The 2 x 200704 fp8 / MNBT 1024 shape (30904ba) crash-loops at boot: the
engine dies in determine_available_memory -> profile_run -> _dummy_run with
the SAME torch.compile dynamo constraint that killed the bf16 2 x 262144
shape on 2026-10-01:
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)'
Not an OOM. Restoring the last shape measured serving (fp8 3 x 262144 /
KV 6.1e9 / MNBT 2048 / arena 6,248) so the endpoint serves again; the
desired edits are re-applied one at a time from this base.
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
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.
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.
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.
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.
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.
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.
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.
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.
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).
DFlash2 experiment declared failed 2026-10-01: the drafter serves and
drafts (12.8 tok/s proposed) but acceptance is pinned at 1.0-1.38 on ALL
text classes including verbatim repetition — the aux-hidden-state capture
semantics are wrong (single-stream entering-state vs post-layer/comb is
the untested alternative). At ~1.2 acceptance the 8-token verify tax makes
decode 5x SLOWER than the 9.9-10.0 baseline (1.6-1.8 tok/s measured).
Restores the verified 37-40 tok/s shape: qwen3.8-flash-next FP8, MTP4,
prefetch off, 200k x 3 seqs, fp8 KV.
Payload: Intel/GLM-5.3-Flash-W4A16-AutoRound (AutoRound symmetric int4 group
128, auto_round:auto_gptq, 34 shards + 2 extras, 113,074 tensors, ~170 GiB).
It is the only W4A16 checkpoint this fork can serve with expert offload: its
quant_method "auto-round" is overridden to "inc", which routes the MoE to
libr4d's grouped W4A16 GEMM (R4dW4a16MoEMethod). A compressed-tensors W4A16
build of the same model resolves to TritonWNA16Experts, which has no offload
recipe, and refuses to serve at all (170 GiB of experts cannot fit 64 GiB of
VRAM, so offload is mandatory).
Shape: tcclaviger RDNA4 vLLM fork (same digest-pinned image as the 2026-09-29
qwen cutover), TP=2, 131,072 ctx x 2 seqs, bf16 KV (fp8 is ILLEGAL here — it
disables the sparse MLA backend's rope-free Triton path, the only MLA decode
gfx12 has), util 0.98, NBATCH 2048, --enable-expert-offload
--expert-precise-memory, prefix caching, glm47 tool + reasoning parsers,
MTP and expert prefetch absent by measurement.
Measured: decode 9.9-10.0 tok/s, prefill 918 tok/s (warm), arena 14.51 GiB =
2,383 slots/rank over 12,096 host-backed experts (73.64 GiB pinned/rank).
THE 35 tok/s TARGET IS NOT MET and the shortfall is measured: live telemetry
(R4D_LRU_TELEMETRY=1) gives a 0.53-0.66 per-layer hit rate, a step moves
0.82 GiB of misses in ~100 ms = 8.2 GB/s effective against a link measured at
22.74 GB/s — the same structural gather-path gap the qwen campaign found.
Growing the arena 13.08 -> 14.51 GiB changed decode by nothing.
Rejected by measurement: MTP4 (head loads, acceptance 3.76-4.90, but decode
unchanged and prefill collapses 918 -> 255 — a verification forward gathers the
union of the batch's experts), NBATCH 8192 (identical prefill).
Also: scripts/patches/gpu_worker-kv-cap.patch (fork-local fix for a KV-reserve
model that under-counts GLM's per-sequence KDA state; not needed by this shape),
runbook, AGENTS.md row + section, both indexes, work log.
Rollback: 2339fae (qwen FP8 + MTP4).
Unquoted value + set -a sourcing parses 'qwen-fp8' as a command ->
ExecStart exit 127 -> unit restart loop (caught on the first deploy).
The deployer's wait_for_health was killed and will re-run on the fresh
deploy.
Replace the R9V radiance fork with the tcclaviger RDNA4 vLLM stack (the
digest-pinned image the 2026-09-29 tuning campaign measured), serving
orcarouter/Qwen3.8-Flash-Next-Uncensored-FP8 (131 shards, 172.8 GiB,
already on disk) with MTP4 spec decode.
Qualified by boot probe on 2026-09-29:
- MAXLEN=200000 x SEQS=3 (600k total) at --kv-cache-dtype fp8 (q8/q8 KV):
'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: global 16G and 9G both OOM (worker tried to
allocate the full size; ~7.5 GiB/rank is the ceiling with the arena).
- prefetch OFF by law (telemetry: 36% precision, ~50% wasted traffic);
TunableOp off (corrupts numerics).
- decode at this shape: 42.94/34.55/36.09 tok/s; arena 6,032 slots.
Trio: frank-primary.env (all FRANK_PRIMARY_* keys), serve-frank-primary.sh
(direct podman run; entrypoint execs vllm serve; waits on the container),
frank-primary.service (root unit, same ExecStop law, new container name
frank-primary-qwen). Deployer gates rewritten (image digest + shard count
+ weight-map index). download-frank-primary.sh is now inventory/verify
(repo is GATED — 401 anonymous, masked LFS hashes; payload already on
disk). Seam rewritten for the new contract. Pre-cutover tag:
frank-primary-r9v-q8-20260929.
