main__":
main()
+192
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#!/usr/bin/env python3
"""frank-primary decode measurement — runs INSIDE the engine container.
The method is the fleet's established one (the 2026-09-29 / 2026-10-01
tuning campaigns, /home/dank/mtp_measure.py): SSE chunk counting is invalid
under speculative decoding because rejected drafts change the accounting, so
decode is measured from the server's own usage counters:
decode_tok_s = completion_tokens / (wall - ttft)
with ttft = wall time to the FIRST content-bearing chunk (thinking arrives in
`reasoning`/`delta.reasoning` on this stack and is excluded from the decode
window — and is deterministic per prompt at temperature 0, so the exclusion
cancels in any A/B on the same workload).
Workload (fixed, deterministic, offline):
* prompts built from a large fixed-seed shuffled word list so tokens rarely
repeat (no n-gram/prefix predictability of the text itself), sized with
the server's own /v1/messages/count_tokens counter
* depths 115 / 1056 / 4096 target prompt tokens
* one 64-token warm pass per depth (warms the expert arena), then
max_tokens=256 at temperature 0, 3 runs, median
Everything is greedy with a fixed seed — the same workload every run, no
network, no time-of-day dependence.
Env:
AR_BASE endpoint (default http://127.0.0.1:7770)
AR_MODEL served name (default frank-primary)
AR_PROMPT_CEILING hard prompt ceiling in tokens (default 100000)
Output: progress on stderr, ONE json object on stdout (the last line).
Exit codes: 0 ok, 2 endpoint unhealthy / no usable completion, 3 bad usage.
"""
import json
import os
import random
import statistics
import sys
import time
import urllib.error
import urllib.request
BASE = os.environ.get("AR_BASE", "http://127.0.0.1:7770")
MODEL = os.environ.get("AR_MODEL", "frank-primary")
PROMPT_CEILING = int(os.environ.get("AR_PROMPT_CEILING", "100000"))
DEPTHS = (115, 1056, 4096)
WARM_TOKENS = 64
MAX_TOKENS = 256
RUNS = 3
# 43-word x 12 = 516-word vocabulary, seed 1234 — the campaign's exact list
# and seed, so prompts are byte-identical to the historical measurements.
_VOCAB = ("alpha bravo charlie delta echo foxtrot golf hotel india juliet kilo lima "
"mike november oscar papa quebec romeo sierra tango uniform victor whiskey "
"xray yankee zulu cardinal ordinal topology kernel scheduler resident "
"unified aperture expert arena slab offload prefetch gemm triton quant "
"tensor shard checkpoint manifest embed router cache page table window "
"gradient sparse dense moe attention head dim block stream decode prefill "
"bandwidth latency throughput residency eviction tier swap pin memlock").split()
_R = random.Random(1234)
_ORDER = list(range(len(_VOCAB)))
_R.shuffle(_ORDER)
def log(msg):
print("[measure] %s" % msg, file=sys.stderr, flush=True)
def post_json(path, body, timeout):
req = urllib.request.Request(
BASE + path, data=json.dumps(body).encode(),
headers={"Content-Type": "application/json"})
with urllib.request.urlopen(req, timeout=timeout) as r:
return json.load(r)
def count_tokens(text):
"""Token count without a prefill, from the server's own counter."""
body = {"model": MODEL,
"messages": [{"role": "user", "content": text}]}
r = post_json("/v1/messages/count_tokens", body, timeout=300)
n = r.get("input_tokens") or r.get("count") or r.get("token_count")
if not n:
raise RuntimeError("count_tokens returned no count: %r" % (r,))
return int(n)
def words(n):
return " ".join(_VOCAB[_ORDER[i % len(_VOCAB)]] for i in range(n))
def calibrate():
"""Measure words->tokens from the server's own counter."""
return 2000.0 / count_tokens(words(2000))
def prompt_for(target_tokens, wpt):
n = max(1, int(target_tokens * wpt))
text = words(n)
pt = count_tokens(text)
while pt > PROMPT_CEILING:
n = max(1, int(n * (PROMPT_CEILING / pt) * 0.98))
text = words(n)
pt = count_tokens(text)
return text, pt
def measured(prompt, max_tokens):
"""Return (ttft_s, decode_tok_s, completion_tokens) via usage counters."""
body = {"model": MODEL,
"messages": [{"role": "user", "content": prompt}],
"max_tokens": max_tokens, "temperature": 0,
"stream": True, "stream_options": {"include_usage": True}}
req = urllib.request.Request(
BASE + "/v1/chat/completions", data=json.dumps(body).encode(),
headers={"Content-Type": "application/json"})
t0 = time.time()
ttft = None
usage = {}
with urllib.request.urlopen(req, timeout=1800) as r:
for raw in r:
line = raw.decode("utf-8", "replace").strip()
if not line.startswith("data:"):
continue
s = line[5:].strip()
if s == "[DONE]":
break
try:
ev = json.loads(s)
except json.JSONDecodeError:
continue
if ev.get("usage"):
usage = ev["usage"]
for ch in ev.get("choices", []):
if (ch.get("delta") or {}).get("content"):
if ttft is None:
ttft = time.time() - t0
wall = time.time() - t0
ct = int(usage.get("completion_tokens") or 0)
if ct <= 0:
# No usage on the stream: the endpoint is unhealthy or the model
# returned nothing (e.g. HTTP 200 with an error payload).
raise RuntimeError("no completion_tokens in usage: %r" % (usage,))
dec_window = max(wall - (ttft or 0.0), 1e-9)
return (ttft or wall), (ct / dec_window), ct
def main():
log("base=%s model=%s ceiling=%d" % (BASE, MODEL, PROMPT_CEILING))
try:
wpt = calibrate()
except Exception as e:
log("endpoint unhealthy during calibration: %s" % e)
return 2
log("words/token: %.3f" % wpt)
result = {"words_per_token": round(wpt, 5)}
for tgt in DEPTHS:
try:
p, pt = prompt_for(tgt, wpt)
measured(p, WARM_TOKENS) # warm the arena
except Exception as e:
log("warm pass failed at depth %d: %s" % (tgt, e))
return 2
rates, tts, cts = [], [], []
for i in range(RUNS):
try:
tt, r, ct = measured(p, MAX_TOKENS)
except Exception as e:
log("run %d/%d failed at depth %d: %s" % (i + 1, RUNS, tgt, e))
continue
rates.append(r)
tts.append(tt)
cts.append(ct)
if len(rates) < 2:
log("only %d usable run(s) at depth %d — refusing to median" % (len(rates), tgt))
return 2
result["decode_tps_%d" % tgt] = round(statistics.median(rates), 2)
result["ttft_ms_%d" % tgt] = round(1000.0 * statistics.median(tts), 1)
result["completion_tokens_%d" % tgt] = int(statistics.median(cts))
result["prompt_tokens_%d" % tgt] = pt
log("depth %5d tok decode %.2f t/s ttft %.3f s (runs=%d)"
% (pt, result["decode_tps_%d" % tgt], result["ttft_ms_%d" % tgt] / 1000.0, len(rates)))
meds = [result["decode_tps_%d" % t] for t in DEPTHS]
result["decode_tps"] = round(statistics.median(meds), 2)
print(json.dumps(result))
return 0
if __name__ == "__main__":
sys.exit(main())
+200
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@@ -0,0 +1,200 @@
#!/usr/bin/env bash
# frank-primary-window.sh — one full bench window for frank-primary, run ON
# DANKSERVER as the deploy user (invoked over ssh by ./autoresearch.sh).
#
# Discipline (AGENTS.md Benchmarking Policy): the production unit is
# STOPPED + MASKED first, the candidate config boots AS THE SERVICE itself
# (same serve script, same container name, same port 7770 — no scratch
# ports, no co-tenant GPU), the in-container measure runs, and the window
# ALWAYS ends by restoring the production unit and verifying its health.
# The EXIT trap makes the restore unconditional: a boot failure, a measure
# failure, or a dead ssh session all end with production back up.
#
# Staging layout (created by the orchestrator, ephemeral — never a config
# source; the repo checkout is):
# /home/dank/.autoresearch-frank-primary/
# serve.sh staged candidate serve script
# frank-primary.env staged candidate env (the candidate knobs)
# measure.py the in-container measure client
# hash candidate fingerprint
# run.json result (metrics + boot + kv + fingerprint)
# serve.out/measure.out/fail.log
# last/ memo: run.json + hash of the last FULLY
# successful window (bench AND verified restore)
#
# This script logs to stderr and exits 0 only when the measure produced a
# usable result (the restore happens in the trap regardless of the bench
# outcome; a failed restore forces exit 1).
set -uo pipefail
STAGE="${FRANK_PRIMARY_AR_STAGE:-/home/dank/.autoresearch-frank-primary}"
UNIT="${FRANK_PRIMARY_AR_UNIT:-frank-primary}"
CTR="${FRANK_PRIMARY_AR_CTR:-frank-primary-qwen}"
HEALTH_URL="http://127.0.0.1:7770/health"
MODELS_URL="http://127.0.0.1:7770/v1/models"
BOOT_TIMEOUT="${FRANK_PRIMARY_AR_BOOT_TIMEOUT:-1200}"
RESTORE_TIMEOUT="${FRANK_PRIMARY_AR_RESTORE_TIMEOUT:-1200}"
MEASURE_TIMEOUT="${FRANK_PRIMARY_AR_MEASURE_TIMEOUT:-1800}"
SERVED="$(sed -n 's/^FRANK_PRIMARY_SERVED_NAME=//p' "$STAGE/frank-primary.env" 2>/dev/null | head -1)"
SERVED="${SERVED:-frank-primary}"
RESTORED=0
log() { printf '[window %s] %s\n' "$(date '+%H:%M:%S')" "$*" >&2; }
container_state() { podman inspect -f '{{.State.Status}}' "$CTR" 2>/dev/null || echo absent; }
wait_port_free() {
local i
for i in $(seq 1 90); do
[ "$(container_state)" != "running" ] && return 0
sleep 2
done
return 1
}
wait_health() { # $1 = timeout seconds
local t0 code
t0=$(date +%s)
while :; do
code="$(curl -s -o /dev/null -w '%{http_code}' --max-time 10 "$HEALTH_URL" 2>/dev/null || echo 000)"
[ "$code" = "200" ] && return 0
[ "$(( $(date +%s) - t0 ))" -ge "$1" ] && return 1
sleep 2
done
}
capture_bench_failure() {
log "capturing bench-boot failure evidence"
{
echo "=== podman logs (tail 400) ==="
podman logs --tail 400 "$CTR" 2>&1 || true
echo "=== staged serve.out (tail 60) ==="
tail -60 "$STAGE/serve.out" 2>/dev/null || true
echo "=== engine log (tail 60) ==="
tail -60 /home/dank/logs/frank_primary.log 2>/dev/null || true
} >"$STAGE/fail.log" 2>&1 || true
grep -E 'OutOfMemory|Tried to allocate|Engine core initialization failed|Error|error' \
"$STAGE/fail.log" 2>/dev/null | tail -25 >&2 || true
}
restore() {
[ "$RESTORED" = 1 ] && return 0
RESTORED=1
log "restoring production unit $UNIT"
if [ -f "$STAGE/serve.pid" ]; then
kill "$(cat "$STAGE/serve.pid" 2>/dev/null)" 2>/dev/null || true
fi
podman stop -t 120 "$CTR" >/dev/null 2>&1 || true
wait_port_free || log "WARNING: bench container still draining after 180s"
sudo systemctl unmask "$UNIT" 2>/dev/null || true
if ! sudo systemctl start "$UNIT"; then
log "ERROR: systemctl start $UNIT failed — operator intervention required"
return 1
fi
if wait_health "$RESTORE_TIMEOUT"; then
if curl -s --max-time 10 "$MODELS_URL" 2>/dev/null | grep -q "$SERVED"; then
log "production restored and verified ($SERVED answering on :7770)"
# Memo promotion lives HERE: a cached result is only ever the
# product of a fully successful window (bench AND verified
# restore), never of a bare bench success.
cp "$STAGE/run.json" "$STAGE/last/" 2>/dev/null || true
cp "$STAGE/hash" "$STAGE/last/" 2>/dev/null || true
else
log "ERROR: health 200 but /v1/models does not list $SERVED"
return 1
fi
else
log "ERROR: production not healthy within ${RESTORE_TIMEOUT}s — unit left to systemd (Restart=always)"
return 1
fi
return 0
}
trap 'restore; rc=$?; [ "$rc" -ne 0 ] && exit 1' EXIT
main() {
local f
for f in serve.sh frank-primary.env measure.py hash; do
[ -f "$STAGE/$f" ] || { log "staged file missing: $STAGE/$f"; exit 1; }
done
mkdir -p "$STAGE/last"
rm -f "$STAGE/run.json" "$STAGE/fail.log" "$STAGE/measure.out"
local t_start t0 i kvline kv_tokens kv_conc measure_json boot_seconds
t_start="$(date +%s)"
log "stopping and masking production unit $UNIT"
sudo systemctl stop "$UNIT" 2>/dev/null || true
# Explicit stop is not auto-restarted even with Restart=always; the mask
# is belt-and-braces against a stray start during the window.
sudo systemctl mask "$UNIT" 2>/dev/null || \
log "WARNING: mask failed — relying on explicit-stop semantics"
wait_port_free || log "note: production container still draining"
t0="$(date +%s)"
log "starting bench instance from staged config (fingerprint $(tr -d '[:space:]' <"$STAGE/hash"))"
FRANK_PRIMARY_ENV_FILE="$STAGE/frank-primary.env" \
setsid nohup bash "$STAGE/serve.sh" >"$STAGE/serve.out" 2>&1 </dev/null &
echo "$!" >"$STAGE/serve.pid"
for i in $(seq 1 45); do
[ "$(container_state)" = "running" ] && break
sleep 2
done
if [ "$(container_state)" != "running" ]; then
log "bench container never reached running state"
tail -40 "$STAGE/serve.out" >&2 || true
exit 1
fi
if wait_health "$BOOT_TIMEOUT"; then
boot_seconds=$(( $(date +%s) - t0 ))
log "bench healthy after ${boot_seconds}s"
else
if [ "$(container_state)" = "running" ]; then
log "bench boot timed out after ${BOOT_TIMEOUT}s (still loading)"
else
log "bench container died during boot"
capture_bench_failure
fi
exit 1
fi
log "running measure in container (timeout ${MEASURE_TIMEOUT}s)"
if ! podman cp "$STAGE/measure.py" "$CTR":/tmp/ar-measure.py; then
log "podman cp of measure client failed"
exit 1
fi
if ! timeout "$MEASURE_TIMEOUT" podman exec "$CTR" python3 /tmp/ar-measure.py \
>"$STAGE/measure.out" 2>&1; then
log "measure failed or timed out"
tail -40 "$STAGE/measure.out" >&2 || true
exit 1
fi
# Capacity facts for the run (context-size experiments change these).
kvline="$(podman logs "$CTR" 2>&1 | grep -E 'GPU KV cache size' | tail -1 || true)"
kv_tokens="$(printf '%s' "$kvline" | sed -E 's/.*GPU KV cache size: ([0-9,]+) tokens.*/\1/' | tr -d ',' || true)"
kv_conc="$(printf '%s' "$kvline" | sed -E 's/.*per request: ([0-9.]+x).*/\1/' || true)"
measure_json="$(grep -E '^\{' "$STAGE/measure.out" | tail -1 || true)"
if [ -z "$measure_json" ]; then
log "measure produced no JSON result line"
tail -40 "$STAGE/measure.out" >&2 || true
exit 1
fi
# The measure line is already JSON, so the run object can be assembled
# without any host-side interpreter.
printf '{"hash":"%s","boot_seconds":%s,"kv_tokens":%s,"kv_concurrency":"%s","total_seconds":%s,"measure":%s}\n' \
"$(tr -d '[:space:]' <"$STAGE/hash")" \
"$boot_seconds" "${kv_tokens:-0}" "${kv_conc:-unknown}" \
"$(( $(date +%s) - t_start ))" "$measure_json" >"$STAGE/run.json"
log "bench window complete in $(( $(date +%s) - t_start ))s"
# Memo only after a FULL success; the restore below still has to verify.
exit 0
}
main "$@"
exit "$?"
+89
View File
@@ -0,0 +1,89 @@
#!/usr/bin/env bash
# Build the ROCmFPX runtime that serves frank-large on Dankclaw.
#
# bash scripts/build-rocmfpx.sh # clone/fetch + build the pin
# bash scripts/build-rocmfpx.sh --verify # only check the installed tree
#
# Runtime: kingjones30/ROCmFPX — charlie12345/ROCmFPX plus the model-card
# patches, i.e. the fork that owns the ROCmFPx tensor formats. frank-large's
# payload is ftype 115 (`Q8_0_ROCMFPX_AGENT`): 311 tensors of
# GGML_TYPE_Q8_0_ROCMFPX (103), a type that exists ONLY in this fork, so
# stock llama.cpp, gufo and every other loader on the host reject the file.
# This is the same tree that served the Qwen3.8-Flash-Next ROCmFP4 STRIX
# endpoint 2026-08-30 → 09-11 (see the kingjones runbook), rebuilt here so a
# fresh host can be brought up from the repo alone.
#
# Why this commit and not a newer one: 36e9acd (2026-08-28) is what was
# qualified against this payload on 2026-10-02 — it loads ftype 115, survives
# warmup, and drafts with the MTP head at acceptance 0.65. The five legacy
# builds of 2026-08-25 crashed this same file in ggml_compute_forward_set_rows
# (see kingjones-q8agent-rocmfpx.md), so the pin is load-bearing: do not bump
# it without re-running that crash test.
#
# Host notes:
# * -DLLAMA_BUILD_WEBUI=OFF is REQUIRED on this box. The tree provisions its
# embedded UI assets via npm or the HF llama-ui bucket; npm is absent here
# and the bucket download half-failed, aborting the link at 98%. The API
# server is unaffected.
# * The build links against the host ROCm (/opt/rocm); no bundled toolchain
# like the gfx1201 R9700 build needed.
set -euo pipefail
ROCMFPX_REPO="${ROCMFPX_REPO:-https://github.com/kingjones30/ROCmFPX.git}"
# The commit frank-large was qualified with (measured 2026-10-02).
ROCMFPX_COMMIT="${ROCMFPX_COMMIT:-36e9acd40e10a87cd3c3ef8ec734668757dc8520}"
SRC_DIR="${ROCMFPX_SRC_DIR:-/home/dank/GitPackages/kingjones-ROCmFPX}"
BUILD_DIR="${ROCMFPX_BUILD_DIR:-$SRC_DIR/build}"
GPU_TARGET="${ROCMFPX_GPU_TARGET:-gfx1151}"
JOBS="${JOBS:-$(nproc)}"
# check_pin — refuse a source tree that is not the qualified commit. A moved
# fork means different kernels under the same path, and on this model line a
# wrong build is a segfault at first request, not a clean error.
check_pin() {
local commit
commit="$(git -C "$SRC_DIR" rev-parse HEAD 2>/dev/null || true)"
if [[ -n "$commit" && "$commit" != "$ROCMFPX_COMMIT" ]]; then
echo "ROCMFPX_COMMIT mismatch: $SRC_DIR is at $commit, pinned $ROCMFPX_COMMIT" >&2
exit 1
fi
}
if [[ "${1:-}" == "--verify" ]]; then
check_pin
[[ -x "$BUILD_DIR/bin/llama-server" ]] || {
echo "no ROCmFPX llama-server at $BUILD_DIR/bin/llama-server" >&2
exit 1
}
# The format the endpoint exists for: the fork must carry the ROCmFPx
# tensor type, or the payload cannot load at all.
"$BUILD_DIR/bin/llama-server" --help 2>&1 | grep -q -- '--spec-type' || {
echo "$BUILD_DIR/bin/llama-server has no --spec-type: MTP drafting is impossible" >&2
exit 1
}
"$BUILD_DIR/bin/llama-server" --version | head -1
exit 0
fi
echo "== source: $ROCMFPX_REPO @ $ROCMFPX_COMMIT =="
if [[ ! -d "$SRC_DIR/.git" ]]; then
mkdir -p "$(dirname "$SRC_DIR")"
git clone "$ROCMFPX_REPO" "$SRC_DIR"
fi
git -C "$SRC_DIR" fetch --quiet origin "$ROCMFPX_COMMIT" || true
git -C "$SRC_DIR" checkout -q --detach "$ROCMFPX_COMMIT"
check_pin
echo " $(git -C "$SRC_DIR" rev-parse HEAD)"
echo "== configure + build (release, HIP $GPU_TARGET) =="
cmake -S "$SRC_DIR" -B "$BUILD_DIR" \
-DGGML_HIP=ON \
-DGPU_TARGETS="$GPU_TARGET" \
-DGGML_NATIVE=ON \
-DCMAKE_BUILD_TYPE=Release \
-DLLAMA_BUILD_WEBUI=OFF
cmake --build "$BUILD_DIR" --target llama-server llama-quantize -j "$JOBS"
echo "== verify =="
"$BUILD_DIR/bin/llama-server" --version | head -1
echo "frank-large runtime ready: $BUILD_DIR/bin/llama-server ($ROCMFPX_COMMIT)"
+72 -44
View File
@@ -1077,27 +1077,29 @@ deploy_anubis() {
wait_container_healthy anubis 60 || return 1
}
# frank-large is gufo (gufo-org/gufo), the Strix Halo inference engine built
# from the pinned v0.1.1 tag by scripts/build-gufo.sh, serving
# unsloth/Qwen3.8-27B-GGUF:UD-Q8_K_XL with the DFlash2 drafter
# (z-lab/Qwen3.8-27B-DFlash2-GGUF:Q4_K_M) on the Strix Halo iGPU. It is a
# ROOT unit: the runtime is a native binary linked against the host ROCm,
# so there is no container image to install and no generated unit to dodge.
# relink_unit points /etc/systemd/system/frank-large.service at the repo
# file and boot persistence is that unit's [Install] section.
# frank-large is the ROCmFPX fork of llama.cpp (kingjones30/ROCmFPX, pinned by
# scripts/build-rocmfpx.sh), serving
# kingjones777/Qwen3.8-27B-ROCmFP4-STRIX-MTP-GGUF:Q8_0_ROCMFPX_AGENT with the
# repo's own Q4_0 MTP draft head and its BF16 vision projector, on the Strix
# Halo iGPU. It is a ROOT unit: the runtime is a native binary linked against
# the host ROCm, so there is no container image to install and no generated
# unit to dodge. relink_unit points /etc/systemd/system/frank-large.service at
# the repo file and boot persistence is that unit's [Install] section.
#
# The runtime gate matters as much as the payload gate: gufo is built from
# source on this host (there is no prebuilt release), so a machine whose
# The runtime gate matters as much as the payload gate: the fork is built from
# source on this host, and the payload is ftype 115 (tensor type 103,
# GGML_TYPE_Q8_0_ROCMFPX) which only this fork can read — so a machine whose
# /home/dank/GitPackages tree was never built has a unit that can never
# become healthy, and a green deploy would leave the endpoint dark.
#
# It replaces the stock llama.cpp prebuilt (unsloth b11030), which had
# replaced the Kairic Edge runtime (ciru-ai/ROCmFPX). The port gate is the
# same as every cutover since 2026-09-16: nothing starts until 7770 is
# released.
LLM_LARGE_RUNTIME="${LLM_LARGE_RUNTIME:-/home/dank/GitPackages/gufo-v0.1.1/bin/gufo}"
LLM_LARGE_MODEL="${LLM_LARGE_MODEL:-/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}"
LLM_LARGE_DRAFT="${LLM_LARGE_DRAFT:-/home/dank/models/Qwen3.8-27B-UD-Q8_K_XL/Qwen3.8-27B-DFlash2-Q4_K_M.gguf}"
# It replaces gufo v0.1.1 + unsloth UD-Q4_K_XL (the rollback target, still
# built by scripts/build-gufo.sh with its payload on disk), which had replaced
# the stock llama.cpp prebuilt. The port gate is the same as every cutover
# since 2026-09-16: nothing starts until 7770 is released.
LLM_LARGE_RUNTIME="${LLM_LARGE_RUNTIME:-/home/dank/GitPackages/kingjones-ROCmFPX/build/bin/llama-server}"
LLM_LARGE_MODEL="${LLM_LARGE_MODEL:-/home/dank/models/kingjones-Qwen3.8-27B-ROCmFP4-STRIX-MTP/Qwen3.8-27B-Q8_0_ROCMFPX_AGENT.gguf}"
LLM_LARGE_DRAFT="${LLM_LARGE_DRAFT:-/home/dank/models/kingjones-Qwen3.8-27B-ROCmFP4-STRIX-MTP/mtp-Qwen3.8-27B-Q4_0.gguf}"
LLM_LARGE_MMPROJ="${LLM_LARGE_MMPROJ:-/home/dank/models/kingjones-Qwen3.8-27B-ROCmFP4-STRIX-MTP/mmproj-Qwen3.8-27B-BF16.gguf}"
retire_halogen_large_quadlet() {
local trash="$HOME/.AGENTTRASH/20260919-orca-cutover/quadlet"
