Deploying Qwen3.8-2.4T-A95B on Amazon SageMaker HyperPod with vLLM
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Learn how to deploy Qwen3.8-2.4T-A95B, a 2.4-trillion-parameter open-weight model, on Amazon SageMaker HyperPod with vLLM. This walkthrough covers cluster provisioning, NVFP4 quantization, and an OpenAI-compatible endpoint with built-in reasoning, tool calling, and native MTP speculative decoding.
On August 12, 2026, Alibaba’s Qwen team released Qwen3.8-2.4T-A95B . This is the first time a Qwen-Max-class model has been made available as open weights. With 2.4 trillion total parameters (95 billion activated per token), a hybrid linear-plus-full-attention architecture, and native context up to 262K tokens (extensible to 1M), Qwen3.8 targets the most demanding agentic and reasoning workloads. These include multi-step coding, long-horizon planning, and autonomous tool use. Open weights…
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