A recipe for Gemma4-26B
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recipes/gemma4-26b-a4b.yaml
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49
recipes/gemma4-26b-a4b.yaml
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# Recipe: Gemma4-26B-A4B
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# Gemma4-26B-A4B model in online FP8 quantization
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recipe_version: "1"
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name: Gemma4-26B-A4B
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description: vLLM serving Gemma4-26B-A4B
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# HuggingFace model to download (optional, for --download-model)
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model: google/gemma-4-26B-A4B-it
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# Only cluster is supported
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cluster_only: false
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solo_only: false
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# Container image to use
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container: vllm-node-tf5
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# No mods required
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mods: []
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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: 8192
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# Environment variables
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env: {}
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# The vLLM serve command template
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command: |
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vllm serve google/gemma-4-26B-A4B-it \
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--max-model-len {max_model_len} \
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--gpu-memory-utilization {gpu_memory_utilization} \
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--port {port} \
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--host {host} \
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--load-format fastsafetensors \
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--enable-prefix-caching \
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--enable-auto-tool-choice \
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--tool-call-parser gemma4 \
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--reasoning-parser gemma4 \
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--quantization fp8 \
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--kv-cache-dtype fp8 \
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--max-num-batched-tokens {max_num_batched_tokens} \
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-tp {tensor_parallel} --distributed-executor-backend ray
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