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English(EN) 🤖 【AWS ML Blog】Deploying Qwen3.8-2.4T-A95B on Amazon SageMaker HyperPod with vLLM Learn how to deploy Qwen3.8-2.4T-A95B, a 2.4-trillion-parameter open-weight mo

阿里巴巴发布 Qwen3.8-2.4T-A95B 开放权重模型,用于复杂的 AI 任务

阿里巴巴的 Qwen 团队发布了 Qwen3.8-2.4T-A95B,这是他们 Qwen-Max 系列中的首个开放权重模型。这个拥有 2.4 万亿参数、每个 token 激活 950 亿参数的混合注意力架构的大模型,专为要求严苛的智能体和推理任务而设计。发布内容详细介绍了如何使用 vLLMAmazon SageMaker HyperPod 上部署该模型,通过工具调用和推测解码等功能实现高效推理。 AI

影响 为开放权重模型树立了新的标杆,有望加速企业在复杂智能体工作负载方面的应用。

排序理由 前沿实验室模型发布,附带系统卡。[lever_c_demoted from frontier_release: ic=2 ai=1.0]

在 Mastodon — mastodon.social 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

阿里巴巴发布 Qwen3.8-2.4T-A95B 开放权重模型,用于复杂的 AI 任务

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前沿实验室模型发布,附带系统卡。[lever_c_demoted from frontier_release: ic=2 ai=1.0]
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2 independent sources
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Topics
model release, infra
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报道来源 [2]

  1. AWS Machine Learning Blog TIER_1 English(EN) · Dmitry Soldatkin ·

    在 Amazon SageMaker HyperPod 上使用 vLLM 部署 Qwen3.8-2.4T-A95B

    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 spe…

  2. Mastodon — mastodon.social TIER_1 English(EN) · aitools2u ·

    🤖 【AWS ML Blog】使用 vLLM 在 Amazon SageMaker HyperPod 上部署 Qwen3.8-2.4T-A95B 了解如何部署 Qwen3.8-2.4T-A95B,一个拥有 2.4 万亿参数的开放权重模型

    🤖 【AWS ML Blog】Deploying Qwen3.8-2.4T-A95B on Amazon SageMaker HyperPod with vLLM Learn how to deploy Qwen3.8-2.4T-A95B, a 2.4-trillion-parameter open-weight model, on Amazon SageMaker HyperPod with vLL... # AI # TechNews 🔗 https:// aws.amazon.com/blogs/machine-l earning/deployin…