Replace the vLLM 0.30 UVA-offload wiring (never deployed; llama.cpp
b11030 endpoint replaced by Frank's order, downtime window open) with
the R9V radiance-vLLM shape on the same root unit:
- serve-frank-primary.sh: layer the on-host qualified setup state
(104 tuned R9V_* keys, /home/dank/r9v-state/uncensored/setup.json)
under repo production overrides, then exec the fork's own launcher
through the docker->podman shim and block on docker wait so a crashed
engine is a nonzero ExecStart (launch.sh --detach alone would fake
green). Gates: pinned image by OCI manifest digest in RepoDigests,
PLE at pinned byte count (stat -c %s), all GGUF shards + mmproj.
- frank-primary.env: thin production overrides only (LAN bind 0.0.0.0,
:7770, alias frank-primary, container frank-primary-r9v, GPU BDFs);
tuned engine shape stays in the setup state by design.
- frank-primary.service: same root-unit shape (User=dank,
LimitMEMLOCK=infinity for the tiered-expert pin), plus ExecStop
podman stop — docker wait cannot stop the container child.
- deploy-remote.sh deploy_llm_primary: state-driven gates (state ready,
image digest present in rootless storage, PLE bytes, shard files)
replace the fp030 shard-index gate; false-green MainPID check kept.
- tests/frank_primary_unit.bats: seam rewritten for the R9V shape.
The llama.cpp b11030 trio becomes the vLLM 0.30 trio ahead of the
FP8 cutover on :7770 — same port, same alias, no client moves.
Serve shape: locally built ROCm gfx1201 image
(localhost/frank-primary:vllm030) execs via podman as dank from the
root unit (LimitMEMLOCK=infinity legalizes the pin). UVA offload:
--offload-backend uva pins the PLE family (47.75 GiB, 138 tensors:
131 n-gram table shards + 7 per-layer conv/proj) + routed experts
(114.86 GiB, 150,528 tensors) in host RAM — 162.60 GiB combined,
~81.3 GiB per rank under TP=2, hence --cpu-offload-gb 82 (80/card
strands 2.6 GiB of experts on the cards). Parsers per the host's
own Ornith-era precedent: qwen3_xml tools + qwen3 reasoning (vLLM
0.30 emits the channel as `reasoning` — reasoning_content is
renamed server-side) + enable_thinking/preserve_thinking template
kwargs. Spec decode stays env-wired and OFF at bring-up.
Deployer deploy_llm_primary rewritten: image gate, index-driven
shard-count gate (131), stale-container cleanup, port wait, and the
false-green hardening — health is only green when the unit's own
MainPID is live behind the answer (2026-09-26 lesson).
Seam tests rewritten to the vLLM contract (15 gates): offload
arithmetic, parser wiring, no-llama.cpp-ism, deployer gates. Suite
349/349 green.
Blocks 0-4 on ROCm0 + 45-47 on ROCm1. This exact shape was probed and
battery-verified earlier the same session: card0 2.54 GiB free at boot,
2.11 GiB after the vision graph (steady under load), card1 unchanged
at ~3.3 GiB. Card1 cannot take another block (0.82 GiB would OOM the
vision graph + boot drift), so 5/3 is the physical limit at the
4x262144 / V-q8_0 shape. OT assertion pins the new value.
- CONTEXT_SIZE=1048576 / PARALLEL_SLOTS=4: four conversations, each the
full native 262144 window (per-slot window unchanged; slots divide
the pool, they never multiply it).
- CACHE_TYPE_V=q8_0 / CACHE_TYPE_K=f16: main KV drops 24,576 -> 18,816
B/token (-23.4%); the shared MTP drafter's KV ignores the V type
(measured: 2,048 MiB draft pool = the f16 law at 1,048,576 cells).
- OT_OVERRIDES: blocks 0-3 on ROCm0 and 45-47 on ROCm1 stay
GPU-resident (2.42/2.49 GiB per block, measured); the rest stay
CPU-computed. Measured free under load: ~4.9 GB card0 / ~3.4 GB
card1; a 5th block on card0 lands at 2.27 GB, under the 3 GB
checkpoint floor, so blocks are atomic and 4 is the safe fill.
- serve script: --cache-type-k/v env-wired tunables; ONE joined
--override-tensor flag (b11030 deprecates repeated flags, and the
loader is first-match-wins, so the specific patterns must precede
the broad exps=CPU sweep).
- seams: the window test asserts per-slot = 262144 at 4 slots; new
KV-type test; OT exact-value assertion pins the ordering law.
The shared MTP head borrows the main model output head, which a -ts 1,1
layer split places on ROCm1. With tensor overrides set, n_copies==1 in the
draft's scheduler, and a borrowed output.weight in a ROCm1 buffer aborts the
draft graph (ggml-backend.cpp:941) when the draft context is on ROCm0 —
the unit crash-looped 4x at ~12 s per attempt during the 2026-09-26 cutover.
