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This post details deploying the 2.4-trillion parameter Qwen3.8-2.4T-A95B model on Amazon SageMaker HyperPod using vLLM. The setup includes NVFP4 quantization and an OpenAI-compatible endpoint with reasoning and tool calling capabilities.
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From AWS machine learning blog - “Deploying Qwen3.8-2.4T-A95B on Amazon SageMaker HyperPod with vLLM”
A walkthrough is presented for deploying Qwen3.8-2.4T-A95B on Amazon SageMaker HyperPod. The deployment utilizes vLLM. The process includes cluster provisioning. NVFP4 quantization is used to reduce model size. An OpenAI-compatible endpoint is created. This endpoint includes built-in reasoning, tool calling, and native MTP speculative decoding. This configuration provides an inference endpoint suitable for a range of applications.
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