Frank
295d5784d3
Comments/docs only - no functional change. The live boot of c769ff2 reported:
GPU KV cache size: 398,658 tokens,
Maximum concurrency for 200,704 tokens per request: 1.99x
expert cache space 14.87 GiB / 6,496 slots of 2.344 MiB
The arena prediction (6,496) landed exactly; the concurrency prediction (2.04x)
did not, because the per-token KV price is SHAPE-DEPENDENT: 7,701 B/token at
MAXLEN 262144 (6.1e9 -> 792,069 tokens) but 7,892 at 200704 (3.146e9 ->
398,658). Never extrapolate a concurrency figure across geometries.
Also smoke-verified: three concurrent 67-token requests answered in parallel,
~4.1 s each - the 3 slots are real, and the pool admits 2 full-length.
111 lines
6.5 KiB
Bash
111 lines
6.5 KiB
Bash
# frank-primary.env — tcclaviger RDNA4 vLLM production config (dankserver :7770).
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#
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# 2026-10-02 shape D: fp8 KV, MAXLEN 200704 x SEQS 3, the KV pool cut to ~2
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# full-length contexts. The window shrinks from the native 262144 to 200704 and
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# the pool from 6.1e9 to 3.15e9; --max-num-seqs stays 3 because SEQS=2 CANNOT
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# boot this model (measured 2x2 below). Same digest-pinned tcclaviger RDNA4
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# fork. Rollback for the fp8+MTP4 era is git tag frank-primary-fp8-mtp-20261001.
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#
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# HIP reads bare env vars TEMP, HOST, GPU_MAX_HEAP_SIZE — every key here is
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# prefixed FRANK_PRIMARY_ so none can leak.
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#
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# --- runtime ----------------------------------------------------------------
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# Digest-pinned: the floating :latest tag moved once already. Local alias
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# qwen-fp8-runtime:tuned-20260929 (image ID 3322dbbbc96d) points at the same
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# bytes in rootless storage.
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FRANK_PRIMARY_IMAGE=docker.io/tcclaviger/vllm@sha256:da4029666668b90a0386c1ed23ea370c79916ad4e1a6ad1dd9db098b9fa069ea
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# --- payload ----------------------------------------------------------------
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FRANK_PRIMARY_MODEL_DIR=/home/dank/models/Qwen3.8-Flash-Next-Uncensored-FP8
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FRANK_PRIMARY_MODEL_SHARDS=131
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# --- identity ---------------------------------------------------------------
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# The harness models.yml id stays frank-primary (provider 192.168.0.235:7770).
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FRANK_PRIMARY_CONTAINER=frank-primary-qwen
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FRANK_PRIMARY_SERVED_NAME=frank-primary
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FRANK_PRIMARY_PUBLISH=7770:7770
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# Containers removed before every start: the retired R9V identity and the ad
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# hoc experiment identity (both hold the GPUs / name registrations).
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FRANK_PRIMARY_LEGACY_CONTAINERS="frank-primary-r9v qwen-fp8"
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# --- qualified engine shape (2026-10-02, shape D) ---------------------------
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# WHAT THE SLOT COUNT DOES AND DOES NOT DO. The endpoint advertises 3 slots
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# (SEQS 3), but the POOL, not the slot count, decides how many full-length
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# conversations are resident. MEASURED LIVE 2026-10-02 at this shape:
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# GPU KV cache size: 398,658 tokens,
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# Maximum concurrency for 200,704 tokens per request: 1.99x
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# (3,146,129,408 B reserved — 7,892 B/token). The per-token price is
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# SHAPE-DEPENDENT, not a constant: the 262144 shape priced at 7,701 B/token
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# (6,100,000,000 B -> 792,069 tokens), ~2.5% cheaper, so never extrapolate a
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# concurrency figure across geometries. Shorter requests use the spare blocks,
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# and a third LONG request queues rather than being refused. Verified: three
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# concurrent 67-token requests answered in parallel, ~4.1 s each.
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#
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# WHY NOT --max-num-seqs 2 (measured 2026-10-02, single-variable boot probes
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# against the then-deployed known-good shape, production stopped for each):
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# SEQS 2 + MNBT 1024 -> Engine core initialization failed
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# SEQS 2 + MNBT 2048 -> Engine core initialization failed
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# SEQS 3 + MNBT 1024 -> healthy (792,069 tokens, 3.02x, arena 6,248)
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# SEQS 3 + MNBT 2048 -> healthy (the deployed incumbent)
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# The failure is torch.fx ConstraintViolationError: query_start_loc.size()[0]
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# "marked dynamic but your code specialized it to be a constant (3)", raised
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# from AOT build_guards(strict_error=True) during profile_run -> _dummy_run.
