Layout: GPU 0 = cyberprev (KV 16 -> 15 GiB, 1.29x), erp-seat (moved from GPU 1, KV 8.49 -> 5.5 GiB, 1.32x), voices (ctx 8,192 -> 40,960, its native maximum, KV 6 GiB, 1.07x), coder (moved from GPU 1, ctx 16,384 -> 32,768, the card maximum, 2.35x), parakeet-nemo. GPU 1 = gen-small (moved from GPU 0, 5.5 GiB, 1.76x), meromero-rp (22 GiB, 1.32x), intern-decision. Sizing rule: KV >= 1.25x max context rounded up to 0.5 GiB, checked against 7 days of LiteLLM traffic and the engines' own KV-usage logs. Each card keeps spare memory for its bursty tenant (parakeet's cap on GPU 0, intern-decision's 32k call on GPU 1). YaRN extensions are not enabled: they do not fit, and the Qwen cards warn static YaRN degrades short prompts. gen-small gets --override-generation-config max_new_tokens 32768. It applies only to requests that omit max_tokens (vLLM get_max_tokens) and answers 9 runaway ~260k-token replies in 7 days; the longest normal reply was 6,357. Applied with playbooks/fv-ml1-rebalance-20261005.yaml (boot-check guard and health/KV verification per seat); all nine seats healthy, gateway smoke tests pass.
123 lines
5.3 KiB
YAML
123 lines
5.3 KiB
YAML
# gen-small-seat — a fast, cheap "gen-small" seat: Qwen3.6-35B-A3B (3B active MoE),
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# Heretic-abliterated, on fv-ml1 GPU 1, :8026.
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#
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# WHY: a tiny-active (A3B = ~3B active of 35B total) gen tier for high-volume / low-latency
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# work, complementing the big gen seat (flash-next :8022). Operator-directed 2026-09-14.
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# "3.8 if possible, 3.6 if not" — there is NO general Qwen3.8 A3B (the 3.8 MoEs are
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# Flash-Next and the 2.4T), so this is the 3.6-35B-A3B fallback, which is the current-gen A3B.
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#
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# MODEL: /tank/aimodels/qwen36-35b-a3b-heretic-nvfp4 =
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# llmfan46/Qwen3.6-35B-A3B-uncensored-heretic-Native-MTP-Preserved-NVFP4-Experts-Only
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# - Heretic v1.3.0 (MPOA — Magnitude-Preserving Orthogonal Ablation), the operator's
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# house-favorite abliteration method: 88% fewer refusals (10/100 vs 83/100) at
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# 0.0015 KL divergence (quality preserved).
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# - modelopt NVFP4, experts-only (256 experts NVFP4; attn/shared-expert/linear_attn bf16).
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# - 19 MTP tensors preserved (native), so speculative decoding is available.
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# - hybrid arch (Qwen3_5MoeForConditionalGeneration): linear_attn (GDN) + attention +
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# MoE, native context 262144.
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#
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# ⚠ NVFP4 MoE serving: this is modelopt NVFP4 on the experts. If the NVFP4 MoE kernel
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# refuses ("does not support the deployment configuration ... kernel does not support
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# current device"), the erp-seat lesson applies (Marlin fallback) — but this is Blackwell
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# sm120 with native FP4, so it should take the native path. Read the boot log.
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#
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# ⚠ MTP on an A3B MoE is UNVERIFIED on this build — abliteration can desync an MTP head, and
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# MoE MTP has its own failure modes. GEN_SMALL_SPEC_CONFIG defaults to qwen3_5_mtp k=3;
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# gate it on a MEASURED acceptance (>=~40%) via a coherence + acceptance smoke, exactly as
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# cyberprev/flash-next were. To turn MTP off, delete the two --speculative-config lines.