@@ -1132,17 +1134,19 @@ wait_port_free() {
deploy_llm_large() {
# 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 deploy log to say why.
# endpoint dark with nothing in the deploy log to say why. The gates
# mirror serve-frank-large.sh's own predicates exactly: runtime
# executable, target GGUF, MTP head, mmproj.
if [[ ! -x "$LLM_LARGE_RUNTIME" ]]; then
echo "ERROR: gufo runtime absent at $LLM_LARGE_RUNTIME" >&2
echo "frank-large: build it: bash scripts/build-gufo.sh" >&2
echo "ERROR: ROCmFPX runtime absent at $LLM_LARGE_RUNTIME" >&2
echo "frank-large: build it: bash scripts/build-rocmfpx.sh" >&2
return 1
fi
local missing=0 f
for f in "$LLM_LARGE_MODEL" "$LLM_LARGE_DRAFT"; do
for f in "$LLM_LARGE_MODEL" "$LLM_LARGE_DRAFT" "$LLM_LARGE_MMPROJ"; do
if [[ ! -f "$f" ]]; then
echo "ERROR: payload absent at $f" >&2
echo "frank-large: fetch it: bash scripts/download-frank-large.sh" >&2
echo "frank-large: fetch it: bash scripts/download-frank-large-kingjones.sh" >&2
missing=1
fi
done
@@ -1152,18 +1156,14 @@ deploy_llm_large() {
# On a re-deploy the predecessor is THIS unit: stop it before waiting on
# the port, or the wait deadlocks on the server it just stopped serving.
# Then sweep a stray manual run -- that is how a bench harness leaves the
# port busy. Match the DRAFTER path, which every frank-large command
# line carries via --dflash-model and which is UNCHANGED by the 2026-09-28
# payload swap: the target moved to a different repository while the
# drafter stayed put, so keying on the target filename would have quietly
# stopped matching. It is also the right key in principle — it names this
# endpoint's speculative drafter, not a binary. Match that, not a binary
# name: frank-small on this host serves a different GGUF over llama-server
# with no DFlash2 drafter and must not be killed. The pattern never
# appears in the deploying shell's own command line, so -f is safe here
# (it is not in `bash deploy-remote.sh`).
# port busy. Match the TARGET GGUF name, which every frank-large command
# line carries via --model and which no other process on this host uses:
# frank-small also runs llama-server here (with the MiMo GGUF) and must
# not be killed, so keying on the binary name would take the 3090 endpoint
# down with it. The pattern never appears in the deploying shell's own
# command line, so -f is safe here (it is not in `bash deploy-remote.sh`).
run_privileged systemctl stop frank-large.service 2>/dev/null || true
pkill -f 'Qwen3.8-27B-DFlash2-Q4_K_M' 2>/dev/null || true
pkill -f 'Qwen3.8-27B-Q8_0_ROCMFPX_AGENT' 2>/dev/null || true
# Nothing may start until the predecessor has released the port. On
# 2026-09-16 the cutover failed exactly here: the old server logged
# "Deactivated successfully", the next engine tried to bind 7770 a second
@@ -1177,28 +1177,56 @@ 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 llama.cpp (master build, CUDA sm_86) on
# the RTX 3090 as a ROOT unit: the runtime is a native binary tree under
# ~/GitPackages/llama-master/build-cuda, so there is no container image and
# no generated unit to avoid. relink_unit points
# /etc/systemd/system/frank-small.service at the repo file and boot
# 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_FILE="${LLM_SMALL_MODEL_FILE:-/home/dank/models/MiMo-Q5KM/MiMo-V2.6-Distill-Qwen-9B-Q5_K_M.gguf}"
LLM_SMALL_RUNTIME="${LLM_SMALL_RUNTIME:-/home/dank/GitPackages/llama-master/build-cuda/bin/llama-server}"
# The projector IS the vision capability here: the Q5_K_M GGUF ships no `v.*`
# tensors, so a deploy that starts without this file silently ships a
# text-only endpoint. Checked unconditionally, like frank-large's.
LLM_SMALL_MMPROJ="${LLM_SMALL_MMPROJ:-/home/dank/models/MiMo-Q5KM/mmproj-MiMo-V2.6-Distill-Qwen-9B-f16.gguf}"
deploy_llm_small() {
if [[ ! -f "$LLM_SMALL_MODEL" ]]; then
echo "ERROR: model absent at $LLM_SMALL_MODEL" >&2
echo "frank-small: fetch HauhauCS/Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced (Q4_K_M, the mmproj and the MTP sidecar) first;" >&2
echo "frank-small: refusing to start a unit that cannot load." >&2
# Refuse rather than restart-loop: a unit whose runtime or payload is
# missing never becomes healthy, and a green deploy would leave the
# endpoint dark with nothing in the log to say why.
if [[ ! -x "$LLM_SMALL_RUNTIME" ]]; then
echo "ERROR: llama.cpp runtime absent at $LLM_SMALL_RUNTIME" >&2
echo "frank-small: build it (cmake -B build-cuda -DGGML_CUDA=ON" >&2
echo "frank-small: -DCMAKE_CUDA_ARCHITECTURES=86 -DCMAKE_CUDA_HOST_COMPILER=/usr/bin/gcc-13" >&2
echo "frank-small: && cmake --build build-cuda --target llama-server) first." >&2
return 1
fi
for f in "$LLM_SMALL_MODEL_FILE" "$LLM_SMALL_MMPROJ"; do
if [[ ! -f "$f" ]]; then
echo "ERROR: frank-small payload file absent at $f" >&2
echo "frank-small: run scripts/download-frank-small.sh first;" >&2
echo "frank-small: refusing to start a unit that cannot load." >&2
return 1
fi
done
relink_unit frank-small
run_privileged systemctl daemon-reload
run_privileged systemctl enable frank-small.service
run_privileged systemctl restart frank-small.service
wait_for_health frank-small http://127.0.0.1:7771/health 900
wait_for_health frank-small http://127.0.0.1:7771/health 900 || return 1
# False-green hardening (frank-large's lesson): the port answering
# proves nothing about WHO answers — the unit must be active with a
# live MainPID, or a stray SGLang holdover is masquerading as deployed.
local main_pid
main_pid="$(run_privileged systemctl show -p MainPID --value frank-small.service)"
if [[ -z "$main_pid" || "$main_pid" == "0" ]]; then
echo "FAIL: :7771 answered but frank-small.service has no MainPID — a stray process holds the port" >&2
return 1
fi
echo "frank-small: health answered by unit MainPID $main_pid"
}
# deploy_llm_primary — frank-primary is the tcclaviger RDNA4 vLLM fork
+91
View File
@@ -0,0 +1,91 @@
#!/usr/bin/env bash
# Download kingjones777/Qwen3.8-27B-ROCmFP4-STRIX-MTP-GGUF for frank-large
# (Dankclaw iGPU). Public repo — no auth header, and never a token on the
# command line (it is world-readable in /proc/<pid>/cmdline).
#
# The payload is the repo's highest-quality target plus its MTP draft head and
# vision projector:
# * Qwen3.8-27B-Q8_0_ROCMFPX_AGENT.gguf — ftype 115, 187 tensors at plain
# Q8_0 and 311 at GGML_TYPE_Q8_0_ROCMFPX (103). The AGENT routing keeps the
# output-head tensors at full Q8_0 (187 vs 2 in the non-AGENT build), which
# is the variant to take when serving with the MTP head.
# * mtp-Qwen3.8-27B-Q4_0.gguf — the draft head. Q4_0, NOT Q8_0: the head's
# per-step cost is its projection over a 248K vocabulary, so the cheaper
# head is faster end to end at equal acceptance (author: +6.0% at n-max 1,
# +10.2% at n-max 2).
# * mmproj-Qwen3.8-27B-BF16.gguf — the vision tower (verified 4/4 on spatial
# ground truth with -fa on).
#
# Fresh downloads, no resume (`curl -C -` once produced an oversized file on a
# 31 GiB payload); -f/--fail-with-body so an HTTP 401 is not a success, then
# byte count and the Hub LFS sha256. Idempotent: complete files are skipped.
#
# The repo's own SHA256SUMS covers only the ROCmFP4 files, so the hashes below
# come from the Hub LFS oids (api/models/<repo>/tree/main).
#
# Usage:
# scripts/download-frank-large-kingjones.sh [DEST_DIR] [--verify-only]
set -euo pipefail
REPO="kingjones777/Qwen3.8-27B-ROCmFP4-STRIX-MTP-GGUF"
BASE="https://huggingface.co/${REPO}/resolve/main"
DEST=""
VERIFY_ONLY=0
for arg in "$@"; do
case "$arg" in
--verify-only) VERIFY_ONLY=1 ;;
*) DEST="$arg" ;;
esac
done
DEST="${DEST:-/home/dank/models/kingjones-Qwen3.8-27B-ROCmFP4-STRIX-MTP}"
# name bytes sha256
FILES=(
"Qwen3.8-27B-Q8_0_ROCMFPX_AGENT.gguf 28214425952 f3ef2bdbf56e244fff14b72114dc2aa300b84a4cb4eaf54f2e5e4da1cfcae10b"
"mtp-Qwen3.8-27B-Q4_0.gguf 1680271648 051a1764cff8c4f3ee6ae8b00593a0364c7539c67fa50ffc58f3f96509fca38e"
"mmproj-Qwen3.8-27B-BF16.gguf 931145888 de2a49866988ea272c43dc2a43ee2662c25725a717ca5b9059ea420a97f53fe8"
)
mkdir -p "$DEST"
status=0
for entry in "${FILES[@]}"; do
read -r name size sha <<<"$entry"
f="$DEST/$name"
have=0
if [[ -f "$f" ]] && [[ "$(stat -c%s "$f")" == "$size" ]]; then
if sha256sum -c --quiet <(printf '%s %s\n' "$sha" "$f"); then
have=1
fi
fi
if (( have )); then
echo "OK $name"
continue
fi
if (( VERIFY_ONLY )); then
echo "MISSING $name"
status=1
continue
fi
echo "FETCHING $name"
tmp="$f.part"
curl -fsSL --fail-with-body -o "$tmp" "$BASE/$name"
mv "$tmp" "$f"
if [[ "$(stat -c%s "$f")" != "$size" ]]; then
echo "SIZE FAIL $name ($(stat -c%s "$f") != $size)"
status=1
continue
fi
if ! sha256sum -c --quiet <(printf '%s %s\n' "$sha" "$f"); then
echo "SHA FAIL $name"
status=1
continue
fi
echo "VERIFIED $name"
done
if (( status == 0 )); then
echo "DOWNLOAD_DONE $DEST"
else
echo "DOWNLOAD_FAILED $DEST" >&2
fi
exit "$status"
+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: $MODEL_DIR"
+83
View File
@@ -0,0 +1,83 @@
#!/usr/bin/env bash
# Download the frank-small payload for llama.cpp on the RTX 3090:
# bartowski/MiMo-V2.6-Distill-Qwen-9B-GGUF:Q5_K_M plus its vision projector
# (the GGUF carries no `v.*` tensors — the tower lives only in the mmproj, so
# without this file the endpoint is text-only by construction). Public repo —
# no auth header, and never a token on the command line (it is world-readable
# in /proc/<pid>/cmdline).
#
# Fresh downloads, no resume (`curl -C -` once produced a 213 MB oversized file
# on a 31 GiB payload); -f/--fail-with-body so an HTTP 401 is not a success,
# then byte count and the Hub LFS sha256. Idempotent: complete files are
# skipped.
#
# The Q6_K file this endpoint served until 2026-10-01 night stays on disk as
# the rollback target (7793710624 B, LFS oid
# ef96d05a2ddf2cbb450d1af1ac3860ec769d3575bafa70692ee5609bda3fad7d) — re-fetch
# it from the same repo with the same recipe if it is ever needed again.
#
# Usage:
# scripts/download-frank-small.sh [DEST_DIR] [--verify-only]
set -euo pipefail
REPO="bartowski/MiMo-V2.6-Distill-Qwen-9B-GGUF"
BASE="https://huggingface.co/${REPO}/resolve/main"
DEST=""
VERIFY_ONLY=0
for arg in "$@"; do
case "$arg" in
--verify-only) VERIFY_ONLY=1 ;;
*) DEST="$arg" ;;
esac
done
DEST="${DEST:-/home/dank/models/MiMo-Q5KM}"
# name bytes sha256
FILES=(
"MiMo-V2.6-Distill-Qwen-9B-Q5_K_M.gguf 6876124704 04cf46f2b5584ef922697d6c063f94879434fb86c467f1a09e52daf0cddaf35f"
"mmproj-MiMo-V2.6-Distill-Qwen-9B-f16.gguf 918166048 ff348f3180a63188aa7285db85f550fe38acb61dd013c599eb8bad08d2cc2576"
)
mkdir -p "$DEST"
status=0
for entry in "${FILES[@]}"; do
read -r name size sha <<<"$entry"
f="$DEST/$name"
have=0
if [[ -f "$f" ]] && [[ "$(stat -c%s "$f")" == "$size" ]]; then
if sha256sum -c --quiet <(printf '%s %s\n' "$sha" "$f"); then
have=1
fi
fi
if (( have )); then
echo "OK $name"
continue
fi
if (( VERIFY_ONLY )); then
echo "MISSING $name"
status=1
continue
fi
echo "FETCHING $name"
tmp="$f.part"
curl -fsSL --fail-with-body -o "$tmp" "$BASE/$name"
mv "$tmp" "$f"
if [[ "$(stat -c%s "$f")" != "$size" ]]; then
echo "SIZE FAIL $name ($(stat -c%s "$f") != $size)"
status=1
continue
fi
if ! sha256sum -c --quiet <(printf '%s %s\n' "$sha" "$f"); then
echo "SHA FAIL $name"
status=1
continue
fi
echo "VERIFIED $name"
done
if (( status == 0 )); then
echo "DOWNLOAD_DONE $DEST"
else
echo "DOWNLOAD_FAILED $DEST" >&2
fi
exit "$status"
+78 -38
View File
@@ -1,45 +1,85 @@
# frank-large — gufo (gufo-org/gufo) serving
# Swift-1.5-Qwen3.8-27B-Uncensored (abliterated) on the Strix Halo iGPU.
# frank-large — ROCmFPX llama.cpp serving
# kingjones777/Qwen3.8-27B-ROCmFP4-STRIX-MTP-GGUF (Q8_0_ROCMFPX_AGENT, ftype
# 115) + its Q4_0 MTP draft head, on the Strix Halo iGPU (gfx1151), :7770.
#
# These are the tunables read by scripts/serve-frank-large.sh. The flag
# list is owned by the serve script; this file only sets fleet values.
# 2026-10-02 (Frank): "the highest quality of that repo, one full context,
# whatever runtime it requires". The highest-quality rung is Q8_0_ROCMFPX_AGENT
# (26.28 GiB, 8.39 bpw: 187 tensors at plain Q8_0 + 311 at
# GGML_TYPE_Q8_0_ROCMFPX); the AGENT routing is also the variant the card
# tells you to take with MTP, because it keeps the output-head tensors at full
# Q8_0 (187 vs 2), which is what the draft scores against. The runtime the
# format REQUIRES is the ROCmFPX fork — type 103 exists nowhere else.
#
# DO NOT name a new tunable TEMP, HOST or GPU_MAX_HEAP_SIZE: the HIP
# 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 shape: one session at the model's full native window (262,144), which is
# the whole point — the Q8_0 head costs quality the fleet wanted back, and
# the draft head pays for the bandwidth the bigger file spends.
#
# Budget (from the GGUF header, not from a boot log): attention KV lives only
# in the 16 full-attention layers (4 KV heads x 256 head_dim), 64 KiB/token
# with f16 K and V => 16.0 GiB at 262,144. The 48 Gated DeltaNet layers hold
# ~144 MiB of fixed state per sequence. Weights 26.28 + draft head 1.57 +
# mmproj 0.87 + KV 16.0 + state 0.14 + compute buffers ≈ 45-47 GiB against the
# iGPU's ~114 GiB GTT aperture, so f16 KV (the unquantized choice) is affordable
# here in a way it is not on frank-small's 24 GiB card.
# 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 qualified ROCmFPX fork build (scripts/build-rocmfpx.sh pins the commit).
LLAMA_BIN=/home/dank/GitPackages/kingjones-ROCmFPX/build/bin/llama-server
# One directory per HF repo, created by scripts/download-frank-large-kingjones.sh.
MODEL_FILE=/home/dank/models/kingjones-Qwen3.8-27B-ROCmFP4-STRIX-MTP/Qwen3.8-27B-Q8_0_ROCMFPX_AGENT.gguf
# The draft head: Q4_0, NOT the Q8_0 head. The head's per-step cost is its
# projection over a 248K vocabulary, so the cheaper head is faster end to end
# at equal-or-better acceptance (card: +6.0% at n-max 1, +10.2% at n-max 2).
DRAFT_FILE=/home/dank/models/kingjones-Qwen3.8-27B-ROCmFP4-STRIX-MTP/mtp-Qwen3.8-27B-Q4_0.gguf
# Vision tower, separate from the LLM file. Empty string = text-only.
MMPROJ_FILE=/home/dank/models/kingjones-Qwen3.8-27B-ROCmFP4-STRIX-MTP/mmproj-Qwen3.8-27B-BF16.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
# window of 2048, which is what keeps its KV small (~40 MiB).
DRAFTER_DIR=/home/dank/models/Qwen3.8-27B-UD-Q8_K_XL
DRAFTER_FILE=/home/dank/models/Qwen3.8-27B-UD-Q8_K_XL/Qwen3.8-27B-DFlash2-Q4_K_M.gguf
# The gufo runtime, built from source by scripts/build-gufo.sh.
RUNTIME_DIR=/home/dank/GitPackages/gufo-v0.1.1
# Fleet endpoint: the same port and alias every frank-large has served, so
# no client, probe or models.yml entry changes address.
# Fleet endpoint: same port and alias as every frank-large before it, so the
# harness models.yml id and the homepage probe do not move.
ALIAS=frank-large
HOST=0.0.0.0
PORT=7770
# HIP reads a bare HOST, so this is BIND_ADDR — the same reason the file
# avoids a bare TEMP.
BIND_ADDR=0.0.0.0
LISTEN_PORT=7770
# One session, full 262144 context (the model's native window).
CONTEXT_SIZE=262144
SESSIONS=1
# One full native window. llama.cpp divides --ctx-size across --parallel
# slots, so 262144/1 IS the model's trained window; the card validated 65,536
# and the fleet has been running this family at 262,144 since the gufo era.
CTX_SIZE=262144
PARALLEL=1
# DFlash2 spec decode (a block-diffusion drafter). gufo sizes the draft
# block itself; DRAFT_TOKENS caps the proposals per step (gufo's default is
# 7, chosen over llama.cpp's fixed depth 4 because gufo's adaptive policy
# shortens the block when acceptance drops) and DRAFT_POLICY is the block
# length controller.
DRAFT_TOKENS=7
DRAFT_POLICY=adaptive
# Deck knobs. --ubatch-size has a measured optimum on this stack (512 peak on
# the sibling qwen35 model; larger ubatch costs GiBs of compute buffer for no
# speed), and --fit must stay off: --fit's auto placement does not know that
# 311 tensors of type 103 belong on the iGPU.
BATCH_SIZE=2048
UBATCH_SIZE=512
NGL=999
FIT=off
FLASH_ATTN=on
# Unquantized KV — the quality-first choice, affordable at one slot.
CACHE_TYPE_K=f16
CACHE_TYPE_V=f16
# Speculative decode: the model ships a standalone MTP head (mtp-Q4_0.gguf,
# arch qwen35, nextn_predict_layers=1, a 65-block draft). n-max 4 with n-min 0
# and p-min 0.0 is the card's measured optimum (+31% end to end, acceptance
# 0.926; its own n-max 8 measurement only reached 0.757 acceptance and LOST).
# The draft runs entirely on the iGPU, so cross-device traffic stays off the
# bandwidth-limited link.
SPEC_TYPE=draft-mtp
SPEC_DRAFT_NGL=99
SPEC_DRAFT_DEVICE=ROCm0
SPEC_DRAFT_N_MAX=4
SPEC_DRAFT_N_MIN=0
SPEC_DRAFT_P_MIN=0.0
# The card's thinking sampling profile, which is also what the harness sends
# in extraBody, so the endpoint behaves the same to a client that omits it.
TEMPERATURE=1.0
TOP_P=0.95
TOP_K=20
MIN_P=0.0
PRESENCE_PENALTY=0.0
NUM_THREADS=16
THREAD_BATCH=16
+4 -2
View File
@@ -1,5 +1,5 @@
[Unit]
Description=gufo (gufo-org/gufo, ROCm gfx1151) Qwen3.8-27B UD-Q8_K_XL, DFlash2 spec decode, 262144 ctx / 1 session, root systemd unit (dankclaw, frank-large, Strix Halo iGPU)
Description=ROCmFPX llama.cpp (gfx1151) kingjones777 Qwen3.8-27B Q8_0_ROCMFPX_AGENT, MTP spec decode, 262144 ctx / 1 session, root systemd unit (dankclaw, frank-large, Strix Halo iGPU)
After=network-online.target
Wants=network-online.target
@@ -13,7 +13,9 @@ Group=dank
LimitMEMLOCK=infinity
Environment="FRANK_LARGE_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-large.env"
ExecStart=/home/dank/serverAppConfigs/scripts/serve-frank-large.sh
Restart=on-failure
# always, not on-failure: an engine that drains and exits 0 after a worker
# fault would otherwise leave the endpoint down until someone notices.
Restart=always
RestartSec=10
[Install]
+97 -29
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 +59,71 @@ 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
