Renamed recipe for qwen3.5-35b-a3b-fp8 to match others
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recipes/qwen3.5-35b-a3b-fp8.yaml
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recipes/qwen3.5-35b-a3b-fp8.yaml
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# Recipe: Qwen/Qwen3.5-35B-A3B-FP8
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# Qwen/Qwen3.5-35B-A3B model in native FP8 format
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recipe_version: "1"
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name: Qwen35-35B-A3B
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description: vLLM serving Qwen3.5-35B-A3B-FP8
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# HuggingFace model to download (optional, for --download-model)
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model: Qwen/Qwen3.5-35B-A3B-FP8
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#solo_only: true
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# Container image to use
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container: vllm-node
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# Mod required to fix slowness and crash in the cluster (tracking https://github.com/vllm-project/vllm/issues/33857)
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mods:
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- mods/fix-qwen3-coder-next
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# Default settings (can be overridden via CLI)
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defaults:
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port: 8000
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host: 0.0.0.0
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tensor_parallel: 2
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gpu_memory_utilization: 0.7
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max_model_len: 262144
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max_num_batched_tokens: 16384
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# Environment variables
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env:
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VLLM_MARLIN_USE_ATOMIC_ADD: 1
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# The vLLM serve command template
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command: |
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vllm serve Qwen/Qwen3.5-35B-A3B-FP8 \
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--host {host} \
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--port {port} \
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--max-model-len {max_model_len} \
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--max-num-batched-tokens {max_num_batched_tokens} \
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--gpu-memory-utilization {gpu_memory_utilization} \
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--enable-auto-tool-choice \
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--tool-call-parser qwen3_coder \
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--kv-cache-dtype fp8 \
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--load-format fastsafetensors \
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--attention-backend flashinfer \
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--enable-prefix-caching \
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-tp {tensor_parallel} \
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--distributed-executor-backend ray
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