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name: gen-small-seat
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services:
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vllm-gen-small:
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image: ${GEN_SMALL_IMAGE:-vllm/vllm-openai:nightly-e9d1398d9edfd90fcc1cf783805240e3effec013}
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container_name: ${GEN_SMALL_CONTAINER_NAME:-vllm-gen-small}
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restart: unless-stopped
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ipc: host
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ports:
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- "${GEN_SMALL_PORT:-8026}:8000"
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volumes:
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- /tank/aimodels/huggingface:/hfcache
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- ${GEN_SMALL_MODEL:-/tank/aimodels/qwen36-35b-a3b-heretic-nvfp4}:/model:ro
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environment:
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- VLLM_API_KEY=${API_KEY:-}
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- PYTORCH_CUDA_ALLOC_CONF=${GEN_SMALL_ALLOC_CONF:-}
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command:
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- /model
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- --served-model-name
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- ${GEN_SMALL_SERVED_NAME:-gen-small}
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- ${GEN_SMALL_SERVED_NAME_THINK:-gen-small-thinking}
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- --host
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- 0.0.0.0
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- --port
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- "8000"
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- --quantization
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- ${GEN_SMALL_QUANT:-modelopt_fp4}
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- --gpu-memory-utilization
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- "${GEN_SMALL_GPU_MEM_UTIL:-0.55}"
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# KV pinned in bytes — GPU 0 is shared with cyberprev, so an explicit KV budget
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# avoids the util-fraction fight between co-resident seats. fp8 KV + an A3B's small
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# attention footprint make this cheap; tuned to a sane concurrency band, not max.
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- --kv-cache-memory
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- "${GEN_SMALL_KV_CACHE_MEMORY:-5905580032}"
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# Default output cap (2026-10-05, Prime). A request that OMITS max_tokens stops at 32,768
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# instead of max_model_len - prompt; an explicit max_tokens still wins (vLLM get_max_tokens:
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# request value first, generation-config max_new_tokens only as the fallback). Reason: 9
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# runaway replies in 7 days, each ~260k tokens over 20+ min (albok-nemi, all-agents-local),
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# while the longest normal reply was 6,357 tokens.
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- --override-generation-config
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- '{"max_new_tokens": 32768}'
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- --max-model-len
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- "${GEN_SMALL_MAX_MODEL_LEN:-262144}"
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- --max-num-seqs
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- "${GEN_SMALL_MAX_NUM_SEQS:-16}"
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- --max-num-batched-tokens
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- "${GEN_SMALL_MAX_NUM_BATCHED_TOKENS:-4096}"
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- --trust-remote-code
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- --dtype
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- auto
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# Hybrid backbone carries linear_attn (GDN); its state wants float32.
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- --mamba-cache-dtype
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- float32
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- --kv-cache-dtype
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- ${GEN_SMALL_KV_CACHE_DTYPE:-fp8}
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- --enable-prefix-caching
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- --enable-chunked-prefill
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- --reasoning-parser
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- ${GEN_SMALL_REASONING_PARSER:-qwen3}
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- --default-chat-template-kwargs
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- '{"reasoning_effort": "${GEN_SMALL_REASONING_EFFORT:-medium}"}'
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- --enable-auto-tool-choice
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- --tool-call-parser
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- ${GEN_SMALL_TOOL_PARSER:-qwen3_xml}
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# MTP k=3 — verify acceptance on THIS build before trusting it (see header).
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- --speculative-config
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- '${GEN_SMALL_SPEC_CONFIG:-{"method": "qwen3_5_mtp", "num_speculative_tokens": 3}}'
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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device_ids:
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- "${GEN_SMALL_GPU_ID:-0}"
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capabilities:
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- gpu
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healthcheck:
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test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
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interval: 30s
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timeout: 10s
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retries: 3
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start_period: 900s
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networks:
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- tnet
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labels:
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- homepage.group=AI - Inference
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- homepage.name=gen-small (Qwen3.6-35B-A3B heretic)
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- homepage.icon=mdi-lightning-bolt
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- homepage.description=Fast A3B (3B-active) Heretic-abliterated gen seat, MTP, fv-ml1 GPU 0
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- homepage.href=http://10.251.50.54:${GEN_SMALL_PORT:-8026}/docs
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networks:
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tnet:
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name: traefik-net
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external: true
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