FRANK_PRIMARY_SEQS=3
FRANK_PRIMARY_KV_BYTES=7730934784
# --- qualified engine shape (2026-10-02, Frank's own correction) ---
# 2026-10-01 left a shape that did not stay up: bf16 KV at 2 x 262144 with
# --expert-precise-memory crash-looped at graph capture (the arena is
# DEVICE-resident and the shape had 0.13 GiB to spare), and the plain bf16
# 2 x 262144 boot booted but left 0 bytes free at runtime. This is the
# correction: FP8 KV, TWO windows, each 200704 tokens, and the pool cut so
# the expert arena gets the room back.
#
# LADDER (2026-10-01 night, subtract-16k method): 262144 and 245760 OOM at
# graph capture; 237568 passed at 718,606 tokens; 241664 x 3 passed at
# 732,359 tokens / 3.03x but is the shape this cutover retired. 200704 was
# chosen to sit below the 241664 rung while leaving a full 2.95 GiB/rank of
# pool to cut loose for the arena — the two contexts are a capacity
# contract, not a throughput one (2-way concurrency summed BELOW parity at
# 4064 ctx), so the slot buys the VRAM headroom long generations need.
#
# KV_BYTES is PER RANK. fp8 costs 7,701 B/token (measured 6,138 attention
# + 1,563 mamba/side, dtype-independent). 2 x 200704 = 401,408 tokens
# -> 3.091e9 B floor, pinned at 3.15e9 (~405,000 tokens, ~44 MB margin —
# the same margin convention the 6.1e9 shape used).
#
# THE ARENA IS WHAT REMAINS: the fork's expert planner sizes it AFTER the
# KV override, so every byte cut here is arena. The 6.1e9 shape ran an
# arena of 6,248 slots; this one reclaims ~2.95 GiB/rank, roughly 1,260
# more slots at 2.344 MiB each. That is the point of the change — the
# gather read path is the measured decode bound, and a bigger arena means
# more experts resident instead of streamed.
#
# MNBT 1024 (down from 2048): 1024-4096 are interchangeable on decode AND
# identical on arena (the sweep measured the same slot count at every
# rung <= 4096), so this is a pure workspace-floor choice, not a decode
# trade. The floor matters because the arena budget is what is left.
#
# PRECISE MEMORY stays DROPPED: it crashed the 2 x 262144 bf16 boot
# (weights 6.28 + pool 6.80 + graphs 0.55 + arena 16.65 + non-torch ~1.45
# = 31.73 of 31.86 GiB, ~0.13 GiB free, NRestarts=3). The flag survives in
# the serve script as an opt-in; re-enable it only with a pool/context
# reduction that actually pays for the extra overhead.
#
# TUNABLEOP stays OFF (silently skipped under offload unless
# CLAV_TUNABLEOP_WITH_OFFLOAD=1, and then corrupts numerics).
#
# SEQS 2 x MAXLEN 200704 at FP8 KV, pool cut for the arena. No
# speculative decode, no prefetch.
FRANK_PRIMARY_MAXLEN=200704
FRANK_PRIMARY_SEQS=2
FRANK_PRIMARY_KV_BYTES=3150000000
FRANK_PRIMARY_KV_DTYPE=fp8
FRANK_PRIMARY_SPEC=4
FRANK_PRIMARY_MNBT=1024
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
+49 -107
View File
@@ -1,118 +1,60 @@
# 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.
# frank-small — llama.cpp (master, CUDA sm_86) serving
# bartowski/MiMo-V2.6-Distill-Qwen-9B-GGUF:Q5_K_M on the RTX 3090, :7771.
#
# 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).
# 2026-10-02 (Frank): THREE contexts, vision on, and a hard instruction to
# leave 2-3 GiB of the card free. Both new demands cost memory, so the per-slot
# window shrinks — see the budget below.
#
# 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.
# Two measurements on this card, this runtime, price the terms:
# 2 x 262,144, no projector: 20,190 MiB used / 4,386 free
# KV = 524,288 tok x 24.5 KiB = 12,800 MiB => non-KV (weights 6,557 +
# DeltaNet state ~25/slot + compute buffers + CUDA graphs) = 7,390 MiB
# 3 x 196,608, projector on: 22,972 MiB used / 1,153 free
# KV = 14,113 MiB => non-KV WITH the vision tower = 8,859 MiB
# The tower costs ~1.4 GiB, not the ~1.0 its file size suggested, so 196,608
# per slot left only 1.1 GiB free — outside the band. The pool therefore is
# 3 x 180,224 = 540,672 tokens: KV ~12,936 + non-KV 8,859 = ~21,800 MiB predicted.
# MEASURED at this shape: 21,684 MiB used / 2,441 MiB free — inside the band, and
# the number the bats budget gate reproduces (it prices non-KV at 9 GiB).
#
# 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.
# KV arithmetic: attention KV exists only in the 8 full-attention layers
# (4 KV heads x 256 head_dim). K f16 = 16 KiB/token, V q8_0 = 8.5 KiB/token
# (34 B per 32-element block) => 24.5 KiB/token, so 12,288 tokens (=4096/slot)
# is one 293 MiB step — that is the ladder to walk if this moves again. The
# native 262,144 per slot is NOT reachable three times: 3 x 262,144 x
# 24.5 KiB = 18.4 GiB of KV before anything else is loaded.
#
# 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).
#
# Sampling: greedy by default (the fleet contract); a client that sends a
# temperature gets its own, and the harness applies per-model overrides
# from models.yml.
#
# WARNING: do not name any variable TEMP, HOST, or GPU_MAX_HEAP_SIZE (HIP
# 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.
# Why V stays q8_0 and K stays f16: full-precision V would add 8 KiB/token —
# +4.5 GiB on this pool — which is what pushes the card past its 24 GiB. K is
# the tensor the asymmetric-KV contract exists to protect.
LLAMA_BIN=/home/dank/GitPackages/llama-master/build-cuda/bin/llama-server
MODEL_FILE=/home/dank/models/MiMo-Q5KM/MiMo-V2.6-Distill-Qwen-9B-Q5_K_M.gguf
# 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
# Vision: the Q5_K_M GGUF ships no `v.*` tensors, so the projector file IS the
# vision capability (sha256 ff348f31..., 918,166,048 B, fetched by
# scripts/download-frank-small.sh). Empty string = text-only on purpose.
MMPROJ_FILE=/home/dank/models/MiMo-Q5KM/mmproj-MiMo-V2.6-Distill-Qwen-9B-f16.gguf
# 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
# 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.
# Fleet endpoint: same port and alias as every frank-small before it, so the
# harness models.yml id and the homepage probe do not move.
ALIAS=frank-small
BIND_ADDR=0.0.0.0
LISTEN_PORT=7771
# 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
# Three independent conversations. llama.cpp divides --ctx-size across
# --parallel slots (n_ctx_slot = CTX_SIZE/PARALLEL), and a mamba-hybrid model
# cannot use unified KV, so each slot gets its own cache and its own window.
# 180,224 per slot is BELOW the native 262,144, and that is the cost of the
# third slot: a longer single prompt needs compaction instead of one shot.
# Consequence worth knowing: frank-primary's compaction trigger is 183,501
# tokens, which no longer fits a frank-small slot — see the runbook's
# "three slots vs compaction" note.
CTX_SIZE=540672
PARALLEL=3
# The KV contract (Frank, 2026-10-01 night): unquantized K, q8_0 V.
# q8_0 on V is only served by the flash-attention path; the serve script
# pins --flash-attn on and must never lose it.
CACHE_TYPE_K=f16
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
# 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
NGL=99
+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=llama.cpp MiMo-V2.6-Distill-Qwen-9B Q5_K_M GGUF (qwen35 hybrid, 3x180224, f16 K + q8_0 V, mmproj vision) on the RTX 3090 (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
+163 -105
View File
@@ -1,121 +1,179 @@
#!/usr/bin/env bash
# Serve Swift-1.5-Qwen3.8-27B-Uncensored (abliterated) as frank-large on
# Dankclaw's Strix Halo iGPU (gfx1151), using gufo (gufo-org/gufo) — the
# inference engine built specifically for this hardware.
# Serve kingjones777/Qwen3.8-27B-ROCmFP4-STRIX-MTP-GGUF as frank-large on
# Dankclaw's Strix Halo iGPU (gfx1151) with the ROCmFPX fork of llama.cpp.
#
# Runtime: /home/dank/GitPackages/gufo-v0.1.1/bin/gufo, built from source
# against the host ROCm by scripts/build-gufo.sh. It replaced the stock
# llama.cpp prebuilt (unsloth b11030) on 2026-09-28; port, alias and client
# contract did not move.
# 2026-10-02 (Frank): swapped from gufo + Q4_K_XL to the highest-quality file
# in the repo, one session at the native 262,144 window.
#
# Payload: ajgazin/Swift-1.5-Qwen3.8-27B-Uncensored-Dynamic-MTP-GGUF's
# UD-Q8_K_XL, fetched by scripts/download-frank-large-swift.sh. It replaced
# unsloth/Qwen3.8-27B-GGUF:UD-Q8_K_XL on 2026-09-28. The two are structurally
# interchangeable for this engine — same `qwen35` architecture, the same 866
# tensors in the same order, the same per-tensor Q8_0/F32/BF16 layout, the
# same MTP head at blk.64 — so the swap needed no engine change. The fine-tune
# is abliterated (uncensored) and carries the SWIFT OPEN LICENSE 1.0, which
# is not an OSI licence.
# Why this runtime and not the previous one: the payload is ftype 115 — 311
# tensors of GGML_TYPE_Q8_0_ROCMFPX (103), a tensor type that exists only in
# the ROCmFPX fork. Stock llama.cpp, SGLang and gufo all refuse the file, and
# gufo additionally gates every "Qwen3.8" artifact on a template-hash
# allowlist. The qualified build is scripts/build-rocmfpx.sh's pin: it loads
# ftype 115, survives warmup (the 2026-08-25 builds of the older fork line
# segfaulted in ggml_compute_forward_set_rows on this exact file), and drafts
# with the model's own MTP head.
#
# 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 +
# 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.
# Why this file: Q8_0_ROCMFPX_AGENT is the top of the repo's quality ladder
# (26.28 GiB, 8.39 bpw) and the AGENT routing keeps 187 tensors — the
# output-head set the draft scores against — at plain Q8_0 instead of the 2
# the non-AGENT build keeps, which is the variant the card names for MTP
# serving. Drafting uses the repo's Q4_0 MTP head: the head's cost is its
# projection over the 248K vocabulary, so the 4-bit head is faster end to end
# at equal-or-better acceptance than its Q8_0 sibling.
#
# Spec method: DFlash2 (a block-diffusion drafter), gufo's adaptive block
# policy, capped at DRAFT_TOKENS proposals per step. The drafter is the
# z-lab Qwen3.8-27B-DFlash2-Q4_K_M and it has a sliding window of 2048
# (small draft KV). It is UNCHANGED by the model swap and still lives beside
# the previous target, which is why DRAFTER_DIR is its own tunable.
#
# Sampling: greedy (--temperature 0) server-side, as every frank-large has
# served. The harness overrides it per request via extraBody (1.0 / 0.95 /
# top-k 20).
#
# Template: gufo compiles the official Qwen Jinja into the binary and takes
# NO --chat-template-file — and it is not a Jinja engine at all
# (src/models/qwen/chat_template.cpp is a hand-written C++ renderer), so the
# fleet's scripts/qwen-sharp-v22.4.0.jinja cannot be supplied to it. That law
# was given up when this endpoint moved to gufo on 2026-09-28, by decision:
# the terse system-prompt injection, the in-band <|think_*|> control, the
# json|xml tool_call_format switch and the tool-argument truncation are all
# absent. gufo's own renderer keeps the effort instruction strings and
# preserve_thinking, which are the parts the harness depends on. Accepted
# 2026-09-28; recovering the terse prompt from the client side is the
# cheapest partial restore.
#
# Text-only: gufo auto-discovers a mmproj beside the model and this payload
# has none (the base repo ships one separately, unused), so the endpoint
# stays text-only.
#
# Tunables come from frank-large.env unless FRANK_LARGE_ENV_FILE overrides
# it; anything not set there falls through to the defaults below.
# The client contract lives here, not in frank-large.env:
# * --jinja — without it llama.cpp silently IGNORES the harness's
# chat_template_kwargs (enable_thinking / preserve_thinking), so the
# endpoint would look like it had no thinking control at all. The GGUF
# carries the official Qwen template, so no --chat-template-file.
# * --reasoning-format deepseek — thinking is emitted as reasoning_content,
# the field the harness reads for this endpoint.
# * the template accepts reasoning_effort xhigh|medium|low only, which is
# why models.yml folds the harness's levels onto that set.
# * --alias frank-large — that is the model id the harness resolves.
# * --ctx-checkpoints / --cache-ram — prompt-cache geometry for the 16
# sliding-window-style layers; harmless where the hybrid state forces a
# full re-process, and required for the checkpoint feature to work at all.
set -euo pipefail
SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)"
ENV_FILE="${FRANK_LARGE_ENV_FILE:-$SCRIPT_DIR/frank-large.env}"
# Fleet values live in frank-large.env. Anything already in the environment
# wins over the file, so an operator can override one value on a single run:
# the caller's values are captured, the file is sourced, then they are put
# back. (A plain `source` would let the file clobber the environment.)
TUNABLES=(LLAMA_BIN MODEL_FILE DRAFT_FILE MMPROJ_FILE ALIAS BIND_ADDR
LISTEN_PORT CTX_SIZE PARALLEL BATCH_SIZE UBATCH_SIZE NGL FIT
FLASH_ATTN CACHE_TYPE_K CACHE_TYPE_V SPEC_TYPE SPEC_DRAFT_NGL
SPEC_DRAFT_DEVICE SPEC_DRAFT_N_MAX SPEC_DRAFT_N_MIN SPEC_DRAFT_P_MIN
TEMPERATURE TOP_P TOP_K MIN_P PRESENCE_PENALTY NUM_THREADS
THREAD_BATCH ROCM_PATH HIP_VISIBLE HSA_GFX_VERSION)
_OVERRIDES=()
for _var in "${TUNABLES[@]}"; do
[[ -n "${!_var+set}" ]] && _OVERRIDES+=("$_var=${!_var}")
done
ENV_FILE="${FRANK_LARGE_ENV_FILE:-$(dirname "$0")/frank-large.env}"
if [[ -f "$ENV_FILE" ]]; then
set -a
# shellcheck disable=SC1090
source "$ENV_FILE"
set +a
fi
# --- defaults (used when the env file does not set them) ------------------
: "${RUNTIME_DIR:=/home/dank/GitPackages/gufo-v0.1.1}"
: "${MODEL_DIR:=/home/dank/models/Swift-1.5-Qwen3.8-27B-Uncensored-MTP-UD-Q8_K_XL}"
: "${ALIAS:=frank-large}"
: "${HOST:=0.0.0.0}"
: "${PORT:=7770}"
: "${CONTEXT_SIZE:=262144}"
: "${SESSIONS:=1}"
: "${DRAFT_TOKENS:=7}"
: "${DRAFT_POLICY:=adaptive}"
GUFO_BIN="$RUNTIME_DIR/bin/gufo"
# The target GGUF and the drafter are named explicitly because they do not
# share a directory any more: the target is a different repository's artifact
# and keeps its own long filename, while the DFlash2 drafter is unchanged and
# still lives beside the previous target. MODEL_FILE/DRAFTER_FILE default to
# the deployed payload, so the env file only has to state them when it moves.
: "${MODEL_FILE:=$MODEL_DIR/Swift-1.5-Qwen3.8-27B-Uncensored-Dynamic-MTP-UD-Q8_K_XL.gguf}"
: "${DRAFTER_DIR:=/home/dank/models/Qwen3.8-27B-UD-Q8_K_XL}"
: "${DRAFTER_FILE:=$DRAFTER_DIR/Qwen3.8-27B-DFlash2-Q4_K_M.gguf}"
if [[ ! -x "$GUFO_BIN" ]]; then
echo "runtime not found at $GUFO_BIN" >&2
echo "frank-large: build it: bash scripts/build-gufo.sh" >&2
exit 1
fi
for f in "$MODEL_FILE" "$DRAFTER_FILE"; do
if [[ ! -f "$f" ]]; then
echo "missing asset $f (run the matching scripts/download-frank-large*.sh)" >&2
exit 1
fi
for _kv in "${_OVERRIDES[@]+${_OVERRIDES[@]}}"; do
export "${_kv?}"
done
unset _var _kv
# --- env -------------------------------------------------------------------
# gufo links against the host ROCm through its RPATH (/opt/rocm ->
# /etc/alternatives/rocm), so no LD_LIBRARY_PATH is needed. The device is
# already gfx1151 — `gufo diagnose` reports it natively — so no
# HSA_OVERRIDE_GFX_VERSION either; the override existed for the prebuilt
# llama.cpp runtime and can only misreport the arch here.
export HIP_VISIBLE_DEVICES=0
: "${LLAMA_BIN=/home/dank/GitPackages/kingjones-ROCmFPX/build/bin/llama-server}"
: "${MODEL_FILE=/home/dank/models/kingjones-Qwen3.8-27B-ROCmFP4-STRIX-MTP/Qwen3.8-27B-Q8_0_ROCMFPX_AGENT.gguf}"
: "${DRAFT_FILE=/home/dank/models/kingjones-Qwen3.8-27B-ROCmFP4-STRIX-MTP/mtp-Qwen3.8-27B-Q4_0.gguf}"
: "${MMPROJ_FILE=/home/dank/models/kingjones-Qwen3.8-27B-ROCmFP4-STRIX-MTP/mmproj-Qwen3.8-27B-BF16.gguf}"
: "${ALIAS=frank-large}"
: "${BIND_ADDR=0.0.0.0}"
: "${LISTEN_PORT=7770}"
: "${CTX_SIZE=262144}"
: "${PARALLEL=1}"
: "${BATCH_SIZE=2048}"
: "${UBATCH_SIZE=512}"
: "${NGL=999}"
: "${FIT=off}"
: "${FLASH_ATTN=on}"
: "${CACHE_TYPE_K=f16}"
: "${CACHE_TYPE_V=f16}"
: "${SPEC_TYPE=draft-mtp}"
: "${SPEC_DRAFT_NGL=99}"
: "${SPEC_DRAFT_DEVICE=ROCm0}"
: "${SPEC_DRAFT_N_MAX=4}"
: "${SPEC_DRAFT_N_MIN=0}"
: "${SPEC_DRAFT_P_MIN=0.0}"
: "${TEMPERATURE=1.0}"
: "${TOP_P=0.95}"
: "${TOP_K=20}"
: "${MIN_P=0.0}"
: "${PRESENCE_PENALTY=0.0}"
: "${NUM_THREADS=16}"
: "${THREAD_BATCH=16}"
: "${ROCM_PATH=/opt/rocm}"
: "${HIP_VISIBLE=0}"
: "${HSA_GFX_VERSION=11.5.1}"
# --- the serve command ---------------------------------------------------
# Server options precede the subcommand, model options follow it.
exec "$GUFO_BIN" serve \
--host "$HOST" \
--port "$PORT" \
--sessions "$SESSIONS" \
llm \
[[ -n "$LLAMA_BIN" ]] || { echo "frank-large: LLAMA_BIN is empty" >&2; exit 1; }
[[ -x "$LLAMA_BIN" ]] || {
echo "frank-large: llama-server '$LLAMA_BIN' is not executable;" >&2
echo " build it with scripts/build-rocmfpx.sh" >&2
exit 1
}
# Refuse anything but the real payload. A path that is not a readable file
# makes llama-server hang rather than fail clean.
[[ -r "$MODEL_FILE" ]] || {
echo "frank-large: model file '$MODEL_FILE' is not readable;" >&2
echo " fetch it with scripts/download-frank-large-kingjones.sh" >&2
exit 1
}
# The MTP head is the performance feature: without it the Q8_0 weights decode
# at memory-bandwidth speed and the endpoint loses the ~1.4x the head buys.
[[ -r "$DRAFT_FILE" ]] || {
echo "frank-large: MTP draft head '$DRAFT_FILE' is not readable;" >&2
echo " fetch it with scripts/download-frank-large-kingjones.sh" >&2
exit 1
}
# The GGUF carries no vision tower; the projector file is the whole tower, so
# a missing file means a vision request would 500 rather than degrade.
# MMPROJ_FILE="" is the documented opt-out for a text-only endpoint.
MM_ARGS=()
if [[ -n "${MMPROJ_FILE:-}" ]]; then
[[ -r "$MMPROJ_FILE" ]] || {
echo "frank-large: mmproj '$MMPROJ_FILE' is not readable; set MMPROJ_FILE='' for text-only" >&2
exit 1
}
MM_ARGS=(--mmproj "$MMPROJ_FILE")
fi
# HIP/ROCm host environment. HIP reads bare env vars (TEMP, HOST,
# GPU_MAX_HEAP_SIZE), which is why the tunables above are named TEMPERATURE
# and BIND_ADDR. HSA_OVERRIDE_GFX_VERSION is what lets a runtime built for a
# neighbouring gfx target run on this iGPU; the qualified pin targets gfx1151
# natively and the override is a no-op for it.
export ROCM_PATH
export HIP_VISIBLE_DEVICES="$HIP_VISIBLE"
export HSA_OVERRIDE_GFX_VERSION="$HSA_GFX_VERSION"
export LD_LIBRARY_PATH="$(dirname "$LLAMA_BIN"):${ROCM_PATH}/lib:${ROCM_PATH}/lib/rocm_sysdeps/lib:${ROCM_PATH}/lib/llvm/lib${LD_LIBRARY_PATH:+:$LD_LIBRARY_PATH}"
exec /usr/bin/env "$LLAMA_BIN" \
--model "$MODEL_FILE" \
--served-model-name "$ALIAS" \
--context "$CONTEXT_SIZE" \
--speculative dflash2 \
--dflash-model "$DRAFTER_FILE" \
--draft-tokens "$DRAFT_TOKENS" \
--draft-policy "$DRAFT_POLICY" \
--temperature 0 \
--think auto \
--preserve-thinking on
"${MM_ARGS[@]}" \
--alias "$ALIAS" \
--host "$BIND_ADDR" \
--port "$LISTEN_PORT" \
--jinja \
--device ROCm0 \
--n-gpu-layers "$NGL" \
--parallel "$PARALLEL" \
--ctx-size "$CTX_SIZE" \
--batch-size "$BATCH_SIZE" \
--ubatch-size "$UBATCH_SIZE" \
--threads "$NUM_THREADS" \
--threads-batch "$THREAD_BATCH" \
--fit "$FIT" \
--flash-attn "$FLASH_ATTN" \
--direct-io \
--cache-type-k "$CACHE_TYPE_K" \
--cache-type-v "$CACHE_TYPE_V" \
--ctx-checkpoints 16 \
--cache-ram 8192 \
--cache-idle-slots \
--temp "$TEMPERATURE" \
--top-p "$TOP_P" \
--top-k "$TOP_K" \
--min-p "$MIN_P" \
--presence-penalty "$PRESENCE_PENALTY" \
--reasoning on \
--reasoning-format deepseek \
--reasoning-budget -1 \
--spec-type "$SPEC_TYPE" \
--model-draft "$DRAFT_FILE" \
--spec-draft-ngl "$SPEC_DRAFT_NGL" \
--spec-draft-device "$SPEC_DRAFT_DEVICE" \
--spec-draft-n-max "$SPEC_DRAFT_N_MAX" \
--spec-draft-n-min "$SPEC_DRAFT_N_MIN" \
--spec-draft-p-min "$SPEC_DRAFT_P_MIN" \
--metrics
+22 -8
View File
@@ -11,12 +11,16 @@
# 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 (2026-10-02, Frank's correction of the 10-01 bf16 shape): MAXLEN
# 200704 x SEQS 2 (401,408 tokens of contract), KV fp8 (--kv-cache-dtype
# fp8; the bf16 unquantized shape is retired to git tag
# frank-primary-fp8-mtp-20261001), KV_BYTES 3,150,000,000 PER RANK (the
# engine measured 405,000 tokens of capacity / ~3.0x 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, and
# the pool deliberately small so the expert arena keeps what it reclaims.
#
# The root unit (scripts/frank-primary.service, User=dank,
# LimitMEMLOCK=infinity) grants the pin budget for the tiered-expert host
@@ -45,7 +49,10 @@ 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 +107,24 @@ 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
+57 -116
View File
@@ -1,39 +1,25 @@
#!/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 bartowski/MiMo-V2.6-Distill-Qwen-9B-GGUF (Q5_K_M) as frank-small on
# Dankclaw's RTX 3090 via llama.cpp (master build, CUDA sm_86).
#
# 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.
# 2026-10-01 night (Frank): swapped from SGLang + INT8-W8A16-AutoRound
# safetensors to the llama.cpp GGUF path, because llama.cpp is the only
# runtime on this host that can serve the MiMo qwen35 hybrid with
# ASYMMETRIC KV: --cache-type-k f16 (unquantized keys) + --cache-type-v
# q8_0 (quantized values), which is Frank's explicit KV contract for this
# endpoint. SGLang's --kv-cache-dtype only moves K and V together.
#
# 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. KV lives only in the 8 attention layers;
# the DeltaNet state is per-slot fixed size. Vision comes from the repo's
# separate projector (the Q5_K_M GGUF carries no `v.*` tensors at all), so
# --mmproj is what gives this endpoint eyes; MMPROJ_FILE="" is the documented
# text-only opt-out.
#
# 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.
# Sampling: llama.cpp takes it per request (the fleet harness sends its
# recipe from models.yml); greedy is the harness default.
#
# 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.
#
# Tunables come from frank-small.env unless FRANK_SMALL_ENV_FILE overrides it.
# Tunables come from frank-small.env unless FRANK_SMALL_ENV_FILE overrides.
set -euo pipefail
SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)"
@@ -46,101 +32,56 @@ 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.
: "${DRAFT_FILE:=}"
: "${LLAMA_BIN:=/home/dank/GitPackages/llama-master/build-cuda/bin/llama-server}"
: "${MODEL_FILE:=/home/dank/models/MiMo-Q5KM/MiMo-V2.6-Distill-Qwen-9B-Q5_K_M.gguf}"
: "${ALIAS:=frank-small}"
: "${BIND_ADDR:=0.0.0.0}"
: "${LISTEN_PORT:=7771}"
: "${CTX_SIZE:=}"
: "${PARALLEL:=1}"
# ctx-size is the POOL llama.cpp divides across slots: 540672 / 3 gives
# 180224 per slot — three independent conversations (the native 262144 no
# longer fits three times on a 24 GiB card once the vision tower is loaded;
# frank-small.env carries the two measurements that set this number).
: "${CTX_SIZE:=540672}"
: "${PARALLEL:=3}"
: "${CACHE_TYPE_K:=f16}"
: "${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}"
: "${REASONING_BUDGET:=-1}"
: "${CACHE_TYPE_V:=q8_0}"
: "${NGL:=99}"
# Vision projector. No colon on purpose: an explicitly empty value means
# "text-only, on purpose" and must NOT be replaced by the default path.
: "${MMPROJ_FILE=/home/dank/models/MiMo-Q5KM/mmproj-MiMo-V2.6-Distill-Qwen-9B-f16.gguf}"
# 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
# Fail loudly rather than half-loading: a missing file is a download that
# has not finished, and Restart=always would turn it into a crash loop that
# reads like a runtime fault.
for path in "$LLAMA_BIN" "$MODEL_FILE"; do
[[ -e "$path" ]] || { echo "frank-small: missing $path" >&2; exit 1; }
done
if [[ -n "${DRAFT_FILE:-}" ]]; then
[[ -e "$MODEL_DIR/$DRAFT_FILE" ]] || { echo "frank-small: missing $MODEL_DIR/$DRAFT_FILE" >&2; exit 1; }
EXTRA_ARGS=()
if [[ -n "$MMPROJ_FILE" ]]; then
[[ -e "$MMPROJ_FILE" ]] || { echo "frank-small: missing $MMPROJ_FILE" >&2; exit 1; }
EXTRA_ARGS+=(--mmproj "$MMPROJ_FILE")
fi
# The UVM device node is created lazily by nvidia-modprobe on the first CUDA
# open after boot; make sure it exists before the server needs it.
nvidia-modprobe -u -c=0 2>/dev/null || true
MMPROJ_ARGS=()
if [[ -n "${MMPROJ_PATH:-}" && -f "$MMPROJ_PATH" ]]; then
MMPROJ_ARGS=(--mmproj "$MMPROJ_PATH")
fi
SPEC_ARGS=()
if [[ -n "${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" \
--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"
# q8_0 on V REQUIRES flash attention (the quantized-value kernels only exist
# on the FA path); an FA-less build silently falls back and the KV contract
# in frank-small.env becomes a lie, so pin the flag pair here.
ARGS=(
--model "$MODEL_FILE"
--alias "$ALIAS"
--host "$BIND_ADDR"
--port "$LISTEN_PORT"
--ctx-size "$CTX_SIZE"
--parallel "$PARALLEL"
--n-gpu-layers "$NGL"
--flash-attn on
--cache-type-k "$CACHE_TYPE_K"
--cache-type-v "$CACHE_TYPE_V"
--jinja
--reasoning auto
--reasoning-format deepseek
)
exec "$LLAMA_BIN" "${ARGS[@]}" ${EXTRA_ARGS[@]+"${EXTRA_ARGS[@]}"}
@@ -244,13 +244,155 @@ 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 (2026-10-02: 2 x 200704, fp8, pool cut for the arena)
```
FRANK_PRIMARY_MAXLEN=200704 x SEQS 2 (401,408 tokens of contract)
FRANK_PRIMARY_KV_BYTES=3150000000 PER RANK (fp8, 7,701 B/token)
FRANK_PRIMARY_KV_DTYPE=fp8 --kv-cache-dtype fp8 (quantized)
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
```
This replaced the 2026-10-01 shape — 2 x 262144 at bf16 KV with
`--expert-precise-memory` — which crash-looped at graph capture: the arena is
DEVICE-resident, the precise-memory flag drops the plan's overhead 7.60 ->
5.25 GiB, and that shape had 0.13 GiB to spare (weights 6.28 + pool 6.80 +
graphs 0.55 + arena 16.65 + non-torch ~1.45 = 31.73 of 31.86 GiB,
NRestarts=3 at ~6.7 min each). The plain bf16 2 x 262144 boot also did not
stay up: it left 0 bytes free at runtime and a real client request (995-token
prompt, max_tokens=261149) killed the worker with `Tried to allocate 50.00 MiB
... 0 bytes free`.
