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spark-vllm-docker/recipes/qwen3.5-122b-int4-autoround.yaml
2026-03-06 23:35:18 -08:00

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# Recipe: Qwen3.5-122B-A10B-INT4-Autoround
# Qwen3.5-122B model in Intel INT4-Autoround quantization
recipe_version: "1"
name: Qwen3.5-122B-INT4-Autoround
description: vLLM serving Qwen3.5-122B-INT4-Autoround
# HuggingFace model to download (optional, for --download-model)
model: Intel/Qwen3.5-122B-A10B-int4-AutoRound
#solo_only: true
# Container image to use
container: vllm-node-tf5
build_args:
- --tf5
# Mod required to fix ROPE syntax error
mods:
- mods/fix-qwen3.5-autoround
- mods/fix-qwen3.5-chat-template
# Default settings (can be overridden via CLI)
defaults:
port: 8000
host: 0.0.0.0
tensor_parallel: 2
gpu_memory_utilization: 0.7
max_model_len: 262144
max_num_batched_tokens: 8192
# Environment variables
env:
VLLM_MARLIN_USE_ATOMIC_ADD: 1
# The vLLM serve command template
command: |
vllm serve Intel/Qwen3.5-122B-A10B-int4-AutoRound \
--max-model-len {max_model_len} \
--gpu-memory-utilization {gpu_memory_utilization} \
--port {port} \
--host {host} \
--load-format fastsafetensors \
--enable-prefix-caching \
--enable-auto-tool-choice \
--tool-call-parser qwen3_coder \
--reasoning-parser qwen3 \
--max-num-batched-tokens {max_num_batched_tokens} \
--trust-remote-code \
--chat-template unsloth.jinja \
-tp {tensor_parallel} \
--distributed-executor-backend ray