# Recipe: OpenAI GPT-OSS 120B
# OpenAI's open source 120B MoE model with MXFP4 quantization support

recipe_version: "1"
name: OpenAI GPT-OSS 120B
description: vLLM serving openai/gpt-oss-120b with MXFP4 quantization and FlashInfer

# HuggingFace model to download (optional, for --download-model)
model: openai/gpt-oss-120b

# Container image to use
container: vllm-node-mxfp4

# Build arguments for build-and-copy.sh
build_args:
  - --exp-mxfp4

# No mods required for this model
mods: []

# Default settings (can be overridden via CLI)
defaults:
  port: 8000
  host: 0.0.0.0
  tensor_parallel: 2
  gpu_memory_utilization: 0.70
  max_num_batched_tokens: 8192

# Environment variables to set in the container
env:
  VLLM_USE_FLASHINFER_MOE_MXFP4_MXFP8: "1"

# The vLLM serve command template
# Uses MXFP4 quantization for memory efficiency
command: |
  vllm serve openai/gpt-oss-120b \
      --tool-call-parser openai \
      --reasoning-parser openai_gptoss \
      --enable-auto-tool-choice \
      --tensor-parallel-size {tensor_parallel} \
      --distributed-executor-backend ray \
      --gpu-memory-utilization {gpu_memory_utilization} \
      --enable-prefix-caching \
      --load-format fastsafetensors \
      --quantization mxfp4 \
      --mxfp4-backend CUTLASS \
      --mxfp4-layers moe,qkv,o,lm_head \
      --attention-backend FLASHINFER \
      --kv-cache-dtype fp8 \
      --max-num-batched-tokens {max_num_batched_tokens} \
      --host {host} \
      --port {port}