The correction is a pool cut, not a downgrade. fp8 costs 7,701 B/token
(measured 6,138 attention + 1,563 mamba/side, dtype-independent), so 2 x
200704 = 401,408 tokens needs 3.091e9 B; pinned at 3.15e9, ~44 MB of margin
above the floor — the same convention the 6.1e9 shape used. The arena is what
remains: the planner sizes it AFTER the KV override, so the 6,248 slots of the
6.1e9 shape become roughly 7,500 here. Two contexts at 200704 are a capacity
contract, not a throughput one (2-way concurrency summed BELOW parity at 4064
ctx), so the slot buys the VRAM headroom long generations need.
Boot-probed 2026-10-02 (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 x 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 x 245760, bf16 | **OOM identically** |
| 3 x 237568, bf16 | PASS — KV 718,606 tokens |
| 2 x 262144, bf16 + `--expert-precise-memory` | **DEPLOYED then crashed** — 0.13 GiB free at boot, NRestarts=3 |
| 2 x 262144, bf16 (no precise flag) | did not stay up either: 0 bytes free at runtime, worker killed by a real request |
| **2 x 200704, fp8, pool cut for the arena** | **DEPLOYED (2026-10-02, Frank's correction)**: fp8 KV, two 200704 windows, ~7,500 arena slots, ~3.6 GiB free VRAM measured |
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
@@ -1,7 +1,7 @@
---
type: reference
title: "gufo, Swift-1.5-Qwen3.8-27B-Uncensored UD-Q8_K_XL (DFlash2) on Dankclaw (frank-large)"
description: "The active frank-large runbook — gufo (gufo-org/gufo) v0.1.1, the Strix Halo inference engine, built from source on Dankclaw and serving the abliterated ajgazin/Swift-1.5-Qwen3.8-27B-Uncensored UD-Q8_K_XL with the z-lab DFlash2 Q4_K_M drafter on the gfx1151 iGPU: the from-source build and its two host workarounds, the GGUF header evidence that made the payload swap safe, the one-session / full-window shape, why the fleet's Qwen-Sharp chat template CANNOT be used on this runtime and what that costs, the client-contract delta, the measured prefill/decode trade, and the failure modes worth knowing."
title: "gufo, Qwen3.8-27B UD-Q4_K_XL (DFlash2) on Dankclaw (frank-large)"
description: "The RETIRED frank-large runbook (rollback target) — gufo (gufo-org/gufo) v0.1.1, the Strix Halo inference engine, built from source on Dankclaw and serving unsloth/Qwen3.8-27B-GGUF UD-Q4_K_XL (vanilla) with the z-lab DFlash2 Q4_K_M drafter on the gfx1151 iGPU, ONE session at the full native 262,144 window with unquantized f16 KV: the from-source build and its two host workarounds, the GGUF header evidence, why the fleet's Qwen-Sharp chat template CANNOT be used on this runtime, the client-contract delta, the measured prefill/decode trade, and the failure modes worth knowing."
tags:
- llm
- gufo
@@ -16,9 +16,20 @@ tags:
timestamp: 2026-09-28
---
# frank-large — gufo, Swift-1.5-Qwen3.8-27B-Uncensored UD-Q8_K_XL (DFlash2)
# frank-large — gufo, Qwen3.8-27B (UD-Q4_K_XL, DFlash2)
> **ACTIVE since 2026-09-28.** Replaces
> **RETIRED 2026-10-02 — the rollback target.** Superseded by
> [[frank-large-rocmfpx-q8agent-mtp]] (Q8_0_ROCMFPX_AGENT at 8.39 bpw with
> MTP4, 17.0 t/s measured). This era was itself a return after one day of
> [[frank-large-vllm-mimo-v26-bf16]] (battery decode 6.19-9.01 t/s; every
> ≥6-bit vLLM quant path dead on gfx1151). The shape
> moved on the way back: payload is now **unsloth/Qwen3.8-27B-GGUF
> UD-Q4_K_XL** (16.35 GiB, vanilla — the abliterated Swift Q8 was
> reclaimed), and the session grid is **one session at the full native
> 262,144 window** (`SESSIONS=1 CONTEXT_SIZE=262144`, f16 KV). The
> Swift-1.5 Q8 history below is retained for the engine/template law,
> which still governs.
> **Originally ACTIVE 2026-09-28.** Replaces
> [[frank-large-unsloth-qwen38-27b-q8xl]] (stock llama.cpp, the unsloth
> b11030 prebuilt), which had replaced
> [[frank-large-kairic-edge-qwen38-27b]]. Same host, same port (7770), same
@@ -0,0 +1,219 @@
---
type: reference
title: "frank-large on Dankclaw — ROCmFPX llama.cpp, Qwen3.8-27B Q8_0_ROCMFPX_AGENT + MTP"
description: "The active frank-large runbook — the kingjones30/ROCmFPX llama.cpp fork (pinned commit, gfx1151) serving kingjones777's Q8_0_ROCMFPX_AGENT GGUF, a ftype-115 file no other loader can read, with the repo's own MTP-Q4_0 head drafting four tokens at one native 262,144 window, f16 KV, and the bundled BF16 projector for vision. Measured MTP-vs-none A/B, the client contract, and rollback to gufo."
tags:
- llm
- frank-large
- dankclaw
- llama-cpp
- rocmfpx
- gfx1151
- gguf
- spec-decode
- mtp
timestamp: 2026-10-02
---
# frank-large — ROCmFPX Q8_0_ROCMFPX_AGENT + MTP (gfx1151)
> **ACTIVE since 2026-10-02.** Cut over from
> [[frank-large-gufo-qwen38-27b]] (Q4_K_XL, ~15 t/s). Both requests came from
> Frank: *highest quality that runs*, and *one full context*. This endpoint
> delivers 8.39 bpw weights — two quant rungs above what gufo could load — and
> measures **17.0 t/s** decode instead of 15, so quality was not bought with
> speed.
>
> The capability that forced this whole shape is a GGUF tensor type:
> **`GGML_TYPE_Q8_0_ROCMFPX` (103)**. It exists in exactly one loader on this
> host, so the runtime was decided by the file, not by preference.
## Identity
| | |
|---|---|
| Host / device | Dankclaw (192.168.0.143), Radeon 8060S iGPU `gfx1151`, ~114 GiB GTT aperture |
| Endpoint | `http://192.168.0.143:7770` — alias `frank-large`, `/v1` OpenAI surface |
| Runtime | **`kingjones30/ROCmFPX`** llama.cpp fork @ `36e9acd40e10a87cd3c3ef8ec734668757dc8520`, built by [`scripts/build-rocmfpx.sh`](../../scripts/build-rocmfpx.sh) → `/home/dank/GitPackages/kingjones-ROCmFPX/build/bin/llama-server` |
| Unit | root systemd `frank-large.service` ([`scripts/frank-large.service`](../../scripts/frank-large.service)), `User=dank`, `Restart=always` |
| Serve script | [`scripts/serve-frank-large.sh`](../../scripts/serve-frank-large.sh) (owns the argv), tunables [`scripts/frank-large.env`](../../scripts/frank-large.env) |
| Weights | `/home/dank/models/kingjones-Qwen3.8-27B-ROCmFP4-STRIX-MTP/Qwen3.8-27B-Q8_0_ROCMFPX_AGENT.gguf` — 28,214,425,952 B, sha256 `f3ef2bdbf56e244f…` |
| Draft | `…/mtp-Qwen3.8-27B-Q4_0.gguf` — 1,680,271,648 B, sha256 `051a1764cff8c4f3…` |
| Projector | `…/mmproj-Qwen3.8-27B-BF16.gguf` — 931,145,888 B, sha256 `de2a4986…` |
| Fetch | [`scripts/download-frank-large-kingjones.sh`](../../scripts/download-frank-large-kingjones.sh) (`-f`, byte-count + LFS sha256 verified, `--verify-only`, token never on the command line) |
| Seam | `tests/frank_large_unit.bats` (19 tests: payload gates, deployer/serve parity, spec block, KV dtype, sweep identity) |
## Why this file, and why only this runtime
`kingjones777/Qwen3.8-27B-ROCmFP4-STRIX-MTP-GGUF` ships several rungs. Parsed
headers of the two candidates:
| File | ftype | Tensor mix | Output-head tensors at plain Q8_0 | Card MTP acceptance |
|---|---|---|---|---|
| `Qwen3.8-27B-Q8_0_ROCMFPX_AGENT.gguf` | **115** | 353 F32 + 187 Q8_0 + **311 type-103** | **187** | 0.953 |
| `Qwen3.8-27B-Q8_0_ROCMFPX.gguf` | 111 | 2 Q8_0 + type-103 | 2 | 0.911 |
Two consequences, both measured off the header rather than guessed:
1. **Quality.** The AGENT routing variant keeps the output-head (and other
routing-sensitive) tensors at plain Q8_0 instead of folding them into the
ROCmFPX kernel layout — 187 vs 2 — so the logits the sampler reads are the
highest-precision tensors in the file. It is also the card's MTP-tuned
variant, so it is the *faster* drafter base at the same time.
2. **The runtime is forced.** Type 103 is a private extension: stock llama.cpp
and gufo both fail at load (`unknown tensor type`). Verified on the host
before deploying — the bake-off was not a horse race, it was a lock-in
check.
**The build identity matters as much as the fork.** The 2026-08-25 ROCmFPX
builds read this file and then died in `ggml_compute_forward_set_rows` — the
exact failure documented in [[kingjones-q8agent-rocmfpx]] when this payload was
first attempted on Dankclaw and routed to Dankserver as
[[frank-medium-rocmfpx]] instead. `scripts/build-rocmfpx.sh` therefore checks
the commit out **by SHA** and refuses to build anything else; the pin is
load-bearing, not tidiness.
## Shape and budget
One session, the model's full native window, unquantized KV:
| Dial | Value | Why |
|---|---|---|
| `--ctx-size` | 262,144 | "one full context" — the native window, no rope scaling |
| `--parallel` | 1 | one conversation, all memory to it |
| KV dtype | **f16** (both K and V) | ~64 KiB/token → ~16 GiB; free inside a 114 GiB aperture, so there is no reason to pay a quant |
| `--fit off` | on | the auto-fitter would silently resize the window we asked for |
| `--flash-attn on` | on | required for the long-window attention path to fit |
| `--direct-io` | on | bypasses page cache for the 26 GiB weight stream (mmap is disabled by it — deliberate) |
| `--ctx-checkpoints 16` | 16 | slot state for checkpoint/rollback |
| `--cache-ram 8192` + `--cache-idle-slots` | 8 GiB | prompt cache; verified a repeat pass over the same 6k prompt replays in **0.5 s** |
| `--jinja` | on | without it `chat_template_kwargs` are silently ignored |
| `--reasoning on --reasoning-format deepseek --reasoning-budget -1` | | thinking in its own channel, unbounded |
Measured steady state (production, one model copy resident):
`mem_info_gtt_used` **63.1 GiB** of the ~114 GiB aperture, `mem_info_vram_used`
0.17 / 2.0 GiB (the iGPU's dedicated carve-out is a stub; everything real lives
in GTT). llama-server RSS 2.1 GiB. Boot to `/health` 200: **16 s** — the fastest
endpoint bring-up in the fleet, because there is no engine compile step.
## Speculative decode — measured, not assumed
```
--spec-type draft-mtp --model-draft <mtp-Qwen3.8-27B-Q4_0.gguf>
--spec-draft-n-max 4 --spec-draft-n-min 0 --spec-draft-p-min 0.0
--spec-draft-device ROCm0 --spec-draft-ngl 99
```
MTP in llama.cpp is a property of the file, not of the flags: the head is a
trained tensor set (`nextn_predict_layers = 1` in this repo's head, arch
`qwen35`, 65 blocks) and the draft context runs on the main model's weights, so
there is no second 26 GiB copy in memory. See the fleet law in
`AGENTS.md → llama.cpp serving`.
**A/B, 2026-10-02** — same session, temp 0, 2,202-token prompt, 512 tokens,
`cache_prompt: false`, `frank-large.service` stopped for every scratch arm (the
benchmarking law), baseline arm stripped of `--model-draft` **and** every
`--spec-*` flag:
| Arm | Decode t/s (2 runs) | Prefill t/s | Draft acceptance |
|---|---|---|---|
| **MTP, n-max 4 (deployed)** | **17.00 / 17.14** | 350.6 / 324.9 | 0.462 (mean acceptance length ≈ 1.86) |
| no draft | 7.60 / 7.66 | 381.8 / 381.0 | — |
**+123 % decode for an 8–15 % prefill tax.** Notes that matter before someone
re-litigates this:
- Acceptance here (0.462) is nowhere near the card's 0.953. The card measures
its own short, repetitive text; this is a 2.2k-token prose prompt. Treat the
card's number as a file property, not a throughput promise.
- `n-max 4` is where the gain was measured; 2 and 8 are **unmeasured**. The
gufo-era law applies in spirit — never rank spec settings on a
self-predictable corpus.
- End-to-end on the chat path is slower than the `/completion` number because
thinking tokens are included: a 2,253-token chat prompt generating 512
tokens took 43.8 s wall (11.7 t/s end-to-end) — that is the cost of an
unbounded reasoning budget, not a regression in decoding.
## Client contract (live-verified 2026-10-02)
| Behavior | Observation |
|---|---|
| Model id | `/v1/models` → `frank-large` |
| Tools | native: `get_weather` → `{"city": "Seattle"}` in `tool_calls` |
| Thinking | in **`reasoning_content`** (llama.cpp field — *not* vLLM's `reasoning`); `models.yml` sets `reasoningContentField` accordingly |
| `reasoning_effort` | accepts **only** `xhigh`, `medium`, `low`; anything else is HTTP 500 (the template raises, it does not clamp). `models.yml` folds `high`/`max` → `xhigh` |
| Sampling | server defaults = the card's thinking recipe (temp 1.0, top_p 0.95, top_k 20, min_p 0, presence 0), mirrored in the harness `extraBody` |
| Vision | the BF16 projector loads (`loaded multimodal model`); a red square answers **`Red`** (`usage: 75 prompt / 71 cached`) |
| Prompt cache | second pass over the same 6k prompt: 0.5 s wall |
Three traps, all hit for real:
1. **`content: null` when reasoning eats the budget.** With
`--reasoning-parser`-style separation, a request whose `max_tokens` is
consumed entirely by thinking returns `message.content = None`. A bench
client that indexes `content` crashes *after* measuring and loses the
numbers — fall back to `reasoning_content`, or size the budget (200 was
enough for the vision probe).
2. **`MTP boundary missing for seq_id=… ; resyncing after a non-token step`**
appears in the log under draft resets. Self-recovering; not an outage signal.
3. **Never `pkill -f llama-server` on Dankclaw** — frank-small is also a
`llama-server`. The sweep key here is the payload name:
`pkill -f 'Qwen3.8-27B-Q8_0_ROCMFPX_AGENT'`.
## Operations
```bash
# deploy (planner selects this endpoint only via its own unit/env/serve trio)
./scripts/deploy.sh dankclaw --service frank-large
# status / logs / cause of a crash loop
systemctl status frank-large
journalctl -u frank-large -n 200 --no-pager
# rebuild the pinned fork (only when deliberately moving the pin)
scripts/build-rocmfpx.sh
# re-verify the payload without re-downloading
scripts/download-frank-large-kingjones.sh --verify-only
```
`serve-frank-large.sh` refuses to start — before touching the port — unless the
fork binary, the weights, the MTP head and (unless `FRANK_LARGE_MMPROJ=""`) the
projector all exist; `scripts/deploy-remote.sh` mirrors the same predicate so a
broken payload never stops the running unit. Caller environment **overrides**
`frank-large.env`, and defaults use `:=` so an explicitly empty value surfaces
as the error it reads as.
## Rollback
git tag **`frank-large-gufo-q4kxl-20261001`**: gufo v0.1.1
(`scripts/build-gufo.sh` still on disk), the Q4_K_XL Qwen3.8-27B payload and the
DFlash2 drafter all remain on the host. Restore that tag's unit/env/serve trio
and redeploy — nothing here deletes anything.
The rollback payloads stay exactly where the tag's env file expects them:
`/home/dank/models/Qwen3.8-27B-UD-Q4_K_XL/` (16.35 GiB) and the DFlash2
drafter `/home/dank/models/Qwen3.8-27B-UD-Q8_K_XL/Qwen3.8-27B-DFlash2-Q4_K_M.gguf`
(1.07 GiB). The one-day vLLM MiMo era's payloads (MiMo-V2.6 BF16 18 GiB,
Qwen3.5-9B MTP source 19 GiB, both DFlash draft dirs) were staged to
`/home/dank/.AGENTTRASH/20261002-retired-llm-payloads/` on 2026-10-02 —
recoverable until the trash is purged, and never part of a rollback plan.
## When it misbehaves
- **`unknown tensor type` / ftype 115 refused** — something moved off the
ROCmFPX binary. Check `readlink -f $(systemctl show frank-large -p ExecStart)`
and the fork commit; this file cannot run on stock llama.cpp or gufo.
- **SIGSEGV in `ggml_compute_forward_set_rows` during load** — a fork build
older than the `36e9acd` pin; rebuild with `scripts/build-rocmfpx.sh`.
History: [[kingjones-q8agent-rocmfpx]].
- **Slow decode with no log error** — check whether the draft is engaged
(`/metrics`, `draft_n` / `draft_n_accepted`; a zero draft count means the head
did not load), and check GTT pressure with
`cat /sys/class/drm/card1/device/mem_info_gtt_used` — a second resident copy
of this model (an orphaned scratch server) drives the whole host into
eviction and halves the rate silently.
- **`500` naming Jinja** — a `chat_template_kwargs` field reached a server
without `--jinja`.
- **HTTP 500 naming the template on the first request of a role** — an
unmapped `reasoning_effort`; fix the fold in `models.yml`, not the model.
@@ -0,0 +1,186 @@
---
type: reference
title: "frank-large on Dankclaw — vLLM TheRock, MiMo-V2.6-Distill-Qwen-9B BF16 + cross-model MTP (RETIRED)"
description: "The RETIRED frank-large runbook (2026-10-01, one day) — the digest-pinned kyuz0 TheRock gfx1151 vLLM image serving XiaomiMiMo MiMo-V2.6-Distill-Qwen-9B in full BF16 on the Strix Halo iGPU. Kept for the measured record: the roof math, the cross-model MTP drafter, and the autoresearch finding that spec decode is NET-NEGATIVE on real chat+reasoning traffic here (6.19 t/s with MTP-2 vs 9.01 t/s without). Rolled back to [[frank-large-gufo-qwen38-27b]] by Frank the same night."
tags:
- llm
- frank-large
- dankclaw
- vllm
- strix-halo
- mimo
- mtp
- spec-decode
- bf16
timestamp: 2026-10-01
---
# frank-large — vLLM MiMo-V2.6-Distill-Qwen-9B BF16 (cross-model MTP)
> **RETIRED 2026-10-01 night, one day active.** Frank's call after the
> autoresearch loop: battery decode 6.19 t/s (MTP-2) / 9.01 t/s (no draft)
> against gufo's ~15 t/s on the 27B — and every ≥6-bit quant path in vLLM
> 0.30 is dead on gfx1151 (quark int8 rejected; all FP8 kernels CDNA-only;
> torchao config unwired). Back to [[frank-large-gufo-qwen38-27b]]
> (Q4_K_XL, 1 x 262144). The measured content below stands as the record.
## Identity
- **Endpoint:** `frank-large` at `192.168.0.143:7770` (Dankclaw).
- **Runtime:** vLLM 0.30.0 in the **digest-pinned** `docker.io/kyuz0/vllm-therock-gfx1151`
image (image ID `2d24a8c5a3fd`, digest `sha256:98c1f3ac9833…` — ROCm 10.0.0 /
torch 2.11.0 / TheRock, Triton Gated DeltaNet kernels). The official vLLM
images are CUDA-only; this fork is the fleet's gfx1151 path. Plain
`podman run` driven by `scripts/serve-frank-large.sh` under a root unit
(`scripts/frank-large.service`, `User=dank`, `Restart=always`,
`ExecStop=podman stop -t 120`, `TimeoutStopSec=180` > the stop grace).
- **Model:** `XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B` in **full BF16**
(17.53 GiB, 4 shards) — the same checkpoint frank-small serves as an INT8
W8A16 AutoRound conversion on the 3090, here unquantized.
- **Draft:** `Qwen/Qwen3.5-9B` (18 GiB on disk; only the 15 `mtp.*` tensors
are loaded into the draft pass).
## Why this shape (the roof math)
Decode speed for a dense model on Strix Halo is bandwidth-bound:
BF16 weights x one pass per token against the LPDDR5x aperture. Measured
2026-10-01 on this host: **13.1 t/s is ~94% of the roof** — the payload, not
a misconfiguration. The same INT8 payload reaches 83.9 t/s on the 3090
because it moves ~12 GiB through ~936 GB/s. The only way past a bandwidth
wall is generating more than one token per weight pass: **speculative decode
is the performance feature of this endpoint**, not a garnish.
The memory side is the opposite of a squeeze: KV grows ONLY on the 8 full
attention layers (32 KiB/token bf16: 8 x 2 x 4 heads x 256 dim x 2 B);
the 24 Gated DeltaNet layers hold a FIXED ~25 MiB state per running
sequence. `--max-model-len 262144` (the native window) with
`--max-num-seqs 4` at `--gpu-memory-utilization 0.45` boots clean — the
four-session contract the gufo shape ran, with the pool shared by the
scheduler instead of carved per session.
## Spec method: cross-model MTP — measured, not assumed
| arm | prefill | decode | acceptance |
|---|---|---|---|
| BF16 base | 17,876 t/s | 13.1 t/s | — |
| BF16 + DFlash 8 tok | 7,976 t/s | 17.4 t/s | pos0 59% pos1 26% (token rate 14.8%) |
| **BF16 + MTP 2 tok** | 7,380 t/s | **19.8 t/s** | pos0 71% pos1 44% (token rate 57.4%) |
One session, temperature 0, 28,647-token prefill / 512-token decode, same
client for all three arms (2026-10-01 bench window, frank-large stopped per
Benchmarking Policy). **MTP wins (+51% vs +33%) and needs only 2 draft
tokens** — acceptance past position 1 is 44% and falling; DFlash's own curve
decays 59/26/14/7, so 8 proposals are mostly wasted verification.
`num_speculative_tokens` beyond 2 is UNMEASURED; do not raise it without a
fresh A/B. Both spec arms pay ~55–59% of prefill (the draft passes share
the compute queues) — this endpoint's thinking-heavy traffic spends its wall
clock in decode, which is the regime where that trade wins.
**Why a Qwen head accepts on a MiMo target:** MiMo-V2.6 is a distillation of
Qwen3.5-9B that preserves the hidden-state geometry — identical
4096-hidden/248320-vocab/32-layer/interval-4 structure, and the 71%/44%
per-position acceptance is the direct measurement that the distillation
preserved more than geometry. MiMo itself ships **ZERO `mtp.*` tensors**
(verified in both the BF16 base and the INT8 conversion) — which is exactly
why frank-small's SGLang NEXTN draft is a 0.00-acceptance ghost: SGLang
reads the head from the TARGET checkpoint, vLLM reads the draft from a
separate path. That difference is the whole trick:
```
--speculative-config '{"method":"mtp","model":"/models/Qwen3.5-9B","num_speculative_tokens":2}'
```
The alternative drafter (`z-lab/Qwen3.5-9B-DFlash`, 6 layers, target_layer_ids
[1,5,…,29]) stays fetched on disk; flip `FRANK_LARGE_SPEC=dflash` and repoint
`FRANK_LARGE_SPEC_DIR` to use it. Its card's "vLLM PR #40898 unmerged" claim
is FALSE — `vllm/v1/spec_decode/dflash.py` ships in 0.30.
## The numerics trap (greedy text is NOT preserved by spec decode)
Measured: temperature-0 completions DIFFER across arms (sha `1318aeb6` base,
`0208b45d` dflash, `20c41c38` mtp). Batched verification changes the bf16
reduction order, argmax near-ties diverge, and the divergence cascades.
vLLM spec decode is distribution-preserving, not bitwise-greedy-preserving.
The gufo-era "greedy == autoregressive text" law does not carry over; do not
chase text drift between spec and no-spec arms as a regression.
## Payload
- Target: 4 safetensors shards (17.53 GiB) + config/tokenizer under
`/home/dank/models/MiMo-V2.6-Distill-Qwen-9B-BF16/`, each shard
byte-count + LFS sha256-verified by
`old/download-frank-large-mimo.sh` (`--verify-only` re-checks; no token on
the curl command line).
- MTP source: `old/download-frank-large-qwen35.sh` →
`/home/dank/models/Qwen3.5-9B/` (4 shards behind
`model.safetensors.index.json`; the shards carry the odd HF asset names
`model.safetensors-0000N-of-00004.safetensors` — the index resolves them,
the engine boots from exactly this tree).
- DFlash drafter: `old/download-frank-large-dflash.sh` →
`/home/dank/models/Qwen3.5-9B-DFlash/`.
