recipe.toml 1.2 KB

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  1. engine = "vllm"
  2. name = "Gemma 4 12B IT (MTP)"
  3. docker_image = "vllm/vllm-openai:gemma4-unified"
  4. model = "google/gemma-4-12B-it"
  5. # docker_image = "ghcr.io/timothystewart6/vllm-gb10:v0.23.0-gb10.1"
  6. # model = "RedHatAI/gemma-4-12B-it-NVFP4"
  7. tensor_parallel_size = 1
  8. pipeline_parallel_size = 1
  9. distributed_backend = "none"
  10. # Single-node recipe: Gemma 4 12B with BF16, FP8 KV cache,
  11. # MTP speculative decoding (5 tokens), 196K context.
  12. entrypoint = ["vllm", "serve"]
  13. args = [
  14. "--dtype", "bfloat16",
  15. "--kv-cache-dtype", "fp8",
  16. "--gpu-memory-utilization", "0.75",
  17. "--max-model-len", "196608",
  18. "--max-num-seqs", "2",
  19. "--max-num-batched-tokens", "8192",
  20. "--enable-prefix-caching",
  21. "--enable-chunked-prefill",
  22. "--enable-auto-tool-choice",
  23. "--tool-call-parser", "gemma4",
  24. "--reasoning-parser", "gemma4",
  25. "--generation-config", "vllm",
  26. "--safetensors-load-strategy", "prefetch",
  27. "--speculative-config", """
  28. '{"method":"mtp","model":"google/gemma-4-12B-it-assistant","num_speculative_tokens":5}'""",
  29. "--limit-mm-per-prompt", """
  30. '{"image":4,"audio":1,"video":1}'""",
  31. "--trust-remote-code",
  32. "--served-model-name", "gemma4-12b",
  33. ]
  34. [env]
  35. TRITON_CACHE_DIR = "/root/.cache/triton"