English(EN) Deploying Kimi K3 on AWS

Moonshot AI 发布 Kimi K3，一款 2.8T 参数的开源 MoE 模型

作者 PulseAugur 编辑部 · [2 个来源] · 2026-07-30 17:22

Moonshot AI 发布了 Kimi K3，这是一款拥有 2.8 万亿参数的开源专家混合（MoE）模型。该模型采用了 Kimi Delta Attention 等架构创新，提高了扩展效率，并在长时程编码和代理工作流等复杂任务上表现出色。模型权重以 MXFP4 格式在 Hugging Face 上提供，并详细介绍了如何使用 Amazon SageMaker HyperPod 和 Amazon EKS 在 AWS 上进行部署，这需要 NVIDIA B300 Blackwell Ultra GPUs 等大量 GPU 资源。 AI

影响为开源 MoE 模型树立了新的标杆，可能加速大规模 AI 的自托管和研究。

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]

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

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Signal score: 0 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Significant; 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]
Source corroboration: 2 independent sources; Multiple independent publishers reporting the same story raises confidence that it's real and newsworthy.
Topics: model release, infra; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
Story freshness: 47 days old; Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

完整方法见我们的编辑标准。

AWS Machine Learning Blog TIER_1 English(EN) · Vivek Gangasani · 2026-07-30 17:22

在 AWS 上部署 Kimi K3

This post walks through deploying Kimi K3 on AWS using two approaches: Amazon SageMaker HyperPod, and  Amazon Elastic Kubernetes Service (Amazon EKS) cluster.
AWS Machine Learning Blog TIER_1 English(EN) · Vivek Gangasani · 2026-07-30 17:22

在 Amazon SageMaker HyperPod 和 Amazon EKS 上部署 Kimi K3

This post walks through deploying Kimi K3 on AWS using two approaches: Amazon SageMaker HyperPod, and  Amazon Elastic Kubernetes Service (Amazon EKS) cluster.