- **Payload status 2026-10-02:** all three trees moved to
`/home/dank/.AGENTTRASH/20261002-retired-llm-payloads/` (59 GiB staged with
the other retired frank payloads) and the fetch trio moved to `old/` — the
endpoint is two runtimes past this one, and re-fetch is cheaper than disk.
- The serve script gates the image by REPO DIGEST (rootless podman resolves
tags from the network; the pin exists to boot exactly these bytes
offline), then config + index + exact shard count, then the spec draft
(either weight layout: single `model.safetensors` or a sharded index),
then `/dev/kfd` + whole `/dev/dri` (never individual renderD nodes —
Dankserver 2026-09-29 lesson).
## Client contract
- **Alias:** `frank-large` (the `id` at `/v1/models`).
- **Reasoning:** `--reasoning-parser qwen3`; vLLM emits the thinking text in
**`reasoning`**, NOT llama.cpp/gufo's `reasoning_content` — the harness
`models.yml` compat block for this provider sets
`reasoningContentField: "reasoning"`. Miss that and thinking silently
vanishes from transcripts.
- **Tools:** `--enable-auto-tool-choice --tool-call-parser qwen3_coder`.
- **Vision:** the checkpoint carries the `qwen3_5_vision` tower but the
serve script passes `--language-model-only` — the endpoint stays
text-only by decision; dropping the flag brings vision back.
- **Sampling:** request-side; the harness sends the Qwen3.5-family recipe
(temp 0.7, top_p 0.8) via `compat.extraBody`, and
`chat_template_kwargs.{enable_thinking,preserve_thinking}` — the
`chat_template_kwargs` form is what vLLM reads; a top-level
`preserve_thinking` is ignored there.
- **Env hygiene:** every tunable is `FRANK_LARGE_`-prefixed because HIP
reads bare `TEMP`/`HOST`/`GPU_MAX_HEAP_SIZE` and the serve script exports
the env file with `set -a`.
## Ops
- Boot ~200–240 s warm; health 503 while loading (do not kill it).
- The serve script sweeps stale container identities before starting:
`frank-large-mimo` itself and the bench-window container `vllm-mimo`.
- Container death → `podman wait` returns non-zero from ExecStart →
`Restart=always` self-heals (a clean exit-0 drain also restarts, the
frank-primary lesson).
- Bench windows: `systemctl stop frank-large` is enough (mask fails on the
relinked unit; the deploy restores).
- First-deploy facts (2026-10-01, deploy #3): healthy after **230 s**;
boot log `GPU KV cache size: 819,332 tokens, Maximum concurrency for
262,144 tokens per request: 3.13x` — four sessions share the pool
(the scheduler, not a carve). Live battery green: alias `frank-large`,
reasoning split into `reasoning`, tool_calls with correct args, and
`/metrics` acceptance pos0 69% pos1 44% (54/86 draft tokens accepted),
matching the bench window.
## Rollback
Git tag **`frank-large-gufo-q4kxl-20261001`** — gufo v0.1.1 (built from
source, `scripts/build-gufo.sh` stays on disk) + the Q4_K_XL Qwen3.8-27B
payload + DFlash2 drafter, all still on the host. Restoring the tag's
unit/env/serve trio and redeploying returns the 27B endpoint.
# Citations
- Model: https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B
- Draft source: https://huggingface.co/Qwen/Qwen3.5-9B
- DFlash drafter: https://huggingface.co/z-lab/Qwen3.5-9B-DFlash
- Engine image: https://hub.docker.com/r/kyuz0/vllm-therock-gfx1151
- Serve script: `scripts/serve-frank-large.sh`; tunables: `scripts/frank-large.env`
- Predecessor: [[frank-large-gufo-qwen38-27b]]; sibling on the same arch:
[[frank-small-sglang-mimo-v26]]
@@ -0,0 +1,171 @@
---
type: reference
title: "frank-small on Dankclaw — llama.cpp, MiMo-V2.6-Distill-Qwen-9B Q5_K_M GGUF"
description: "The active frank-small runbook — a CUDA (sm_86) build of llama.cpp master serving bartowski's MiMo-V2.6-Distill-Qwen-9B Q5_K_M GGUF on the RTX 3090: three conversations of 180,224 tokens, mmproj vision, the asymmetric KV contract (f16 K + q8_0 V), the two VRAM measurements that set the pool size, and what to check when it misbehaves."
tags:
- llm
- frank-small
- dankclaw
- llama-cpp
- rtx3090
- mimo
- gguf
- kv-cache
timestamp: 2026-10-02
---
# frank-small — llama.cpp MiMo-V2.6 Q5_K_M (RTX 3090)
> **ACTIVE since 2026-10-02.** One quant step down from
> [[frank-small-llama-mimo-q6k]] on the same runtime and the same KV
> contract, then **resized twice the same day** on Frank's orders: first to
> three contexts with vision, then down to the pool that keeps 2–3 GiB of the
> card free. Frank's arithmetic request — "as much as can fit while keeping
> overhead open space to 2-3gb on the 3090" — is answered by the two
> measurements in *Shape and the KV contract* below; the answer is
> **3 × 180,224**, not 3 × 262,144.
> **The tradeoff is the per-slot window.** Three sessions cost 81,920 tokens
> of per-conversation memory versus the two-slot shape: 180,224 tokens each
> instead of the model's native 262,144. See *What three slots cost*.
## Identity
|Field|Value|
|---|---|
|Endpoint|`192.168.0.143:7771`, served alias `frank-small`|
|Runtime|llama.cpp **master** (qwen35 model support), CUDA build `sm_86`, at `/home/dank/GitPackages/llama-master/build-cuda/bin/llama-server` — unchanged across the quant swap|
|Payload|`bartowski/MiMo-V2.6-Distill-Qwen-9B-GGUF` **Q5_K_M**, 6,876,124,704 B (6.40 GiB), sha256 `04cf46f2b5584ef922697d6c063f94879434fb86c467f1a09e52daf0cddaf35f` + the repo's `mmproj-MiMo-V2.6-Distill-Qwen-9B-f16.gguf`, 918,166,048 B, sha256 `ff348f3180a63188aa7285db85f550fe38acb61dd013c599eb8bad08d2cc2576` — both at `/home/dank/models/MiMo-Q5KM/`, fetched and byte- and sha256-verified by `scripts/download-frank-small.sh`|
|Unit|root `frank-small.service` (repo `scripts/frank-small.service`, `User=dank`, relinked), env `scripts/frank-small.env`, serve `scripts/serve-frank-small.sh`|
|Repo pins|`tests/frank_small_unit.bats` (stub-argv seam + the VRAM arithmetic), `deploy_llm_small` gates in `scripts/deploy-remote.sh`|
## Shape and the KV contract
`--ctx-size 540672 --parallel 3` — llama.cpp divides the pool across slots, so
each conversation gets `n_ctx_slot = 180224` (boot log: `n_slots = 3,
n_ctx_slot = 180224, kv_unified = 'false'`). `CTX_SIZE` MUST stay divisible by
`PARALLEL`; the bats seam enforces it.
The KV contract is Frank's: **K unquantized (f16), V `q8_0`** —
`--cache-type-k f16 --cache-type-v q8_0`. Two hard dependencies ride on it:
- **`--flash-attn on` is mandatory**: quantized V exists only on the FA path.
Without the flag the engine falls back silently and the contract becomes a
lie. The serve script pins the trio; the bats seam pins the script.
- The VRAM budget: attention KV lives in the 8 full-attention layers only
(4 KV heads × 256 dim). K f16 ≈ 16 KiB/token, V q8_0 ≈ 8.5 KiB/token
(34 B per 32-element block) ⇒ ~24.5 KiB/token over the pool.
**The pool size came from two boots, not from a formula.** `free`-style
arithmetic on this stack is unreliable because the compute buffers, CUDA
graphs and now the vision tower all bill separately, so the fit was measured
at two shapes and solved between them:
|Shape|Projector|`nvidia-smi` used|KV at 24.5 KiB/token|Non-KV (weights + buffers + projector)|
|---|---|---|---|---|
|2 × 262,144 (pool 524,288)|none|20,190 MiB|12,800 MiB|**7,390 MiB**|
|3 × 196,608 (pool 589,824)|f16|22,972 MiB|14,113 MiB|**8,859 MiB**|
The two rows price the projector and its image buffers at **~1.4 GiB** — not
the ~0.9 GiB the 918 MB file suggests, because the vision encoder's own
activation and compute buffers ride along. Solving the second row's non-KV cost
against Frank's 2–3 GiB band: the card is 24,576 MiB, so
`KV ≤ 24,576 − 9,216 − 2,048 = 13,312 MiB` ⇒ pool ≤ 556,630 tokens, rounded
down to a multiple of 3 × 4,096 ⇒ **540,672**, i.e. 13,265 MiB of KV and
**2,441 MiB free** (measured, 21,684 MiB used).
**Why 3 × 262,144 was never possible.** Three native windows are 786,432
tokens = 18.4 GiB of KV *alone*; plus the 8.86 GiB of non-KV cost that is
27.3 GiB on a 24 GiB card. The quant step bought 0.86 GiB; the geometry needed
6 GiB.
## Measured on this shape (2026-10-02, 3 × 180,224 + vision)
|Check|Result|
|---|---|
|Boot to healthy|~20 s, `n_slots = 3`, `n_ctx_slot = 180224`, `loaded multimodal model` logged|
|VRAM|**21,684 MiB used / 2,441 MiB free** of 24,576 (`nvidia-smi`, steady state; the KV pool is allocated whole at boot, so this is the ceiling)|
|Decode, temp 0, no thinking|**106.8 tok/s** (256-token completion at ~1,300-token depth)|
|Prefill|**3,814 tok/s** (same request)|
|Three concurrent requests|all three answered in 1.7 s wall — real parallel slots|
|Fourth concurrent request|answered in 3.0 s while three ran — queued behind a released slot, as the slot ceiling requires|
|Vision|`image_url` part with a 64×64 solid-red PNG → **"Red."**|
|Tools|native `tool_calls` with correct arguments (`get_weather {"city":"Seattle","unit":"f"}`)|
|Thinking|`reasoning_content` populated (145 chars on a "think first" prompt); `reasoning_effort: "low"` accepted|
|Over-slot prompt|`400 exceed_context_size_error: request (184001 tokens) exceeds the available context size (180224 tokens)` — refused, never silently truncated|
Decode is ~5 % **faster** than the 2 × 262,144 shape measured earlier the same
day (100.4–101.8 tok/s): a shorter per-slot window means a shorter attention
scan at equal prompt depth, and one less slot's DeltaNet state resident.
## What three slots cost
The per-slot window is the whole price. Two consequences the fleet depends on:
- **A prompt over 180,224 tokens is a hard 400**, so `~/.omp/agent/models.yml`
sets `contextWindow: 180224` for this endpoint — the harness compacts before
it reaches the ceiling instead of discovering it.
- **frank-primary's compaction prompt no longer fits with room to answer.**
Its trigger is 183,501 tokens — already above this slot — and its summary
budget is 32,768 output tokens. On the two-slot shape (262,144) that left
32.8k of output room, which is why that number was chosen; on this shape a
single compaction request must be truncated or split. Nothing in the fleet
routes compaction here automatically, but any runbook that claims frank-small
"fits a compaction request in ONE request" is describing the 262,144 shape.
## Client contract
- Thinking arrives in **`reasoning_content`** (`--reasoning-format deepseek`),
the field `models.yml` reads for this endpoint.
- **Thinking is off unless the request asks**: the MiMo GGUF template defaults
`enable_thinking` false, so `models.yml` ships
`chat_template_kwargs: {enable_thinking: true, preserve_thinking: true}` in
`extraBody`. A raw client that omits it gets a direct answer — measured, and
not a fault. Trivial questions produce no thinking even with the flag on.
- Tools: `--jinja` + server-side parsing, verified 2026-10-02.
- **Vision is on**, through the projector file (`--mmproj`). Use the
OpenAI-standard `image_url` content part — that path answers correctly
("Red." on a solid-red PNG). The legacy top-level `images` field is **not**
read by `/v1/chat/completions`: the same request sent that way answered
"Brown.", i.e. it generated from text alone. `/completion` takes `images`
but refuses a request without `messages` in this build, so chat is the only
vision path.
- Setting `MMPROJ_FILE=` (explicitly empty) in `scripts/frank-small.env` drops
`--mmproj` and returns ~1.4 GiB of the card to KV — the documented text-only
opt-out. `MMPROJ_FILE` pointing at a file that does not exist is a boot
refusal, never a silent fallback to blindness.
## No spec decode
The GGUF has no MTP tensors (the same fact that made SGLang's NEXTN a 0.00
ghost), and the cross-model DFlash draft
(`/home/dank/models/DFlash-Qwen35/qwen3.5-9b-dflash-Q8_0.gguf`) is an
optimization candidate, not a default — acceptance has to be measured on this
traffic first. The bats seam fails if a draft flag ships unannounced.
## Rollback
|Target|How|
|---|---|
|Q6_K, same runtime|`scripts/frank-small.env` `MODEL_FILE=/home/dank/models/MiMo-Q6K/MiMo-V2.6-Distill-Qwen-9B-Q6_K.gguf` (7,793,710,624 B, still on disk) and the deployer's `LLM_SMALL_MODEL_FILE` default. Q6_K needs ~1.4 GiB more than Q5_K_M, so pair the rollback with `CTX_SIZE` 49,152 tokens lower or `MMPROJ_FILE=`|
|Two 262,144 windows|`CTX_SIZE=524288 PARALLEL=2` (measured 20,190 MiB used, 4,386 free) and `contextWindow: 262144` in `models.yml` — choose it when a single conversation needs the native window or when frank-primary's compaction request has to land here|
|Vision off|`MMPROJ_FILE=` in the env file; the deployer gate then has to be satisfied too, so point `LLM_SMALL_MMPROJ` at any real projector file or drop the gate in the same commit|
|SGLang + INT8|[[frank-small-sglang-mimo-v26]] — venv and old unit/env/serve trio still in place; the INT8 payload was staged to `/home/dank/.AGENTTRASH/20261002-retired-llm-payloads/` on 2026-10-02, so restore it there or re-fetch with `old/download-frank-small-sglang-int8.sh`|
## When it misbehaves
- Port 7771 dark: `journalctl -u frank-small -n 50`; the serve script exits 1
naming the missing file if the binary or GGUF moved.
- `No CUDA GPUs are available`: the 3090 vanished from the bus or the UVM node
is missing — `nvidia-modprobe -u -c=0` (the serve script runs it).
- Requests queue behind each other: three concurrent long generations are the
slot ceiling by contract; a fourth waits for a slot to free (measured: 1.7 s
for the three, 3.0 s for the fourth).
- `400 … exceeds the available context size (180224 tokens)`: the conversation
outgrew ONE slot. This is not pool exhaustion — the pool is 540,672 tokens
and the per-slot window is the binding limit. Shorten the prompt, compact, or
roll back to the 262,144 shape above.
- Vision answers a color it never saw: the client sent `images` instead of an
`image_url` content part (see *Client contract*).
- Slow decode after a CTX or quant change: check `nvidia-smi` — pushing KV out
of VRAM into unified memory halves the rate silently.
@@ -0,0 +1,110 @@
---
type: reference
title: "frank-small on Dankclaw — llama.cpp, MiMo-V2.6-Distill-Qwen-9B Q6_K GGUF (retired)"
description: "The retired 2026-10-01 frank-small runbook — the first llama.cpp + GGUF shape on the RTX 3090: two native-window sessions, the asymmetric KV contract (f16 K + q8_0 V) that motivated the move off SGLang, the VRAM fit at Q6_K, and what to check when it misbehaves. Superseded the same night by the Q5_K_M payload."
tags:
- llm
- frank-small
- dankclaw
- llama-cpp
- rtx3090
- mimo
- gguf
- kv-cache
timestamp: 2026-10-01
---
# frank-small — llama.cpp MiMo-V2.6 Q6_K (RTX 3090)
> **RETIRED 2026-10-01 → 10-02** (one night): superseded by
> [[frank-small-llama-mimo-q5km]], the same runtime and shape one quant rung
> down. The Q6_K file stays at `/home/dank/models/MiMo-Q6K/` as the rollback
> target.
>
> Original order (Frank, 2026-10-01 night): move this endpoint to the GGUF
> path for **asymmetric KV** — unquantized K + q8_0 V — which only llama.cpp
> exposes per-tensor. That contract is what the current deployment kept.
## Identity
|Field|Value|
|---|---|
|Endpoint|`192.168.0.143:7771`, served alias `frank-small`|
|Runtime|llama.cpp **master** (qwen35 model support), CUDA build `sm_86`, at `/home/dank/GitPackages/llama-master/build-cuda/bin/llama-server`|
|Payload|`bartowski/MiMo-V2.6-Distill-Qwen-9B-GGUF` **Q6_K**, 7,793,710,624 B, sha256 `ef96d05a2ddf2cbb450d1af1ac3860ec769d3575bafa70692ee5609bda3fad7d`, at `/home/dank/models/MiMo-Q6K/`|
|Unit|root `frank-small.service` (repo `scripts/frank-small.service`, `User=dank`, relinked), env `scripts/frank-small.env`, serve `scripts/serve-frank-small.sh`|
|Repo pins|`tests/frank_small_unit.bats` (stub-argv seam), `deploy_llm_small` gates in `scripts/deploy-remote.sh`|
## Shape and the KV contract
`--ctx-size 524288 --parallel 2` — llama.cpp divides the pool across slots,
so each session gets `n_ctx_slot = 262144`, the model's full native window
(boot log confirms `n_slots = 2, n_ctx_slot = 262144, kv_unified = 'false'`).
Frank's KV contract: **K unquantized (f16), V `q8_0`** —
`--cache-type-k f16 --cache-type-v q8_0`. Two hard dependencies ride on it:
- **`--flash-attn on` is mandatory**: quantized V exists only on the FA
path. Without the flag the engine falls back silently and the contract
becomes a lie. The serve script pins the trio; the bats seam pins the
script.
- The VRAM budget: attention KV lives in the 8 full-attention layers only
(4 KV heads x 256 dim). K f16 ≈ 16 KiB/token, V q8_0 ≈ 8.5 KiB/token
(34 B per 32-element block) ⇒ ~24.5 KiB/token over the 524,288-token pool
≈ **12.6 GiB**. Weights 7.8 + KV 12.6 + compute buffers/graphs ≈
**20.9 GiB measured** against 24.5 GiB — the "room for checkpoints" the
order asked for. If graph capture OOMs, halve `CTX_SIZE`; never quantize
K to fix it.
## Client contract
- Thinking arrives in **`reasoning_content`** (`--reasoning-format
deepseek`) — the same field SGLang's qwen3 parser used, so `models.yml`
`reasoningContentField` did NOT move. Live-verified 2026-10-01 22:57.
- **Thinking is off unless the request asks**: the MiMo GGUF template
defaults `enable_thinking` false; `models.yml` now ships
`chat_template_kwargs: {enable_thinking: true, preserve_thinking: true}`
in `extraBody`. A raw client that omits it gets a no-thinking answer
(measured — this is not a fault).
- Tools: `--jinja` + server-side tool parsing, verified
`tool_calls` round-trip 2026-10-01 23:0x.
- **Text-only now.** The GGUF carries no vision projector; the
in-checkpoint tower existed only in the SGLang safetensors. `models.yml`
`input: [text]`.
## No spec decode (yet)
The GGUF has no MTP tensors (same fact that killed SGLang NEXTN), and the
cross-model DFlash draft (`/home/dank/models/DFlash-Qwen35/qwen3.5-9b-dflash-Q8_0.gguf`,
Q8_0) is an optimization-loop candidate, not a default — `--spec-type
draft-dflash` needs acceptance measured on this traffic first. The bats
seam fails if a draft flag ships unannounced.
## Build
No ccache, CUDA 12.4 system nvcc with `--gcc-install-dir`-free gcc-13 host
compiler (nvcc 12.4 rejects gcc ≥ 14):
```
cmake -B build-cuda -S . -DCMAKE_BUILD_TYPE=Release -DGGML_CUDA=ON \
-DCMAKE_CUDA_ARCHITECTURES=86 -DCMAKE_CUDA_HOST_COMPILER=/usr/bin/gcc-13 \
-DLLAMA_CURL=OFF -DGGML_CCACHE=OFF
cmake --build build-cuda -j 16 --target llama-server
```
The SGLang venv (`/home/dank/GitPackages/sglang-cu128`) and the INT8
AutoRound payload (`/home/dank/models/MiMo-V2.6-Distill-Qwen-9B-INT8-W8A16-AutoRound`)
stay on disk as the rollback: repoint the unit's serve script and env from
git history (`git show frank-large-gufo-q4kxl-20261001` era is BEFORE this;
use the parent of the 2026-10-01 night swap commit).
## When it misbehaves
- Port 7771 dark: `journalctl -u frank-small -n 50`; the serve script
exits 1 naming the missing file if the binary or GGUF moved.
- `No CUDA GPUs are available`: the 3090 vanished from the bus or the UVM
node is missing — `nvidia-modprobe -u -c=0` (the serve script runs it).
- Requests hang at first token while `/health` is 200: both slots busy —
two concurrent long generations are the ceiling by contract.
- Slow decode after a CTX change: check `nvidia-smi` — swapping KV out of
VRAM into unified memory halves the rate silently.
@@ -0,0 +1,180 @@
---
type: reference
title: "frank-small on Dankclaw — SGLang, MiMo-V2.6-Distill-Qwen-9B INT8 W8A16 (RETIRED)"
description: "The RETIRED frank-small runbook (2026-10-01, hours) — 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 ghost, the CUDA 13 nvcc toolchain the JIT needs, and the measured numbers kept for the record. Replaced by [[frank-small-llama-mimo-q6k]] the same night."
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)
> **RETIRED 2026-10-01, hours after cutover.** Replaced by
> [[frank-small-llama-mimo-q6k]] — llama.cpp CUDA on the MiMo Q6_K GGUF,
> chosen for the asymmetric KV (f16 K + q8_0 V) SGLang cannot express.
> The venv (`/home/dank/GitPackages/sglang-cu128/`) stays in place; the INT8
> payload was staged to
> `/home/dank/.AGENTTRASH/20261002-retired-llm-payloads/` on 2026-10-02 when
> the llama.cpp endpoint was two runtimes deep — recoverable until the trash
> is purged.
## 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. **That compaction arithmetic is
specific to a 262,144-token slot**: the ACTIVE shape runs three slots of
180,224, which 183,501 tokens already exceeds — see *What three slots
cost* in [[frank-small-llama-mimo-q5km]].
- **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 `old/download-frank-small-sglang-int8.sh`
(`--verify-only` re-checks) — the script moved to `old/` when the endpoint
cut over to llama.cpp + GGUF on 2026-10-01 night, and
`scripts/download-frank-small.sh` now fetches the GGUF quant instead. 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-llama-mimo-q5km]] is the live shape two steps forward; the
practical rollback today is [[frank-small-llama-mimo-q6k]] (payload at
`/home/dank/models/MiMo-Q6K/`). This era's own rollback, the llama.cpp
Gemma4-12B QAT payload, was staged to
`/home/dank/.AGENTTRASH/20261002-retired-llm-payloads/Gemma4-12B-QAT/` on
2026-10-02; its unit/env/serve trio remains in `old/`.
# 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
+77 -32
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 (2026-10-02):
**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 — **ROCmFPX llama.cpp (frank-large, port 7770:
kingjones777/Qwen3.8-27B-ROCmFP4-STRIX-MTP-GGUF Q8_0_ROCMFPX_AGENT, a ftype-115
file only that fork can read, with the repo's MTP head drafting 4 tokens, ONE
session at 262,144, f16 KV, vision via the bundled projector)** and
**llama.cpp CUDA (frank-small, port 7771: MiMo-V2.6-Distill-Qwen-9B Q5_K_M
GGUF, 2 x 262,144, asymmetric KV f16 K + q8_0 V, on the RTX 3090)**.
> 2026-08-22: the former `vllmScripts` repository is merged into the
> serverAppConfigs repository. This knowledge base moved from the old repo's
@@ -27,22 +31,22 @@ 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]
E2[RTX 3090 (PCIe x4 dock) +
gfx1151 iGPU 114 GiB GTT]
E[stock llama.cpp (unsloth b11030, gfx1151)
E[ROCmFPX llama.cpp gfx1151, pinned fork build
frank-large, port 7770]
F[Qwen3.8-27B UD-Q8_K_XL + DFlash2 Q4_K_M drafter
262144 ctx / 1 slot, DFlash2 depth 4, q8_0 KV]
G[mainline llama.cpp 37b53fd
F[Qwen3.8-27B Q8_0_ROCMFPX_AGENT + MTP-Q4_0 head
1 x 262144 ctx, f16 KV, draft n-max 4, mmproj vision]
G[llama.cpp master CUDA sm_86
frank-small, port 7771]
H[Gemma4-12B QAT Q4_K_M
4 x 262144 ctx, MTP + vision + audio]
H[MiMo-V2.6 Q5_K_M GGUF
2 x 262144 ctx, f16 K + q8_0 V, flash-attn]
E2 --> E --> F
E2 --> G --> H
end
@@ -61,7 +65,23 @@ frank-small, port 7771]
## Active Deployment
- [[frank-primary-glm53-flash-w4a16]] — the ACTIVE frank-primary runbook
- [[frank-large-rocmfpx-q8agent-mtp]] — **ACTIVE since 2026-10-02**
(root systemd unit, port 7770): the pinned kingjones30/ROCmFPX fork serving
the repo's highest-quality rung `Qwen3.8-27B-Q8_0_ROCMFPX_AGENT.gguf`
(26.28 GiB, ftype 115 = 187 plain-Q8_0 + 311 GGML_TYPE_Q8_0_ROCMFPX
tensors) with the bundled `mtp-Qwen3.8-27B-Q4_0.gguf` head drafting 4
tokens, one 262,144 window, f16 KV, the BF16 projector for vision. Why the
runtime is not interchangeable, the pinned-build set_rows history, the
measured envelope, rollback to gufo
- [[frank-small-llama-mimo-q5km]] — **ACTIVE since 2026-10-02** (root
systemd unit, port 7771): llama.cpp master (CUDA sm_86) serving
bartowski/MiMo-V2.6-Distill-Qwen-9B-GGUF Q5_K_M on the RTX 3090,
THREE slots of 180,224 tokens (pool 540,672) with K f16 + V q8_0 and the
mmproj for vision, ~100 tok/s decode, ~2.7 GiB of the card left free.
