How to self-host Kimi K3 on AWS

Kimi K3 is an open-weight, 2.8-trillion-parameter Mixture-of-Experts model with a 1-million-token context window whose self-hosting requires substantial distributed GPU capacity, high-performance networking, persistent storage, and an inference engine such as vLLM. Running it in an organization’s AWS account can provide greater control over data processing, infrastructure, internal-service connectivity, security requirements, and existing cloud investments, though users must review its licensing terms and accept the operational complexity of production-scale serving. Northflank positions its Bring Your Own Cloud offering as a management layer that deploys Kimi K3 within a customer’s AWS account and VPC while retaining customer control of compute, networking, data, and region selection. The platform supports Kubernetes management, GPU workloads, application services, databases, CI/CD, observability, and enterprise controls including RBAC, SSO, secrets management, audit logging, and network configuration, allowing organizations to operate the model alongside AI agents and dependent applications. A typical deployment involves connecting AWS to Northflank, creating a BYOC cluster, provisioning GPUs, deploying the inference service, connecting applications to its endpoint, and managing it through the platform.

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