Deploying Kimi K3 on Amazon SageMaker HyperPod and Amazon EKS
AWS drops a how-to for running Kimi K3 at scale on SageMaker HyperPod and EKS.
Why it matters
Practitioners deploying frontier models need deployment patterns. This is vendor-authored infrastructure guidance on running a capable model (Kimi K3) on AWS managed services — useful for teams evaluating HyperPod vs. EKS for production inference or fine-tuning.
The key facts
9 to knowTwo deployment architectures covered: SageMaker HyperPod and Amazon EKS
Model: Kimi K3 (Moonshot AI)
AWS managed services as deployment target
Published as vendor blog (AWS ML Blog)
No pricing, performance benchmarks, or adoption data provided
Kimi K3 deployment supported on Amazon SageMaker HyperPod
Kimi K3 deployment supported on Amazon EKS
Two deployment approaches documented
Published July 30, 2026
Go to the source
AWS Machine Learning Blogaws.amazon.com
Publisher excerpt: This post walks through deploying Kimi K3 on AWS using two approaches: Amazon SageMaker HyperPod, and Amazon Elastic Kubernetes Service (Amazon EKS) cluster.