The KV arithmetic, the flash-attn dependency, rollback to Q6_K
- [[frank-primary-glm53-flash-w4a16]] — RETIRED 2026-09-30 → 10-01 (the
- failed GLM experiment; frank-primary runs Qwen FP8 again, see the intro):
(2026-09-30, root systemd unit, port 7770): the tcclaviger RDNA4 vLLM fork
(2026-09-30, root systemd unit, port 7770): the tcclaviger RDNA4 vLLM fork
(digest-pinned `tcclaviger/vllm@sha256:da4029666…`, plain `podman run`,
no shim) serving Intel/GLM-5.3-Flash-W4A16-AutoRound — AutoRound symmetric
@@ -158,14 +178,24 @@ frank-small, port 7771]
(bs1/bs3/bs4/bs6, 8k–700k KV) on Dankserver RTX 3090
- [[deployment]] — deploy and update process for both servers
- [[frank-redo-2026-08-17]] — the 2026-08-17 topology change
- [[frank-large-gufo-qwen38-27b]] — ACTIVE frank-large runbook since
2026-09-28 (root systemd unit, port 7770): gufo (gufo-org/gufo) v0.1.1, the
Strix Halo inference engine, built from source on Dankclaw, serving
unsloth/Qwen3.8-27B-GGUF:UD-Q8_K_XL (27B dense) with the z-lab DFlash2
Q4_K_M drafter (adaptive block policy) on the gfx1151 iGPU — one full
262,144-token conversation, greedy, text-only, the two from-source build
workarounds, the client-contract delta, the measured prefill/decode trade
against llama.cpp, troubleshooting
- [[frank-large-gufo-qwen38-27b]] — **RETIRED 2026-10-02 (the rollback
target)** (root systemd unit, port 7770): gufo
(gufo-org/gufo) v0.1.1, the Strix Halo inference engine, built from
source on Dankclaw, serving unsloth/Qwen3.8-27B-GGUF **UD-Q4_K_XL**
with the z-lab DFlash2 Q4_K_M drafter — ONE session at the full native
262,144 window, unquantized f16 KV. Rolled back by Frank after one day
of [[frank-large-vllm-mimo-v26-bf16]]. The two from-source build
workarounds, the client-contract delta, the measured prefill/decode
trade against llama.cpp
- [[frank-large-vllm-mimo-v26-bf16]] — RETIRED 2026-10-01 (one day;
rollback by Frank after the autoresearch loop): the digest-pinned
kyuz0/vllm-therock-gfx1151 image serving
XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B in FULL BF16, 4 x 262144 ctx,
CROSS-MODEL MTP from Qwen/Qwen3.5-9B — kept for the measured record:
battery decode 6.19 t/s (MTP-2) vs 9.01 t/s (no draft — spec NET-
NEGATIVE on real chat+reasoning traffic), the roof math, the greedy-text
numerics trap, and the death of every ≥6-bit vLLM quant path on gfx1151
(quark int8 rejected, FP8 kernels CDNA-only, torchao unwired)
- [[frank-large-unsloth-qwen38-27b-q8xl]] — RETIRED 2026-09-28 (replaced by
[[frank-large-gufo-qwen38-27b]]; rollback target): stock llama.cpp
(unsloth b11030, ROCm gfx1151) serving
@@ -199,12 +229,27 @@ frank-small, port 7771]
.hgn + quality overlay) on the gfx1151 iGPU — two 200k conversations over one
400,384-position pool, deployed flags, memory model, client contract,
troubleshooting (2026-09-16 → 09-19)
- [[frank-small-gemma4-12b]] — ACTIVE frank-small runbook since 2026-09-17
(root systemd unit, port 7771): mainline llama.cpp serving
- [[frank-small-llama-mimo-q6k]] — **RETIRED 2026-10-01 → 10-02 (rollback
target)**: llama.cpp (master, CUDA sm_86 build) serving
bartowski/MiMo-V2.6-Distill-Qwen-9B-GGUF **Q6_K** on the RTX 3090 — TWO
native 262,144-token sessions with ASYMMETRIC KV (K f16 unquantized + V
q8_0, which forces flash-attn), ~20.9/24.6 GiB measured, text-only (the
GGUF has no vision), reasoning_content, no spec decode; payload still at
`/home/dank/models/MiMo-Q6K/`
- [[frank-small-sglang-mimo-v26]] — RETIRED 2026-10-01 (hours; replaced
by [[frank-small-llama-mimo-q6k]] for the asymmetric KV SGLang cannot
express; venv still on disk, INT8 payload staged to
`~dank/.AGENTTRASH/20261002-retired-llm-payloads/`): SGLang in a
self-contained python3.12 venv serving leteschlead MiMo-V2.6 INT8
W8A16 AutoRound, 2 x 262144 ctx, fp8 KV, in-checkpoint vision,
83.9 tok/s decode
- [[frank-small-gemma4-12b]] — RETIRED 2026-09-17 → 2026-10-01 (replaced by
[[frank-small-sglang-mimo-v26]] → the llama.cpp MiMo shape; payload staged
to `~dank/.AGENTTRASH/20261002-retired-llm-payloads/Gemma4-12B-QAT/`):
mainline llama.cpp serving
HauhauCS/Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced Q4_K_M on the RTX
3090, with the separate MTP assistant sidecar chained behind ngram-mod,
q8_0 KV, and `--fit` sizing the full 262k window into ~12 GiB. A same-day
vLLM detour (2026-09-19) was reverted the same day; see below.
q8_0 KV, and `--fit` sizing the full 262k window into ~12 GiB.
- [[frank-small-vllm-gemma4]] — RETIRED 2026-09-19 (same-day revert,
rollback target): vLLM serving google/gemma-4-12B-it-qat-w4a16-ct (w4a16
Marlin) with the bf16 MTP assistant on the RTX 3090 — bf16 KV, 289,647-
+40 -11
View File
@@ -213,14 +213,27 @@ The LLM inference fleet on the two hosts. Full index:
agentionai/Qwen3.8-Flash-Next-ROCmFP4-FAST-imatrix (87.06 GiB,
Q4_0_ROCMFP4_FAST) + own MTP draft, build-qwen38 (retired 2026-08-30;
rollback record)
- [[frank-large-gufo-qwen38-27b]] — the ACTIVE frank-large runbook since
2026-09-28 (root systemd unit, port 7770): gufo (gufo-org/gufo) v0.1.1,
the Strix Halo inference engine, built from source on Dankclaw and
serving unsloth/Qwen3.8-27B-GGUF:UD-Q8_K_XL (a 27B dense model) with the
z-lab DFlash2 Q4_K_M drafter on the gfx1151 iGPU — one 262,144-token
conversation, adaptive block policy, greedy, text-only, the two
from-source build workarounds, what changed in the client contract, the
measured prefill/decode trade against llama.cpp
- [[frank-large-rocmfpx-q8agent-mtp]] — the ACTIVE frank-large runbook
since 2026-10-02 (root systemd unit, port 7770): the pinned kingjones30/
ROCmFPX fork (scripts/build-rocmfpx.sh) serving kingjones777/
Qwen3.8-27B-ROCmFP4-STRIX-MTP-GGUF **Q8_0_ROCMFPX_AGENT** — ftype 115,
311 tensors of GGML_TYPE_Q8_0_ROCMFPX, a format no other loader on the
host reads — with the repo's Q4_0 MTP head drafting 4 tokens and its BF16
projector, one session at the native 262,144 window
- [[frank-large-gufo-qwen38-27b]] — RETIRED 2026-10-01 → 10-02 (rollback
target, payload and `scripts/build-gufo.sh` both on disk): gufo v0.1.1
built from source serving Qwen3.8-27B UD-Q4_K_XL + the z-lab DFlash2
drafter on the gfx1151 iGPU — the two from-source build workarounds, the
template-hash allowlist, the measured prefill/decode trade
- [[frank-large-vllm-mimo-v26-bf16]] — RETIRED 2026-10-01 (same day;
replaced by the gufo rollback, then by
[[frank-large-rocmfpx-q8agent-mtp]]): the digest-pinned
kyuz0/vllm-therock-gfx1151 image (vLLM 0.30, TheRock ROCm 10) serving
XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B in FULL BF16 on the gfx1151 iGPU,
4 x 262,144 ctx, with CROSS-MODEL MTP spec decode from Qwen/Qwen3.5-9B —
the roof math (13.1 t/s base is ~94% of LPDDR5x BF16), the measured
MTP-vs-DFlash table (19.8 vs 17.4 t/s), the greedy-text numerics trap,
the `reasoning` field change, troubleshooting
- [[frank-large-unsloth-qwen38-27b-q8xl]] — RETIRED 2026-09-28 (replaced by
[[frank-large-gufo-qwen38-27b]]; rollback target): stock llama.cpp
(unsloth b11030, ROCm gfx1151) serving
@@ -269,10 +282,26 @@ 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-llama-mimo-q5km]] — the ACTIVE frank-small runbook since
2026-10-02: a CUDA (sm_86) build of llama.cpp master serving
bartowski/MiMo-V2.6-Distill-Qwen-9B-GGUF **Q5_K_M** on Dankclaw's RTX
3090, port 7771 — THREE conversations at 180,224 tokens each, the
asymmetric KV contract (f16 K + q8_0 V), vision through the repo's mmproj,
and the two VRAM measurements that set the pool size; ~100 tok/s decode
- [[frank-small-llama-mimo-q6k]] — RETIRED 2026-10-01 (same day; replaced
by [[frank-small-llama-mimo-q5km]], payload still on disk): the first
llama.cpp + GGUF shape for this endpoint, Q6_K at the same
2 x 262,144 / f16-K + q8_0-V contract, 20.9 GiB measured
- [[frank-small-sglang-mimo-v26]] — RETIRED 2026-10-01 (rollback target):
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,
2 x 262,144 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
+331
View File
@@ -662,3 +662,334 @@
- `/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`.
## 2026-10-01 — frank-large cutover: gufo -> vLLM TheRock, MiMo-V2.6 BF16 + cross-model MTP
- **Question that started it:** can a Qwen3.5 MTP drafter attach to
frank-small, and how does vLLM run the FULL BF16 MiMo checkpoint? Answer 1:
not on frank-small — SGLang reads the MTP head from the TARGET checkpoint
and MiMo ships ZERO `mtp.*` tensors (base and INT8 alike). Answer 2: the
digest-pinned `kyuz0/vllm-therock-gfx1151` image (vLLM 0.30 / torch 2.11 /
TheRock ROCm 10) boots BF16 MiMo on the gfx1151 iGPU in ~200-240 s, and
vLLM reads the draft from a SEPARATE path — so cross-model MTP from
`Qwen/Qwen3.5-9B` (the distill's source, identical 4096/248320/32-layer
geometry) works. Frank's call: ship that as frank-large.
- **Bench window (frank-large stopped, one session, temp 0, 28,647-token
prefill / 512 decode):** base 17,876 t/s prefill / 13.1 t/s decode (13.1
is ~94% of the LPDDR5x BF16 roof - decode here is bandwidth, not a bug);
+DFlash-8 7,976 / 17.4 (acceptance 59%/26% per position); +MTP-2 7,380 /
19.8 (71%/44%, token rate 57.4%). Deployed MTP-2: +51% decode. Both spec
arms pay ~55-59% of prefill. `num_speculative_tokens` beyond 2 unmeasured.
- **Measured numerics law:** spec arms do NOT reproduce the no-spec greedy
text (bf16 batched verification reorders reductions; near-tie argmaxes
cascade). vLLM spec decode is distribution-preserving, not
bitwise-greedy-preserving.
- **Client-contract delta wired:** vLLM emits `reasoning`, not
`reasoning_content` - `models.yml` frank-large block now sets
`reasoningContentField: "reasoning"`, and the extraBody moved to the
Qwen3.5-family recipe (0.7/0.8) with `chat_template_kwargs`
(a top-level `preserve_thinking` is ignored by vLLM).
- Deployer gap found pre-deploy: the spec-draft gate demanded a single
`model.safetensors` (the dflash layout) and would have rejected the
deployed MTP arm (4 shards behind an index); fixed to accept both
layouts, gated by bats. `z-lab/Qwen3.5-9B-DFlash`'s "vLLM PR #40898
unmerged" card claim is FALSE - `vllm/v1/spec_decode/dflash.py` ships in
0.30 (verified in-image); the drafter stays on disk as the alternative.
- Host state: +38 GiB fetched (MiMo BF16 17.53 GiB, Qwen3.5-9B 18 GiB,
DFlash 2.58 GiB), disk down to ~26 GiB free - reclaim pass due. gufo
rollback pinned at git tag `frank-large-gufo-q4kxl-20261001`; engine,
Q4_K_XL payload and DFlash2 drafter all remain on the host.
- First deploy attempt #2 crash-looped the container 51 times: the serve
script handed vLLM the HOST model path while the tree is mounted at
`/models` inside the container — transformers rejected it as a malformed
repo id. Fixed by converting to the container path (the spec draft was
already converted; the target was not), pinned by bats. Also fixed the
deployer's own draft gate (same single-file bug as the serve script's).
- Reclaim (Frank approved): Swift-1.5 Q8_K_XL payload (30 G, refetchable via
`scripts/download-frank-large-swift.sh`) and the orphaned flux-2-klein
tree under `models/checkpoints` (23 G; ComfyUI mounts
`comfyui-data/models`, not this) purged via
`~/.AGENTTRASH/20261001-frank-large-reclaim/` — 52 G freed. KEPT the
1.1 G `Qwen3.8-27B-DFlash2-Q4_K_M.gguf` (it is the gufo rollback's
drafter, not a remnant).
## 2026-10-02 — frank-large cutover: vLLM MiMo -> ROCmFPX Q8_0_ROCMFPX_AGENT + MTP
Frank's order was the highest quality of
`kingjones777/Qwen3.8-27B-ROCmFP4-STRIX-MTP-GGUF` on one full context, "whatever
runtime it requires". The answer is forced by the file: `Q8_0_ROCMFPX_AGENT.gguf`
carries tensor type 103 (`GGML_TYPE_Q8_0_ROCMFPX`, ftype 115), which stock
llama.cpp, gufo and every other loader on the fleet cannot read — only the
kingjones30/ROCmFPX fork can, so the runtime is pinned to commit
`36e9acd40e10a87cd3c3ef8ec734668757dc8520` and built by
`scripts/build-rocmfpx.sh`. Shape: 1 session x 262,144 (native), f16 KV, the
bundled BF16 mmproj, and MTP from the repo's own `mtp-Qwen3.8-27B-Q4_0.gguf`
(n-max 4, `--spec-draft-device ROCm0`).
- **MTP is the whole performance story: 17.0-17.1 t/s with, 7.60-7.66 without**
(+123 %), one session, temp 0, production stopped per arm, acceptance 0.462 /
mean length ~1.86, at an 8-15 % prefill tax (325-351 vs 381 t/s). The AGENT
routing variant was chosen over the card's plain Q8_0 because it keeps 187
output-head tensors at plain Q8_0 instead of 2, which measured MTP acceptance
0.953 vs 0.911.
- Steady GTT occupancy 63.1 GiB of the ~114 GiB aperture; boot to healthy 16 s.
- Rollback: git tag `frank-large-gufo-q4kxl-20261001`. The retired vLLM-era
fetchers moved to `old/`. Runbook
[[frank-large-rocmfpx-q8agent-mtp]].
## 2026-10-02 — frank-small: Q5_K_M, then three contexts + vision, sized by two boots
Three orders in one day on the same endpoint: `bartowski/…Q5_K_M` on llama.cpp
with two contexts ("whatever context size fits the 3090"), then **three
contexts** "as much as can fit while keeping overhead open space to 2-3gb on
the 3090", then **"frank-small should have vision"**.
- **Final shape: `CTX_SIZE=540672 PARALLEL=3` = 3 x 180,224**, f16 K + q8_0 V
under flash attention, `--mmproj` vision, all layers on the 3090. Measured
**21,684 MiB used / 2,441 MiB free** of 24,576 — inside the 2-3 GiB band.
- **The pool came from two boots, not a formula.** 2 x 262,144 with no
projector: 20,190 MiB used, KV 12,800 => non-KV **7,390 MiB**. 3 x 196,608
with the projector: 22,972 used, KV 14,113 => non-KV **8,859 MiB**. The
difference prices the vision tower at **~1.4 GiB for a 918 MB file** — the
encoder's own buffers ride with it. The first 3-slot deploy (3 x 196,608)
booted healthy but left only 1,153 MiB free, which is how the band got
violated and why the seam now prices non-KV at the measured 9 GiB and
REJECTS that shape.
- **Three contexts cost window, and that is the tradeoff Frank was told:**
180,224 tokens per conversation, not the native 262,144. A longer prompt is
a hard `400 exceed_context_size_error`, so `models.yml` sets
`contextWindow: 180224`. Consequence: frank-primary's 183,501-token
compaction request no longer fits here with summary room; the two-slot
rollback is the way back.
- Measured (2026-10-02, this shape): decode **106.8 t/s**, prefill **3,814
t/s** (~5 % faster decode than 2 x 262,144 — shorter slot, shorter attention
scan), three concurrent requests answered in parallel in 1.7 s with a fourth
queued at 3.0 s, native `tool_calls`, `reasoning_content` populated,
`reasoning_effort: low` accepted, solid-red PNG answered **"Red."**
- **Vision contract gotcha:** `/v1/chat/completions` ignores the legacy
top-level `images` field — that request answered "Brown." for the same red
image, i.e. it generated from text alone. Only the `image_url` content part
reaches the model. `/completion` accepts `images` but this build still
requires `messages`.
- Deployer gates on the projector too (`LLM_SMALL_MMPROJ`), so a missing
mmproj cannot silently ship a blind endpoint; `MMPROJ_FILE=` (explicitly
empty) in the env file is the documented text-only opt-out and returns ~1.4
GiB to KV.
- Reclaim staged, **not purged, awaiting approval**:
`~/.AGENTTRASH/20261002-retired-llm-payloads/` (~59 GiB of superseded
payloads). Kept in place for rollback: `MiMo-Q6K/`, `MiMo-Q5KM/`,
`Qwen3.8-27B-UD-Q4_K_XL/` and `Qwen3.8-27B-UD-Q8_K_XL/` (the latter holds the
gufo DFlash2 drafter). Runbook [[frank-small-llama-mimo-q5km]].
+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": "",
+150
View File
@@ -0,0 +1,150 @@
#!/usr/bin/env bats
# Seam: autoresearch measure client behavior.
#
# The measure client is the whole yardstick of the frank-primary speed
# session, so its METRIC arithmetic gets a behavior test: against a
# deterministic mock endpoint that emits a KNOWN number of completion
# tokens at a KNOWN per-token delay, the reported decode rate must land
# near the nominal rate, the usage accounting must come back exact, and an
# unhealthy endpoint must fail loudly (no half-measured numbers).
#
# The mock implements only what the client calls: POST
# /v1/messages/count_tokens (word count as the token count, which makes the
# client's words/token calibration come out to exactly 1.0) and a streaming
# POST /v1/chat/completions (one content chunk per completion token, then a
# usage chunk, then [DONE]).
load helpers
MEASURE="$REPO_ROOT/scripts/autoresearch/frank-primary-measure.py"
MOCK="$BATS_TEST_TMPDIR/mock.py"
PORT=""
MOCK_PID=""
setup() {
# Deterministic mock; argv: <port> <delay-seconds>; env MOCK_FAIL=1
# makes the chat endpoint answer 500.
cat >"$MOCK" <<'PYEOF'
import json, os, sys, time
from http.server import BaseHTTPRequestHandler, HTTPServer
PORT = int(sys.argv[1])
DELAY = float(sys.argv[2])
FAIL = os.environ.get("MOCK_FAIL", "0") == "1"
class Handler(BaseHTTPRequestHandler):
def log_message(self, *a):
pass
def _send(self, obj, code=200):
b = json.dumps(obj).encode()
self.send_response(code)
self.send_header("Content-Type", "application/json")
self.send_header("Content-Length", str(len(b)))
self.end_headers()
self.wfile.write(b)
def do_POST(self):
n = int(self.headers.get("Content-Length", "0"))
body = json.loads(self.rfile.read(n) or b"{}")
if self.path == "/v1/messages/count_tokens":
text = body["messages"][0]["content"]
self._send({"input_tokens": max(1, len(text.split()))})
elif self.path == "/v1/chat/completions":
if FAIL:
self._send({"error": "engine down"}, 500)
return
max_tokens = int(body.get("max_tokens", 64))
self.send_response(200)
self.send_header("Content-Type", "text/event-stream")
self.end_headers()
for i in range(max_tokens):
ev = {"choices": [{"delta": {"content": "tok%d " % i}}]}
self.wfile.write(("data: %s\n\n" % json.dumps(ev)).encode())
self.wfile.flush()
time.sleep(DELAY)
prompt_words = max(1, len(body["messages"][0]["content"].split()))
ev = {"choices": [{"delta": {}}],
"usage": {"prompt_tokens": prompt_words,
"completion_tokens": max_tokens}}
self.wfile.write(("data: %s\n\n" % json.dumps(ev)).encode())
self.wfile.write(b"data: [DONE]\n\n")
self.wfile.flush()
else:
self._send({"error": "unknown path"}, 404)
HTTPServer(("127.0.0.1", PORT), Handler).serve_forever()
PYEOF
}
free_port() {
python3 -c 'import socket; s = socket.socket(); s.bind(("127.0.0.1", 0)); print(s.getsockname()[1]); s.close()'
}
start_mock() { # $1 = ok|fail
PORT="$(free_port)"
if [ "$1" = "fail" ]; then
MOCK_FAIL=1 python3 "$MOCK" "$PORT" 0.005 &
else
python3 "$MOCK" "$PORT" 0.005 &
fi
MOCK_PID=$!
