project6 391866785e perf(config): match competitor Sub168's proven engine params
From competitor docker log analysis:
- max_model_len: 100000 → 256000 (competitor proven, 19259 GPU blocks)
- gpu_memory_utilization: 0.90 → 0.95 (competitor proven)
- max_num_batched_tokens: None → 4096 (competitor proven)
- enable_chunked_prefill: off → on (competitor proven, critical for 256K context)
- max_num_seqs stays at 2 (matches competitor)

Competitor Sub168 scored 60194 with these exact params before OOM at replay tail.
Our code has OOM-surviving advantages they lack (n>1 clamp, max_completion_tokens).

Docker log evidence: competitor's vLLM started with 19259 GPU blocks at 0.95 util,
ran for ~1h18m before OOM in layernorm.py x.float() at 31.72 GiB GPU.
2026-08-07 08:48:20 +00:00
2026-08-07 08:43:51 +00:00
2026-07-30 17:03:23 +08:00
2026-08-07 07:47:01 +00:00

project_6

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