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# model_runner.py sizes that input buffer max_num_reqs + 1 and _dummy_run sets
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# num_reqs = min(max_num_batched_tokens, max_num_reqs), so the width is
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# SEQS + 1 for ANY MNBT >= SEQS: 3 at SEQS 2, 4 at SEQS 3. MNBT only moves the
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# compile RANGE ((1,1024) vs (1,2048)) and cannot dodge it — the 2x2 above is
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# why MNBT is not a lever here. --enforce-eager bypasses the path but loses
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# CUDA graphs. Same failure class killed the 2026-10-01 bf16 2 x 262144 shape.
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#
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# THE ARENA LEVER IS max_model_len, NOT KV_BYTES (measured 2026-10-02). The
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# planner sizes expert cache as budget - non-expert - KV reserve - graphs -
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# overhead, and the KV reserve is registry-priced at 9190 B/token x max_model_len:
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# MAXLEN 262144 -> reserve 2.48 GiB -> arena 14.30 GiB / 6,248 slots
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# MAXLEN 200704 -> reserve 1.91 GiB -> arena 14.87 GiB / 6,496 slots
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# d(reserve) 0.57 GiB = d(arena) 0.57 GiB = +248 slots. The 6.1e9 -> 3.15e9
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# pool cut buys ZERO arena; it buys runtime HEADROOM (the shape it replaced
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# died with 0 bytes free on a real 995-token request). To grow the arena,
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# lower MAXLEN — not KV_BYTES.
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#
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# GATHER 32x64 stays: R4D_LRU_GATHER_CHUNKS=32 / R4D_LRU_GATHER_LANES=64
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# measured +18.7% decode vs default geometry and the win grows with depth.
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# Do not drop it.
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# MNBT 1024 is Frank's lock: MNBT 512 doubles TTFT at 4064 ctx (2.46 s vs
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# 1.36 s); 1024-4096 are interchangeable on decode; 12288 costs 2.5% and
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# arena. 1024 keeps the workspace floor so the arena stays max. (Side note
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# measured 2026-10-02: MNBT 2048 compiles the first graph in 26 s vs 172 s at
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# 1024 — a startup-cost lever, not a correctness one.)
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# PREFETCH IS ABSENT BY LAW: expert-cache telemetry measured the prefetcher at
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# 36% precision (36,720 slabs prefetched, 13,369 served) — roughly half the
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# gather traffic was waste. Never re-add --expert-prefetch without a fresh A/B.
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# TunableOp stays OFF: CLAV_TUNABLEOP_SWEEP silently skips under expert offload
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# unless CLAV_TUNABLEOP_WITH_OFFLOAD=1, and forcing it corrupts numerics.
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# --expert-precise-memory stays DROPPED: it crashed the 2 x 262144 bf16 boot
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# (0.13 GiB free of 31.86 GiB, NRestarts=3 at ~6.7 min each). It survives in
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# the serve script as an opt-in; re-enable only with a pool/context reduction
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# that pays for the 2.35 GiB it moves into the arena.
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FRANK_PRIMARY_MAXLEN=200704
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FRANK_PRIMARY_SEQS=3
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FRANK_PRIMARY_KV_BYTES=3150000000
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FRANK_PRIMARY_KV_DTYPE=fp8
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FRANK_PRIMARY_MNBT=1024
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FRANK_PRIMARY_GATHER_CHUNKS=32
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FRANK_PRIMARY_GATHER_LANES=64
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FRANK_PRIMARY_UTIL=0.98
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# --- client contract: reasoning split, tools, preserve_thinking ----------------
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# Without --reasoning-parser the engine leaves the thinking text INLINE in
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# `content` with a dangling `</think>` and a null `reasoning` field (measured
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# 2026-10-01: content = 'We need answer...Brief.\n</think>\n\n391') — the
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# malformed thinking block clients choke on. The qwen3 parser splits it
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# properly. The GLM rollback (d91379d) had dropped all three of these; the
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# working values are the ones ecaad36 shipped for this model.
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FRANK_PRIMARY_REASONING_PARSER=qwen3
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# Tools: --enable-auto-tool-choice + the qwen3_xml parser is what makes
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# tool_calls work here (without it, tool_choice auto returns 400).
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FRANK_PRIMARY_TOOL_PARSER=qwen3_xml
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# preserve_thinking keeps prior thinking blocks in the rendered prompt across
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# turns; enable_thinking makes thinking the server-side default. Verified the
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# payload's tokenizer_config template consumes both keys.
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FRANK_PRIMARY_CHAT_TEMPLATE_KWARGS='{"enable_thinking": true, "preserve_thinking": true}' |