local i
for i in $(seq 1 100); do
if python3 -c "import socket; socket.create_connection(('127.0.0.1', $PORT), 0.2).close()" 2>/dev/null; then
return 0
fi
sleep 0.1
done
echo "mock did not start" >&2
return 1
}
stop_mock() {
if [ -n "$MOCK_PID" ]; then
kill "$MOCK_PID" 2>/dev/null || true
wait "$MOCK_PID" 2>/dev/null || true
MOCK_PID=""
fi
}
@test "measure exists and compiles" {
[ -f "$MEASURE" ]
python3 -m py_compile "$MEASURE"
}
@test "measure computes decode rate and exact usage from a controlled endpoint" {
start_mock ok || return 1
run env AR_BASE="http://127.0.0.1:$PORT" AR_MODEL=mock python3 "$MEASURE"
stop_mock
[ "$status" -eq 0 ] || { echo "$output"; return 1; }
# run() merges stderr in; the contract is: exactly ONE json result line
# (the window script parses the same way), progress on stderr.
printf '%s\n' "$output" | python3 -c '
import json, sys
lines = [l for l in sys.stdin.read().splitlines() if l.startswith("{")]
assert len(lines) == 1, "expected exactly one JSON line, got %d" % len(lines)
d = json.loads(lines[0])
# nominal 200 t/s (0.005 s/chunk) minus small per-chunk overhead
for k in ("decode_tps", "decode_tps_115", "decode_tps_1056", "decode_tps_4096"):
v = d[k]
assert 60.0 <= v <= 320.0, "%s=%s outside [60, 320]" % (k, v)
# the mock emits exactly max_tokens completion tokens; the accounting must be exact
assert d["completion_tokens_4096"] == 256, d["completion_tokens_4096"]
assert d["completion_tokens_115"] == 256
# prompt sizing: calibration is exactly 1.0 words/token in the mock, so the
# measured prompt lengths equal the targets
assert d["prompt_tokens_115"] == 115
assert d["prompt_tokens_4096"] == 4096
print("measure claims verified")
'
}
@test "measure fails loudly on an unhealthy endpoint instead of half-measuring" {
start_mock fail || return 1
run env AR_BASE="http://127.0.0.1:$PORT" AR_MODEL=mock python3 "$MEASURE"
stop_mock
[ "$status" -ne 0 ]
! printf '%s\n' "$output" | grep -qE '^\{'
}
+242 -296
View File
@@ -1,334 +1,280 @@
#!/usr/bin/env bats
# Seam: the frank-large root unit on dankclaw.
# Seam: frank-large serves kingjones777's Qwen3.8-27B Q8_0_ROCMFPX_AGENT (a
# ftype-115 ROCmFPX file) with the repo's MTP draft head on the Strix Halo
# iGPU, via the ROCmFPX fork of llama.cpp — one session at the native
# 262,144 window.
#
# Since 2026-09-28 this endpoint is served by gufo (gufo-org/gufo), the
# Strix Halo inference engine built from the pinned v0.1.1 tag, serving
# Swift-1.5-Qwen3.8-27B-Uncensored (abliterated) UD-Q8_K_XL with the z-lab
# DFlash2 Q4_K_M drafter. Two changes landed on this endpoint that day: the
# engine (from the stock llama.cpp prebuilt) and the payload (from
# unsloth/Qwen3.8-27B-GGUF:UD-Q8_K_XL). Port, alias and client contract did
# not move.
# This seam exists because the format is the constraint: GGML_TYPE_Q8_0_ROCMFPX
# (tensor type 103) is understood by the ROCmFPX fork and by nothing else on
# this host, so the runtime, the payload and the deployer's gate have to agree
# on paths that no other endpoint uses. On 2026-10-01 a serve-script gate and
# its deployer twin disagreed during a cutover and the endpoint crash-looped;
# both sides are pinned here.
#
# Most of this seam runs the serve script against a stub engine and asserts
# on the argv it actually execs, so what is pinned is the command the
# operator gets rather than the text of the script: a tunable renamed,
# dropped, or silently defaulted away fails here the way it would fail a
# deployment.
load helpers
ENV_FILE="$REPO_ROOT/scripts/frank-large.env"
UNIT="$REPO_ROOT/scripts/frank-large.service"
SERVE="$REPO_ROOT/scripts/serve-frank-large.sh"
FETCH="$REPO_ROOT/scripts/download-frank-large-swift.sh"
DRAFTER_FETCH="$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"
# Everything is tested from what an operator or a supervisor can observe — the
# command line, the exit code, the deployer's error text — never from anything
# inside llama.cpp.
setup() {
STAGE="$(mktemp -d)"
RUNTIME_DIR="$STAGE/gufo"
MODEL_DIR="$STAGE/models"
DRAFTER_DIR="$STAGE/draft"
mkdir -p "$RUNTIME_DIR/bin" "$MODEL_DIR" "$DRAFTER_DIR"
# A stub engine: the serve script execs it, so $@ is exactly what gufo
# would be invoked with.
cat > "$RUNTIME_DIR/bin/gufo" <<'STUB'
#!/usr/bin/env bash
printf '%s\n' "$@"
STUB
chmod +x "$RUNTIME_DIR/bin/gufo"
# The target and the drafter live in SEPARATE directories since the
# 2026-09-28 payload swap: the target came from a different repository,
# the DFlash2 drafter did not move. A stub that colocated them would
# never notice DRAFTER_DIR going stale.
: > "$MODEL_DIR/$TARGET_STUB"
: > "$DRAFTER_DIR/Qwen3.8-27B-DFlash2-Q4_K_M.gguf"
STUB_ENV="$STAGE/stub.env"
cat > "$STUB_ENV" <<EOF
RUNTIME_DIR=$RUNTIME_DIR
MODEL_DIR=$MODEL_DIR
DRAFTER_DIR=$DRAFTER_DIR
EOF
load helpers
SERVE="$REPO_ROOT/scripts/serve-frank-large.sh"
UNIT="$REPO_ROOT/scripts/frank-large.service"
ENV_FILE="$REPO_ROOT/scripts/frank-large.env"
DEPLOYER="$REPO_ROOT/scripts/deploy-remote.sh"
BUILD="$REPO_ROOT/scripts/build-rocmfpx.sh"
RUNTIME_STUB="/home/dank/GitPackages/kingjones-ROCmFPX/build/bin/llama-server"
MODEL_STUB="/home/dank/models/kingjones-Qwen3.8-27B-ROCmFP4-STRIX-MTP/Qwen3.8-27B-Q8_0_ROCMFPX_AGENT.gguf"
DRAFT_STUB="/home/dank/models/kingjones-Qwen3.8-27B-ROCmFP4-STRIX-MTP/mtp-Qwen3.8-27B-Q4_0.gguf"
MMPROJ_STUB="/home/dank/models/kingjones-Qwen3.8-27B-ROCmFP4-STRIX-MTP/mmproj-Qwen3.8-27B-BF16.gguf"
TEST_TMP="$(mktemp -d)"
SRC="$TEST_TMP/src"
mkdir -p "$SRC"
git -C "$SRC" init -q
git -C "$SRC" -c user.email=t -c user.name=t commit -q --allow-empty -m x
}
teardown() {
if [ -n "${STAGE:-}" ]; then
rm -rf "$STAGE"
fi
rm -rf "$TEST_TMP"
}
# serve_argv [env-file] — run the serve script and capture the engine's argv,
# one token per line, in $output. No argument exercises the built-in defaults
# with the stub's paths.
serve_argv() {
local envfile="${1:-$STUB_ENV}"
if [ -n "$envfile" ]; then
FRANK_LARGE_ENV_FILE="$envfile" run bash "$SERVE"
else
run env FRANK_LARGE_ENV_FILE="$STAGE/absent.env" bash "$SERVE"
fi
# make_stub — an executable that prints its whole argv on one line, so
# "what command line would the supervisor run" is observable output.
make_stub() {
cat > "$TEST_TMP/bin" <<'STUB'
#!/bin/sh
printf '%s\n' "$*"
STUB
chmod +x "$TEST_TMP/bin"
}
# argv_has <token> — exact token match, so --port never satisfies a test
# looking for a different flag.
argv_has() {
grep -qxF -- "$1" <<<"$output"
@test "the env file defines the deployment values" {
grep -qE '^LLAMA_BIN=/' "$ENV_FILE"
grep -qE '^MODEL_FILE=/' "$ENV_FILE"
grep -qE '^DRAFT_FILE=/' "$ENV_FILE"
grep -qE '^ALIAS=[a-z0-9-]+$' "$ENV_FILE"
grep -qE '^LISTEN_PORT=[0-9]+$' "$ENV_FILE"
grep -qE '^CTX_SIZE=[0-9]+$' "$ENV_FILE"
}
# argv_value <flag> — the token following <flag>, empty if the flag is absent.
argv_value() {
local i
i="$(grep -nx -- "$1" <<<"$output" | cut -d: -f1)"
[ -n "$i" ] || return 0
sed -n "$((i + 1))p" <<<"$output"
}
@test "the frank-large unit, env, serve and build files exist where the deployer installs them from" {
[ -f "$ENV_FILE" ]
[ -f "$UNIT" ]
[ -x "$SERVE" ]
[ -x "$BUILD" ]
}
@test "frank-large is boot-persistent, self-healing and unprivileged" {
grep -q '^WantedBy=multi-user.target$' "$UNIT"
grep -q '^Restart=on-failure$' "$UNIT"
grep -q '^RestartSec=' "$UNIT"
grep -q '^User=dank$' "$UNIT"
# The engine pins buffers; the memlock budget must be unbounded or the
# load fails on the RLIMIT.
grep -q '^LimitMEMLOCK=infinity$' "$UNIT"
# The unit runs the repo's own serve script with the repo's env.
grep -q 'ExecStart=/home/dank/serverAppConfigs/scripts/serve-frank-large.sh' "$UNIT"
grep -q 'FRANK_LARGE_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-large.env' "$UNIT"
}
@test "the fleet endpoint and alias survive the cutover" {
serve_argv
[ "$status" -eq 0 ]
# frank-large at :7770, whatever engine answers it.
[ "$(argv_value --served-model-name)" = "frank-large" ]
[ "$(argv_value --port)" = "7770" ]
[ "$(argv_value --host)" = "0.0.0.0" ]
}
@test "the built-in defaults are one session of the full 262144 window with DFlash2" {
serve_argv
[ "$status" -eq 0 ]
# 262144 is the model's native window (the operator's call, 2026-09-21).
[ "$(argv_value --context)" -eq 262144 ]
# One session is the single stream every prior frank-large served.
[ "$(argv_value --sessions)" -eq 1 ]
[ "$(argv_value --speculative)" = "dflash2" ]
# A draft ceiling of 0 would silently serve the autoregressive rate.
[ "$(argv_value --draft-tokens)" -gt 0 ]
}
@test "the shipped env file, not just the defaults, serves the deployed shape" {
# The defaults are a floor; systemd sources the env file. Only the
# on-host paths are redirected at the stub, so every fleet value in the
# shipped file is the one under test. MODEL_FILE and DRAFTER_FILE are
# absolute in the shipped file, so they need redirecting too — a sed that
# only rewrote MODEL_DIR would leave them pointing at /home/dank and the
# test would pass for the wrong reason (or fail on a box that has them).
sed -e "s#^RUNTIME_DIR=.*#RUNTIME_DIR=$RUNTIME_DIR#" \
-e "s#^MODEL_DIR=.*#MODEL_DIR=$MODEL_DIR#" \
-e "s#^MODEL_FILE=.*#MODEL_FILE=$MODEL_DIR/$TARGET_STUB#" \
-e "s#^DRAFTER_DIR=.*#DRAFTER_DIR=$DRAFTER_DIR#" \
-e "s#^DRAFTER_FILE=.*#DRAFTER_FILE=$DRAFTER_DIR/Qwen3.8-27B-DFlash2-Q4_K_M.gguf#" \
"$ENV_FILE" > "$STAGE/shipped.env"
serve_argv "$STAGE/shipped.env"
[ "$status" -eq 0 ]
[ "$(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 ]
[ "$(argv_value --speculative)" = "dflash2" ]
[ "$(argv_value --draft-tokens)" -gt 0 ]
[ "$(argv_value --draft-policy)" = "adaptive" ]
# The shipped file must name the target the fleet actually serves, not a
# path that merely happens to exist.
[ "$(argv_value --model)" = "$MODEL_DIR/$TARGET_STUB" ]
[ "$(argv_value --dflash-model)" = "$DRAFTER_DIR/Qwen3.8-27B-DFlash2-Q4_K_M.gguf" ]
}
@test "the engine is pointed at the payload that is actually on disk" {
serve_argv
[ "$status" -eq 0 ]
[ -f "$(argv_value --model)" ]
# A drafter path that does not exist would load the target and decode at
# the autoregressive rate, which reads as "the new runtime is slow".
[ -f "$(argv_value --dflash-model)" ]
[ "$(argv_value --model)" != "$(argv_value --dflash-model)" ]
}
@test "frank-large stays text-only" {
# The payload has no mmproj, so an --mmproj would point at nothing. The
# fleet's image path is frank-small; models.yml declares frank-large
# text-only.
serve_argv
! argv_has --mmproj
grep -q -- '--mmproj' "$REPO_ROOT/scripts/serve-frank-small.sh"
}
@test "the engine is asked for greedy decoding and for preserved prior reasoning" {
# Greedy is what this endpoint has always served; a silent switch to
# sampled output would be a model-behaviour change disguised as a
# runtime swap. Prior thinking blocks must survive across turns or a
# multi-turn agent loses its own reasoning between tool calls.
serve_argv
[ "$(argv_value --temperature)" = "0" ]
[ "$(argv_value --preserve-thinking)" = "on" ]
}
@test "the serve script refuses a missing runtime with the build pointer" {
rm -f "$RUNTIME_DIR/bin/gufo"
serve_argv
@test "the serve script fails when the runtime is missing" {
# Only the model, the head and the projector exist; the fork was never
# built. llama.cpp is not reached, so this fails fast and says what to
# run instead of failing at bind time.
touch "$TEST_TMP/model.gguf" "$TEST_TMP/draft.gguf" "$TEST_TMP/mmproj.gguf"
run env "LLAMA_BIN=$TEST_TMP/nope/llama-server" \
"MODEL_FILE=$TEST_TMP/model.gguf" "DRAFT_FILE=$TEST_TMP/draft.gguf" \
"MMPROJ_FILE=$TEST_TMP/mmproj.gguf" "$SERVE"
[ "$status" -ne 0 ]
[[ "$output" == *"runtime not found"* ]]
[[ "$output" == *"build-gufo.sh"* ]]
# A restart loop would be the alternative; nothing may be exec'd.
! argv_has serve
[[ "$output" == *"build it with scripts/build-rocmfpx.sh"* ]]
}
@test "the serve script refuses a missing drafter with a fetch pointer" {
# The drafter lives in its own directory now, so the target can be present
# and this still has to be caught.
rm -f "$DRAFTER_DIR/Qwen3.8-27B-DFlash2-Q4_K_M.gguf"
serve_argv
@test "the serve script refuses to start without the model file" {
make_stub
touch "$TEST_TMP/draft.gguf" "$TEST_TMP/mmproj.gguf"
run env "LLAMA_BIN=$TEST_TMP/bin" "MODEL_FILE=$TEST_TMP/absent.gguf" \
"DRAFT_FILE=$TEST_TMP/draft.gguf" "MMPROJ_FILE=$TEST_TMP/mmproj.gguf" "$SERVE"
[ "$status" -ne 0 ]
[[ "$output" == *"missing asset"* ]]
[[ "$output" == *"Qwen3.8-27B-DFlash2-Q4_K_M.gguf"* ]]
[[ "$output" == *"download-frank-large"* ]]
! argv_has serve
[[ "$output" == *"is not readable"* ]]
[[ "$output" == *"download-frank-large-kingjones.sh"* ]]
}
@test "the serve script refuses a missing target and names the file" {
rm -f "$MODEL_DIR/$TARGET_STUB"
serve_argv
@test "the serve script refuses to start without the MTP draft head" {
make_stub
touch "$TEST_TMP/model.gguf" "$TEST_TMP/mmproj.gguf"
run env "LLAMA_BIN=$TEST_TMP/bin" "MODEL_FILE=$TEST_TMP/model.gguf" \
"DRAFT_FILE=$TEST_TMP/absent.gguf" "MMPROJ_FILE=$TEST_TMP/mmproj.gguf" "$SERVE"
[ "$status" -ne 0 ]
[[ "$output" == *"missing asset"* ]]
[[ "$output" == *"$TARGET_STUB"* ]]
[[ "$output" == *"MTP draft head"* ]]
}
@test "both payload files are fetched resumably and verified against declared sizes + sha256" {
# The target and the drafter come from DIFFERENT repositories, fetched by
# two scripts. Anchor the repo checks to the URL ASSIGNMENT, not to the
# file: the same repo string also appears in each script's header comment,
# so a plain grep stayed green after the URL was repointed at another
# repository -- the script would then download something the serve script
# never asked for.
grep -qE '^URL="https://huggingface\.co/ajgazin/Swift-1\.5-Qwen3\.8-27B-Uncensored-Dynamic-MTP-GGUF/resolve/main/' "$FETCH"
grep -qE 'https://huggingface\.co/z-lab/Qwen3\.8-27B-DFlash2-GGUF/resolve/main/' "$DRAFTER_FETCH"
for f in "$FETCH" "$DRAFTER_FETCH"; do
# -f so an HTTP error is a failure rather than a small "artifact";
# -C - so an interrupted 29 GiB run resumes.
grep -q -- '-fL -C -' "$f"
# The size and the sha256 are compared after the transfer, not trusted.
grep -q 'SHA256 MISMATCH' "$f"
grep -q 'SIZE MISMATCH' "$f"
@test "the serve script refuses a missing mmproj unless vision is opted out" {
make_stub
touch "$TEST_TMP/model.gguf" "$TEST_TMP/draft.gguf"
run env "LLAMA_BIN=$TEST_TMP/bin" "MODEL_FILE=$TEST_TMP/model.gguf" \
"DRAFT_FILE=$TEST_TMP/draft.gguf" "MMPROJ_FILE=$TEST_TMP/absent.gguf" "$SERVE"
[ "$status" -ne 0 ]
[[ "$output" == *"set MMPROJ_FILE='' for text-only"* ]]
# The documented opt-out must actually start, without a --mmproj argument.
run env "LLAMA_BIN=$TEST_TMP/bin" "MODEL_FILE=$TEST_TMP/model.gguf" \
"DRAFT_FILE=$TEST_TMP/draft.gguf" "MMPROJ_FILE=" "$SERVE"
[ "$status" -eq 0 ]
[[ "$output" != *"--mmproj"* ]]
}
@test "the serve script fails when LLAMA_BIN is empty" {
touch "$TEST_TMP/model.gguf" "$TEST_TMP/draft.gguf" "$TEST_TMP/mmproj.gguf"
run env LLAMA_BIN= "MODEL_FILE=$TEST_TMP/model.gguf" \
"DRAFT_FILE=$TEST_TMP/draft.gguf" "MMPROJ_FILE=$TEST_TMP/mmproj.gguf" "$SERVE"
[ "$status" -ne 0 ]
[[ "$output" == *"LLAMA_BIN is empty"* ]]
}
@test "the shipped env points at the ROCmFPX runtime and the AGENT payload" {
grep -qE "^LLAMA_BIN=$RUNTIME_STUB$" "$ENV_FILE"
grep -qE "^MODEL_FILE=$MODEL_STUB$" "$ENV_FILE"
grep -qE "^DRAFT_FILE=$DRAFT_STUB$" "$ENV_FILE"
grep -qE "^MMPROJ_FILE=$MMPROJ_STUB$" "$ENV_FILE"
# HIP reads bare HOST/TEMP/GPU_MAX_HEAP_SIZE out of the environment that
# `set -a` creates; a tunable named HOST leaks into the runtime.
! grep -qE '^(HOST|TEMP|GPU_MAX_HEAP_SIZE)=' "$ENV_FILE"
}
@test "the argv contract keeps the fleet's port and alias" {
make_stub
touch "$TEST_TMP/model.gguf" "$TEST_TMP/draft.gguf" "$TEST_TMP/mmproj.gguf"
run env "LLAMA_BIN=$TEST_TMP/bin" "MODEL_FILE=$TEST_TMP/model.gguf" \
"DRAFT_FILE=$TEST_TMP/draft.gguf" "MMPROJ_FILE=$TEST_TMP/mmproj.gguf" \
ALIAS=frank-large BIND_ADDR=127.0.0.1 LISTEN_PORT=7770 "$SERVE"
[ "$status" -eq 0 ]
# The caller's values must survive the env file, or a single-run operator
# override silently does nothing.
[[ "$output" == *"--host 127.0.0.1"* ]]
[[ "$output" == *"--port 7770"* ]]
[[ "$output" == *"--alias frank-large"* ]]
# Vision is wired: the projector is the whole vision tower.
[[ "$output" == *"--mmproj $TEST_TMP/mmproj.gguf"* ]]
}
@test "the shipped argv is one full native window on one session" {
grep -qE '^CTX_SIZE=262144$' "$ENV_FILE"
grep -qE '^PARALLEL=1$' "$ENV_FILE"
# 262144 IS the model's trained window (general.context_length in the
# GGUF), so 1 slot gets the whole thing — no truncation, no yarn scaling.
#
# Budget, from the GGUF header: 26.28 GiB of weights + 1.57 GiB draft head
# + 0.87 GiB projector + 16 full-attention layers x 4 kv heads x 256 dim x
# 2 (K+V) x 2 B = 64 KiB/token of f16 KV (~16 GiB at 262,144) + ~0.14 GiB
# of DeltaNet state + a couple GiB of compute buffers, against the iGPU's
# ~114 GiB GTT aperture. Change CTX_SIZE and this arithmetic, not a boot
# log, is what tells you it no longer fits.
ctx="$(sed -nE 's/^CTX_SIZE=([0-9]+)$/\1/p' "$ENV_FILE")"
kv_gib=$((ctx * 65536 / 1073741824))
total_gib=$((27 + 2 + 1 + kv_gib + 3))
[ "$total_gib" -le 114 ]
}
@test "the MTP draft contract matches the model card's measured optimum" {
make_stub
touch "$TEST_TMP/model.gguf" "$TEST_TMP/draft.gguf" "$TEST_TMP/mmproj.gguf"
run env "LLAMA_BIN=$TEST_TMP/bin" "MODEL_FILE=$TEST_TMP/model.gguf" \
"DRAFT_FILE=$TEST_TMP/draft.gguf" "MMPROJ_FILE=$TEST_TMP/mmproj.gguf" "$SERVE"
[ "$status" -eq 0 ]
# The head is the model's own nextn layer, loaded as a separate draft
# model because this checkpoint ships it standalone (no blk.<n>.nextn.*
# tensors in the target file).
[[ "$output" == *"--spec-type draft-mtp"* ]]
[[ "$output" == *"--model-draft $TEST_TMP/draft.gguf"* ]]
# n-max 4 is the measured optimum; n-max 8 measured WORSE (acceptance
# fell to 0.757 and the extra verification cost outran the savings), so
# the flag is a measurement, not a wish.
[[ "$output" == *"--spec-draft-n-max 4"* ]]
[[ "$output" == *"--spec-draft-n-min 0"* ]]
[[ "$output" == *"--spec-draft-p-min 0.0"* ]]
# The draft runs on the iGPU beside the target: no device-to-device hop
# on a link that measures single-digit GB/s.
[[ "$output" == *"--spec-draft-device ROCm0"* ]]
[[ "$output" == *"--spec-draft-ngl 99"* ]]
}
@test "KV and placement stay unquantized with flash attention on" {
make_stub
touch "$TEST_TMP/model.gguf" "$TEST_TMP/draft.gguf" "$TEST_TMP/mmproj.gguf"
run env "LLAMA_BIN=$TEST_TMP/bin" "MODEL_FILE=$TEST_TMP/model.gguf" \
"DRAFT_FILE=$TEST_TMP/draft.gguf" "MMPROJ_FILE=$TEST_TMP/mmproj.gguf" "$SERVE"
[ "$status" -eq 0 ]
[[ "$output" == *"--cache-type-k f16"* ]]
[[ "$output" == *"--cache-type-v f16"* ]]
# ROCmFPx quantized KV has no kernel on this branch, and the endpoint has
# the aperture to keep KV unquantized anyway.
[[ "$output" == *"--flash-attn on"* ]]
# --fit's placement heuristics do not know that 311 tensors of type 103
# belong on the iGPU, so the whole stack is placed explicitly instead.
[[ "$output" == *"--fit off"* ]]
[[ "$output" == *"--n-gpu-layers 999"* ]]
}
@test "the client contract wires thinking and template kwargs" {
make_stub
touch "$TEST_TMP/model.gguf" "$TEST_TMP/draft.gguf" "$TEST_TMP/mmproj.gguf"
run env "LLAMA_BIN=$TEST_TMP/bin" "MODEL_FILE=$TEST_TMP/model.gguf" \
"DRAFT_FILE=$TEST_TMP/draft.gguf" "MMPROJ_FILE=$TEST_TMP/mmproj.gguf" "$SERVE"
[ "$status" -eq 0 ]
# Without --jinja, llama.cpp silently ignores the harness's
# chat_template_kwargs, so thinking control disappears from the API.
[[ "$output" == *"--jinja"* ]]
# The harness reads `reasoning_content` for this endpoint, which is what
# the deepseek emission format produces (vLLM's `reasoning` is not it).
[[ "$output" == *"--reasoning-format deepseek"* ]]
# The template needs an unbounded thinking budget.
[[ "$output" == *"--reasoning-budget -1"* ]]
}
@test "the deployer gates exactly the paths the serve script opens" {
# A gate that checks a different file than the engine opens is the
# 2026-10-01 crash-loop: deploy passed, the unit restart-looped. Read the
# engine's own paths out of the env file and require the deployer's
# defaults to name the same ones.
for pair in "LLAMA_BIN:LLM_LARGE_RUNTIME" \
"MODEL_FILE:LLM_LARGE_MODEL" \
"DRAFT_FILE:LLM_LARGE_DRAFT" \
"MMPROJ_FILE:LLM_LARGE_MMPROJ"; do
env_key="${pair%%:*}"
dep_key="${pair##*:}"
want="$(sed -nE "s|^${env_key}=(.*)\$|\1|p" "$ENV_FILE")"
[ -n "$want" ]
got="$(grep -oE "${dep_key}:-[^}]+" "$DEPLOYER" | head -1 | sed "s|^${dep_key}:-||")"
[ "$got" = "$want" ]
done
}
@test "the serve script and the fetch scripts agree on the payload filenames" {
# The serve script's MODEL_FILE and the fetch script's REL are two
# independent spellings of one filename, and a repo is not required to
# keep them in step: a re-upload under a new name, or an env edited
# without the fetch, leaves the endpoint unable to start with a
# "missing asset" that no test would have predicted. Bind them here.
local served fetched drafter_served drafter_fetched
served="$(basename "$(grep '^MODEL_FILE=' "$ENV_FILE" | cut -d= -f2-)")"
fetched="$(sed -n 's/^REL="\(.*\)"$/\1/p' "$FETCH")"
[ -n "$served" ]
[ "$served" = "$fetched" ]
drafter_served="$(basename "$(grep '^DRAFTER_FILE=' "$ENV_FILE" | cut -d= -f2-)")"
drafter_fetched="$(sed -n 's/^ *"\(Qwen3\.8-27B-DFlash2[^ ]*\.gguf\) .*/\1/p' "$DRAFTER_FETCH")"
[ -n "$drafter_served" ]
[ "$drafter_served" = "$drafter_fetched" ]
@test "the deployer points a missing runtime at the fork build script" {
grep -qE 'build it: bash scripts/build-rocmfpx\.sh' "$DEPLOYER"
grep -qE 'fetch it: bash scripts/download-frank-large-kingjones\.sh' "$DEPLOYER"
}
@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.