Probed live on the host: ROCm0 aborts identically, ROCm1 loads and serves.
Discovery, not guesswork: dump the GGUF v3 headers of the fetched parts
(scripts/dump-gguf.py, added — a dependency-free reader that never
touches tensor data, so a 50 GiB part scans in milliseconds) before
the first load.
What the dump says (parts 2-3, 2026-09-26):
- The 51B-param PLE n-gram table is ONE tensor: per_layer_token_embd.
weight, dims [160, 320001536], Q8_0, 54.4 GiB — exactly the whole of
part 3. It is the same tensor the shared MTP head borrows, so the
=CPU override is required for placement AND for the draft load
(GPU-resident borrow: "invalid vector subscript").
- The model is qwen4exp, 512 experts, top-10 routing
(qwen4exp.ple.ngram_size=3, heads_per_ngram=8).
- Part 1 is metadata-only (ntensors=0); parts 2-6 carry tensors.
The placeholder pattern ngram_embeddings matched nothing — dropped from
OT_OVERRIDES (env, serve-script default, seam, AGENTS.md, runbook,
LLM index) before it could masquerade as a working override at load
time. Deployed set: exps=CPU,per_layer_token_embd.weight=CPU.
Suite: 346 green.
The 2026-09-26 same-day cutover that ended the Lucebox DS4.1 detour:
Dankserver's :7770 endpoint is now unsloth llama.cpp (the b11030-mix
prebuilt, ROCm gfx120X, bundled runtime) serving
unsloth/Qwen3.8-Flash-Next-GGUF at Q8_0 — 175.30 GiB across six sha256-
verified split parts — on both Radeon AI PRO R9700s, as a ROOT unit (the
frank-large shape: no container, no generated unit).
The deployed contract:
- Placement law: layer split -ts 1,1 with -ngl 999; the routed experts
and the 51B-param n-gram (PLE) table are COMPUTED in host RAM via
-ot exps=CPU,ngram_embeddings=CPU (the x4-pair measurement: streaming
over PCIe loses at 3.7 t/s, computing in RAM does not care).
per_layer_token_embd.weight=CPU is required by the shared MTP head's
borrow path (a GPU-resident borrow crashes the draft load).
mmap stays on; --cache-ram 16384.
- Spec chain draft-mtp,ngram-mod: the shared Q8_0 MTP head
(mtp-...-shared-Q8_0.gguf, 2,786,568,256 B) at depth 2, with the
draftless ngram-mod matcher chained behind it — the only legal way to
layer two spec implementations in one process.
- Vision explicit: --mmproj names the BF16 projector (this build never
autoloads; a server without it comes up healthy and text-only).
- Reasoning: --reasoning-format deepseek → reasoning_content; the
Qwen3.8 template's {xhigh, medium, low} reasoning_effort gate folded
by reasoningEffortMap in models.yml.
- One stream, the model's full 262,144 context; greedy server default
with Qwen-recommended sampling riding compat.extraBody.
The deployer's deploy_llm_primary is rewritten for the root unit: it
gates every artifact at its declared byte count (stat -c %s, never wc -c
— which read the whole 377 GiB lucebox file for minutes on 2026-09-26),
retires the lucebox user quadlet to dated home trash, waits out port
7770, relinks/enables/restarts the root unit and waits up to 1800 s for
/health. The quadlet-era tree under dankserver/frank-primary/ is
archived (dankserver/.AGENTTRASH/20260926-llamacpp-cutover/ on this
box; git history everywhere else) and its planner mapping replaced by
the scripts/ trio.
Observability flips back to the llamacpp namespace: a frank-primary
Prometheus job at 192.168.0.235:7770 (cross-host LAN — the netavark
published-port quirk that forces host.containers.internal for the two
Dankclaw endpoints is same-host only), the LlmEndpointDown runbook
text, and the dashboard description for three llama.cpp endpoints.
Docs: the new runbook (frank-primary-llamacpp-qwen38-flash-next-q8.md),
RETIRED banners on the lucebox and radiance runbooks and their index
entries, the AGENTS.md fleet section rewritten for the root-unit shape,
and the homepage frank-medium card renamed to frank-primary with the
Q8_0 Flash-Next spec (docs.html #models and the modality note updated:
images on frank-primary and frank-small, audio on frank-small only).
models.yml: the dankserver provider is "llamacpp (dankserver)" serving
frank-primary, contextWindow 262144, maxTokens 65536 (compaction-gap
law: 183,501 + 65,536 <= 262,144), input [text, image].
Suite: 346 green (frank_primary_unit.bats rewritten for the root unit —
16 tests pinning the placement law, the shared-head requirement, the
explicit projector, HIP env hygiene (BIND_HOST, never bare HOST), and
the deployer's byte-count gates; the quadlet-era planner and
changed-tests mappings rewritten for the trio; the observability scrape
test asserts three llamacpp jobs again).
Rollback: the lucebox image (localhost/lucebox-rocm:gfx1201) and the
378 GiB payload stay on the host; the Qwen payload stays fetched, so a
re-swap in either direction is a redeploy, not a refetch.
Frank
Comrade Chief Designer