grep -q 'Qwen3.8-27B-UD-Q8_K_XL' "$DRAFTER_FETCH"
! grep -q 'DFlash2' "$FETCH"
@test "the stray-process sweep cannot take frank-small down with frank-large" {
# frank-small serves a different GGUF over llama-server on the SAME host.
# A sweep keyed on the binary name (`pkill -f llama-server`) would kill
# the 3090 endpoint too, so it is keyed on frank-large's own payload file.
grep -q "pkill -f 'Qwen3.8-27B-Q8_0_ROCMFPX_AGENT'" "$DEPLOYER"
! grep -qE "pkill -f 'llama-server'" "$DEPLOYER"
}
@test "the build script refuses a source tree that is not the pinned commit" {
# gufo ships no prebuilt Linux binaries, so the runtime is built here.
# A tag that moves under us would silently install different kernels
# under the same RUNTIME_DIR, so the pin is enforced, not documented.
local src="$STAGE/not-the-pinned-commit"
mkdir -p "$src"
git -C "$src" init -q
git -C "$src" -c user.email=t@t -c user.name=t commit -q --allow-empty -m drift
run env GUFO_SRC_DIR="$src" GUFO_PREFIX="$STAGE/absent-prefix" bash "$BUILD" --verify
# The pin is load-bearing: the older builds of this fork line segfault in
# ggml_compute_forward_set_rows on this exact payload. A runtime that
# differs from what was qualified must be heard about at deploy time.
wrong="$(git -C "$SRC" rev-parse HEAD)"
run env ROCMFPX_SRC_DIR="$SRC" ROCMFPX_COMMIT="ffff$wrong" \
"$BUILD" --verify
[ "$status" -ne 0 ]
[[ "$output" == *"GUFO_COMMIT mismatch"* ]]
[[ "$output" == *"ROCMFPX_COMMIT"*mismatch* ]]
}
@test "the build script reports a runtime that was never built" {
# --verify on a host with no install must say so rather than exit 0 on
# an empty check.
run env GUFO_SRC_DIR="$STAGE/no-source-tree" GUFO_PREFIX="$STAGE/absent-prefix" bash "$BUILD" --verify
[ "$status" -ne 0 ]
[[ "$output" == *"no gufo at"* ]]
@test "the build script pins a real commit and the gfx1151 target" {
grep -qE 'ROCMFPX_COMMIT=.*[0-9a-f]{40}' "$BUILD"
grep -qE 'GPU_TARGET=.*gfx1151' "$BUILD"
grep -qE 'DGPU_TARGETS=' "$BUILD"
# The webui asset fetch half-failed on this box and aborted the link at
# 98%; the build must not depend on it.
grep -qE 'DLLAMA_BUILD_WEBUI=OFF' "$BUILD"
}
@test "the deploy handler gates on the runtime, the payload and the port" {
grep -q 'relink_unit frank-large' "$REMOTE_DEPLOY"
grep -q 'systemctl enable frank-large.service' "$REMOTE_DEPLOY"
grep -q 'wait_port_free 7770' "$REMOTE_DEPLOY"
grep -q '127.0.0.1:7770/health' "$REMOTE_DEPLOY"
grep -q 'LLM_LARGE_RUNTIME' "$REMOTE_DEPLOY"
grep -q 'LLM_LARGE_MODEL' "$REMOTE_DEPLOY"
grep -q 'LLM_LARGE_DRAFT' "$REMOTE_DEPLOY"
@test "the deployed unit keeps the fleet's restart and boot-persistence shape" {
grep -qE '^Restart=(always|on-failure)$' "$UNIT"
grep -qE '^WantedBy=' "$UNIT"
grep -qE '^ExecStart=.*/serve-frank-large\.sh$' "$UNIT"
grep -qE '^User=dank$' "$UNIT"
# The payload is 26 GiB of mmap'd weights plus pinned staging buffers; an
# RLIMIT smaller than the pinned set fails the load in a way that looks
# like an engine crash.
grep -qE '^LimitMEMLOCK=infinity$' "$UNIT"
}
@test "the deploy handler will not stop a serving endpoint it cannot replace" {
# The runtime gate must be live (a real conditional on an executable
# path, not a branch that never fires) and it must return BEFORE the
# stop, or a host whose gufo was never built takes frank-large down on
# its way to reporting the failure.
local large gate bail stop
large="$(sed -n '/^deploy_llm_large() {/,/^}/p' "$REMOTE_DEPLOY")"
[[ "$large" == *'build-gufo.sh'* ]]
gate="$(grep -n 'if \[\[ ! -x "\$LLM_LARGE_RUNTIME" \]\]' <<<"$large" | head -1 | cut -d: -f1)"
stop="$(grep -n 'systemctl stop frank-large' <<<"$large" | head -1 | cut -d: -f1)"
[ -n "$gate" ]
[ -n "$stop" ]
bail="$(awk -v g="$gate" 'NR > g && /return 1/ { print NR; exit }' <<<"$large")"
[ -n "$bail" ]
[ "$bail" -lt "$stop" ]
}
@test "the stray-run sweep keys on the drafter and cannot take frank-small down" {
# The sweep used to key on the TARGET filename, which the 2026-09-28
# payload swap moved to a different repository. It would have stopped
# matching the live process, and a stray run would then hold 7770 past the
# port gate and fail the deploy. The drafter is the part that did NOT
# move, and every frank-large command line carries it via --dflash-model.
grep -q "pkill -f 'Qwen3.8-27B-DFlash2-Q4_K_M'" "$REMOTE_DEPLOY"
# frank-small serves a different GGUF on the 3090 with no DFlash2 drafter,
# so a binary-name sweep is the only thing that would endanger it.
local large
large="$(sed -n '/^deploy_llm_large() {/,/^}/p' "$REMOTE_DEPLOY")"
! grep -q 'pkill -x llama-server' <<<"$large"
! grep -q 'pkill -x gufo' <<<"$large"
}
@test "the deploy handler retires the halogen quadlet without deleting it" {
grep -q 'retire_halogen_large_quadlet' "$REMOTE_DEPLOY"
grep -q 'HOME/.AGENTTRASH' "$REMOTE_DEPLOY"
! grep -qE '(^|[^[:alnum:]_])rm (-[a-zA-Z]+ )?.*frank-large' "$REMOTE_DEPLOY"
# Nothing live ships for this endpoint as a container any more. The
# archived copy is host state in an ignored .AGENTTRASH — deliberately
# untracked, and present only in a primary checkout — so search the
# tracked tree, not the filesystem.
[ ! -e "$REPO_ROOT/dankclaw/frank-large/quadlet/frank-large.container" ]
! git -C "$REPO_ROOT" grep -q 'Image=.*halogen' -- dankclaw
@test "the unit points at no retired frank-large runtime path" {
# The host keeps every retired payload and build on disk, so a stale path
# in a unit still resolves — to a runtime nobody has measured in weeks.
! grep -qE 'GitPackages/(ROCmFPX-kairic|llama.cpp-ik_llama|llama-builds|ciru-orca)' "$UNIT"
! grep -q 'halogen' "$UNIT"
}
+147 -56
View File
@@ -2,25 +2,25 @@
# 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).
# 2026-10-02 correction of the 2026-10-01 BF16 cutover): 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 +43,22 @@ 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"
@@ -76,41 +91,94 @@ DOWNLOAD="$REPO_ROOT/scripts/download-frank-primary.sh"
}
@test "the qualified engine shape is in the env file" {
# 2026-09-29 boot probe: 200,000 x 3 seqs at fp8 KV, util 0.98, KV_BYTES
# 7.2 GiB PER RANK boots at "GPU KV cache size: 729,545 tokens" and
# reports max concurrency 3.65x for 200,000-token requests. KV_BYTES is
# PER RANK — sizing it to the global requirement OOMs the worker
# (measured twice: 16 GiB and 9 GiB both die with ~7.5 GiB free). So 4
# full-length 200k contexts do NOT fit: four clients share the ~730k
# token pool and each runs below 200k when all are deep.
grep -q '^FRANK_PRIMARY_MAXLEN=200000$' "$ENV_FILE"
grep -q '^FRANK_PRIMARY_SEQS=3$' "$ENV_FILE"
# 2026-10-01 night ladder (Frank's method), then a runtime-survivability
# correction, then Frank's 2026-10-02 decision to give the pool back to
# the expert arena. SEQS=3 bf16 topped out at 241664 (KV 732,359 / 3.03x);
# SEQS=6 fp8 does NOT fit (6 x 241664 asked 10.70 GiB against 9.18 GiB
# free); SEQS=5 fp8 x 262144 BOOTED (KV 1,350,182 / 5.15x) but left ~0
# bytes free at runtime and a real client request (995-token prompt with
# max_tokens=261149) killed the worker with `Tried to allocate 50.00 MiB
# ... 0 bytes free`. 200704 sits below the 241664 rung while leaving a
# full 2.95 GiB/rank to cut loose for the arena. UTIL stays 0.98
# (lowering it shrinks the engine's own budget instead of buying slack).
# FINAL (2026-10-02, Frank): TWO windows at 200704 with FP8 KV and a pool
# cut for the arena. fp8 costs 7,701 B/token (measured 6,138 attention +
# 1,563 mamba/side), so 2 x 200704 = 401,408 tokens needs 3.091e9 B;
# pinned at 3.15e9 (~405k tokens, ~44 MB margin). The arena is what
# remains — the planner sizes it AFTER the KV override — so the 6,248
# slots of the 6.1e9 shape become roughly 7,500 here.
grep -q '^FRANK_PRIMARY_MAXLEN=200704$' "$ENV_FILE"
grep -q '^FRANK_PRIMARY_SEQS=2$' "$ENV_FILE"
grep -q '^FRANK_PRIMARY_UTIL=0.98$' "$ENV_FILE"
grep -q '^FRANK_PRIMARY_KV_BYTES=7730934784$' "$ENV_FILE"
grep -q '^FRANK_PRIMARY_KV_BYTES=3150000000$' "$ENV_FILE"
grep -q '^FRANK_PRIMARY_MNBT=1024$' "$ENV_FILE"
grep -q '^FRANK_PRIMARY_KV_DTYPE=fp8$' "$ENV_FILE"
grep -q '^FRANK_PRIMARY_SPEC=4$' "$ENV_FILE"
# --expert-precise-memory is NOT set: with bf16 2 x 262144 it put the
# boot 0.13 GiB from the 31.86 GiB ceiling (arena 16.65 device-resident)
# and crash-looped at graph capture. The serve script keeps the opt-in
# flag; the smaller pool here is the arena it would have been paying for.
! grep -q '^FRANK_PRIMARY_PRECISE_MEMORY=' "$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=' "$ENV_FILE"
grep -q '^FRANK_PRIMARY_MODEL_SHARDS=131$' "$ENV_FILE"
}
@test "the pool is sized as the arena floor, not the context floor" {
# THE LAW this seam pins: the fork's expert planner sizes the arena
# AFTER the KV override, so every byte cut out of KV_BYTES becomes
# arena. A context-size change must move the pool with it, or the
# reduction buys nothing. 2 x 200704 = 401,408 tokens at fp8's 7,701
# B/token is 3.091e9 B; the pin is 3.15e9, ~44 MB of margin above the
# floor — the same convention the 6.1e9 shape used.
floor=$(awk -v n="401408" -v b="7701" 'BEGIN{printf "%.0f", n*b}')
[ "$floor" = "3091243008" ]
kv=$(grep '^FRANK_PRIMARY_KV_BYTES=' "$ENV_FILE" | cut -d= -f2)
[ "$kv" = "3150000000" ]
margin=$(( kv - floor ))
[ "$margin" -gt 40000000 ]
[ "$margin" -lt 100000000 ]
}
@test "the serve script wires the engine flags from the env" {
grep -q -- '--max-num-seqs "$FRANK_PRIMARY_SEQS"' "$SERVE"
grep -q -- '--max-model-len "$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 +193,51 @@ 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"' "$SERVE"
}
@test "MNBT is at Frank's 1024 with the arena intact" {
# MNBT 512 doubles TTFT at 4064 ctx (2.46 s vs 1.36 s); 1024-4096 are
# interchangeable on decode AND identical on arena (the sweep measured
# 6,499 slots at every rung <=4096); 12288 costs 2.5% plus arena.
# 1024 is the 2026-10-02 setting — the pool was cut to feed the expert
# arena, so the workspace floor matters more than it did at 2048: the
# arena budget is what is left, and 1024-4096 pay nothing for it.
grep -q '^FRANK_PRIMARY_MNBT=1024$' "$ENV_FILE"
grep -q -- '--max-num-batched-tokens "$FRANK_PRIMARY_MNBT"' "$SERVE"
}
@test "expert prefetch is absent BY LAW, not by omission" {
# Telemetry (2026-09-29): the prefetcher served 13,369 of 36,720
# prefetched slabs (36% precision) — roughly half the gather traffic was
+168 -75
View File
@@ -1,12 +1,13 @@
#!/usr/bin/env bats
# Seam: the frank-small mainline-llama.cpp root unit on dankclaw.
# frank-small is the RTX 3090 endpoint created on 2026-09-16, when frank-large
# went back to the halogen engine on the iGPU. This seam pins what the flags
# alone do not say: boot persistence for a NATIVE runtime (no generated quadlet
# is involved), the repo-relative paths the unit executes, the separate client
# port, the MTP contract (the head is a separate sidecar file loaded as the
# draft model, chained behind ngram-mod), the vision handoff from frank-large,
# and the KV budget: q8_0 quantized KV whose context --fit sizes to the card.
# Seam: the frank-small llama.cpp root unit on dankclaw.
# frank-small is the RTX 3090 endpoint; since 2026-10-01 night it serves
# bartowski/MiMo-V2.6-Distill-Qwen-9B-GGUF:Q5_K_M via a CUDA (sm_86) build of
# llama.cpp master, chosen for the ASYMMETRIC KV Frank asked for: K f16
# (unquantized) + V q8_0, which only llama.cpp exposes per-tensor. Since
# 2026-10-02 it runs THREE contexts and carries a vision projector, and the
# card must keep 2-3 GiB free. This seam runs the serve script against a stub
# engine and asserts on the argv it actually execs, so what is pinned is the
# command the operator gets.
load helpers
@@ -15,6 +16,52 @@ SERVE="$REPO_ROOT/scripts/serve-frank-small.sh"
ENV_FILE="$REPO_ROOT/scripts/frank-small.env"
REMOTE_DEPLOY="$REPO_ROOT/scripts/deploy-remote.sh"
ENV_LARGE="$REPO_ROOT/scripts/frank-large.env"
TARGET_STUB="MiMo-V2.6-Distill-Qwen-9B-Q5_K_M.gguf"
# Same basename as the shipped projector: the test env repoints it into $STAGE.
MM_STUB="mmproj-MiMo-V2.6-Distill-Qwen-9B-f16.gguf"
setup() {
STAGE="$(mktemp -d)"
RUNTIME_DIR="$STAGE/llama"
MODEL_DIR="$STAGE/models"
mkdir -p "$RUNTIME_DIR/bin" "$MODEL_DIR"
cat > "$RUNTIME_DIR/bin/llama-server" <<'STUB'
#!/usr/bin/env bash
printf '%s\n' "$@"
STUB
chmod +x "$RUNTIME_DIR/bin/llama-server" "$RUNTIME_DIR/bin" 2>/dev/null || chmod +x "$RUNTIME_DIR/bin/llama-server"
touch "$MODEL_DIR/$TARGET_STUB" "$MODEL_DIR/$MM_STUB"
}
teardown() {
rm -rf "$STAGE"
}
# serve_argv [env-file] — run the serve script and capture the engine's
# argv, one token per line, in $output.
serve_argv() {
local envf="${1:-$STAGE/test.env}"
local mmproj
mmproj="$(sed -nE 's/^MMPROJ_FILE=(.+)$/\1/p' "$ENV_FILE")"
cat > "$envf" <<EOF
LLAMA_BIN=$RUNTIME_DIR/bin/llama-server
MODEL_FILE=$MODEL_DIR/$TARGET_STUB
MMPROJ_FILE=$MODEL_DIR/${mmproj##*/}
ALIAS=frank-small
BIND_ADDR=0.0.0.0
LISTEN_PORT=7771
CTX_SIZE=$(sed -nE 's/^CTX_SIZE=([0-9]+)$/\1/p' "$ENV_FILE")
PARALLEL=$(sed -nE 's/^PARALLEL=([0-9]+)$/\1/p' "$ENV_FILE")
CACHE_TYPE_K=$(sed -nE 's/^CACHE_TYPE_K=(.+)$/\1/p' "$ENV_FILE")
CACHE_TYPE_V=$(sed -nE 's/^CACHE_TYPE_V=(.+)$/\1/p' "$ENV_FILE")
NGL=$(sed -nE 's/^NGL=([0-9]+)$/\1/p' "$ENV_FILE")
EOF
run env FRANK_SMALL_ENV_FILE="$envf" nvidia-modprobe=true bash "$SERVE"
}
argv_value() {
grep -A1 -xF -- "$1" <<<"$output" | tail -1
}
@test "frank-small unit, serve script and env exist in scripts/" {
[ -f "$UNIT" ]
@@ -28,94 +75,140 @@ ENV_LARGE="$REPO_ROOT/scripts/frank-large.env"
grep -q '^RestartSec=' "$UNIT"
grep -q '^User=dank$' "$UNIT"
grep -q '^LimitMEMLOCK=infinity$' "$UNIT"
}
@test "frank-small runs the repo's own serve script with the repo's env" {
grep -q '^ExecStart=/home/dank/serverAppConfigs/scripts/serve-frank-small.sh$' "$UNIT"
grep -q 'FRANK_SMALL_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-small.env' "$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 "the shipped env points at the llama.cpp runtime and the Q5_K_M GGUF" {
grep -qE '^LLAMA_BIN=/home/dank/GitPackages/llama-master/build-cuda/bin/llama-server$' "$ENV_FILE"
grep -qE "^MODEL_FILE=/home/dank/models/MiMo-Q5KM/$TARGET_STUB$" "$ENV_FILE"
}
@test "frank-small caps its CPU RAM cache below the build default" {
# Without the flag the 8192 MiB default returns and the env cap is a
# silent no-op; this memory-tight host needs the cap to hold.
grep -q -- '--cache-ram "$CACHE_RAM"' "$SERVE"
@test "the deployer gates on exactly the payload paths the env file ships" {
# Anti-drift: the deploy handler checks files by its own defaults. If
# those ever differ from what the unit actually loads, a green deploy
# would be gating on a file nobody reads — and a missing projector would
# ship a blind endpoint.
local env_v dep_v path pair
for pair in "MODEL_FILE LLM_SMALL_MODEL_FILE" "MMPROJ_FILE LLM_SMALL_MMPROJ"; do
read -r env_v dep_v <<<"$pair"
path="$(sed -nE "s/^${env_v}=(.+)\$/\1/p" "$ENV_FILE" | tail -1)"
[ -n "$path" ]
grep -qF -- "${dep_v}=\"\${${dep_v}:-${path}}\"" "$REMOTE_DEPLOY"
done
}
@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"' "$SERVE"
@test "the shipped env serves the fleet shape: three 180224-token contexts" {
serve_argv
[ "$status" -eq 0 ]
[ "$(argv_value --alias)" = "frank-small" ]
[ "$(argv_value --port)" = "7771" ]
[ "$(argv_value --host)" = "0.0.0.0" ]
[ "$(argv_value --model)" = "$MODEL_DIR/$TARGET_STUB" ]
[ "$(argv_value --n-gpu-layers)" -gt 0 ]
# llama.cpp divides --ctx-size across slots and a mamba hybrid cannot
# share one cache, so the observable contract is the per-slot window.
[ "$(argv_value --parallel)" -eq 3 ]
ctx="$(argv_value --ctx-size)"
par="$(argv_value --parallel)"
[ $((ctx % par)) -eq 0 ]
[ $((ctx / par)) -eq 180224 ]
[ $((ctx / par)) -le 262144 ]
}
@test "frank-small carries the fleet's image path, and only it" {
grep -q '^MMPROJ_PATH=.*mmproj-Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced-BF16\.gguf$' "$ENV_FILE"
grep -q -- '--mmproj "$MMPROJ_PATH"' "$SERVE"
! grep -q '^ENABLE_VISION=1$' "$ENV_LARGE"
@test "the KV contract is asymmetric: unquantized K, q8_0 V, flash-attn on" {
serve_argv
[ "$status" -eq 0 ]
[ "$(argv_value --cache-type-k)" = "f16" ]
[ "$(argv_value --cache-type-v)" = "q8_0" ]
# q8_0 on V only exists on the flash-attention path; without this flag
# pair the KV contract in the env file is a lie the engine never sees.
[ "$(argv_value --flash-attn)" = "on" ]
}
@test "frank-small's slot grid is full-window and fits the 24 GiB card" {
local parallel cache_k cache_v ctx fixed per_slot
parallel="$(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")"
@test "the KV budget leaves 2-3 GiB of the 3090 free" {
# Rate: K f16 (16 KiB/token) + V q8_0 (~8.5, budgeted 25 with slack).
# The non-KV half is MEASURED on this card on 2026-10-02: with the
# projector loaded the engine reported 22,972 MiB used against 14,113
# MiB of KV, so weights + vision tower + DeltaNet state + compute
# buffers + CUDA graphs = 8,859 MiB => 9 GiB. Two asserts, both about
# the output the operator sees: the pool must still fit with 2 GiB
# spare, and it must be large enough that 5 GiB spare is NOT reachable
# (an undersized pool is as wrong as an oversized one). Arithmetic, not
# a boot log: change CTX_SIZE and this bites before the deploy does —
# it rejects the 3 x 196,608 pool that measured only 1.1 GiB free. The
# same pool with f16 V (34 KiB/token) lands past the card, which is why
# the contract is asymmetric.
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
[ $((fixed + parallel * per_slot)) -le 24576 ]
# Quantized KV on CUDA needs the GGML_CUDA_FA_ALL_QUANTS build option,
# without which prefill collapses about 12x (see the CUDA lesson in
# AGENTS.md). The build-cuda tree must carry it.
grep -q '^FLASH_ATTN=on$' "$ENV_FILE"
kv_gib=$((ctx * 25 / 1048576))
[ $((kv_gib + 9 + 2)) -le 24 ]
[ $((kv_gib + 9 + 5)) -gt 24 ]
f16v_gib=$((ctx * 34 / 1048576))
[ $((f16v_gib + 9)) -gt 24 ]
}
@test "frank-small runs on its own port beside frank-large's" {
grep -q '^LISTEN_PORT=7771$' "$ENV_FILE"
grep -q '^ALIAS=frank-small$' "$ENV_FILE"
grep -q -- '--port "$LISTEN_PORT"' "$SERVE"
grep -q -- '--host "$BIND_ADDR"' "$SERVE"
# The two endpoints cannot share a port: frank-large holds 7770, this one
# 7771.
grep -q '^PORT=7770$' "$ENV_LARGE"
! grep -q '^PORT=7771$' "$ENV_LARGE"
@test "no speculative draft ships by default" {
# The qwen35 GGUF has no MTP tensors, and the cross-model DFlash draft
# is a measured decision the harness makes later, not a default.
! grep -q -- '--model-draft' "$SERVE"
! grep -q -- '--spec-type' "$SERVE"
! grep -q '^DRAFT' "$ENV_FILE"
}
@test "the deploy handler installs the root unit and refuses a missing model" {
@test "vision ships by default and MMPROJ_FILE empty opts out of the image path" {
# The Q5_K_M GGUF carries no `v.*` tensors, so the projector argument IS
# the vision capability: no flag, no eyes.
serve_argv
[ "$status" -eq 0 ]
[ "$(argv_value --mmproj)" = "$MODEL_DIR/$MM_STUB" ]
# The documented opt-out must reach the engine as ABSENCE of the flag,
# not as an argument pointing at an empty string.
sed -i 's|^MMPROJ_FILE=.*|MMPROJ_FILE=|' "$STAGE/test.env"
run env FRANK_SMALL_ENV_FILE="$STAGE/test.env" nvidia-modprobe=true bash "$SERVE"
[ "$status" -eq 0 ]
! grep -qxF -- '--mmproj' <<<"$output"
}
@test "the fleet reasoning contract survives the reslice to three contexts" {
serve_argv
[ "$status" -eq 0 ]
# deepseek format = thinking lands in reasoning_content, the field the
# harness reads on this endpoint; --jinja is what makes
# chat_template_kwargs reach the template at all.
[ "$(argv_value --reasoning-format)" = "deepseek" ]
argv_value --jinja >/dev/null
grep -qxF -- '--jinja' <<<"$output"
}
@test "the serve script refuses a missing runtime, GGUF or projector" {
rm -f "$MODEL_DIR/$MM_STUB"
serve_argv
[ "$status" -ne 0 ]
[[ "$output" == *"frank-small: missing"* ]]
rm -f "$RUNTIME_DIR/bin/llama-server"
serve_argv
[ "$status" -ne 0 ]
[[ "$output" == *"frank-small: missing"* ]]
}
@test "the deploy handler gates on binary, GGUF and projector, then MainPID-hardens health" {
grep -q 'deploy_llm_small' "$REMOTE_DEPLOY"
grep -q 'LLM_SMALL_RUNTIME' "$REMOTE_DEPLOY"
grep -q 'LLM_SMALL_MODEL_FILE' "$REMOTE_DEPLOY"
grep -q 'LLM_SMALL_MMPROJ' "$REMOTE_DEPLOY"
grep -q 'relink_unit frank-small' "$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' "$REMOTE_DEPLOY"
grep -q 'refusing to start a unit that cannot load' "$REMOTE_DEPLOY"
grep -q '127.0.0.1:7771/health' "$REMOTE_DEPLOY"
grep -q 'frank-small.service has no MainPID' "$REMOTE_DEPLOY"
}
@test "frank-small's serve script refuses to start on a half-finished download" {
grep -q 'frank-small: missing' "$SERVE"
@test "the two endpoints keep separate ports and the large handler never pkills llama-server" {
# frank-large's gufo sweep must not take down frank-small, whose
# process is llama-server on the SAME host since this swap.
grep -q '^LISTEN_PORT=7771$' "$ENV_FILE"
local large
large="$(sed -n '/^deploy_llm_large() {/,/^}/p' "$REMOTE_DEPLOY")"
! grep -q 'pkill -x llama-server' <<<"$large"
}