Run Your Own Inference Stack on Vultr with Modelplane

Modelplane v0.3 adds Vultr Kubernetes Engine as a supported inference cluster provider, allowing users to define scalable GPU clusters through YAML manifests that specify regions, node pools, instance types, and scaling limits while automatically provisioning networking, Kubernetes components, GPU infrastructure, and the inference layer. The open-source platform aims to provide a uniform operating model across cloud providers including Vultr, GKE, EKS, and AKS, enabling model deployment manifests to remain unchanged when underlying hardware changes. The release also adds end-to-end support for Anthropic’s Messages API through vLLM, allowing compatible clients such as Claude Code to use models hosted on users’ own Vultr GPU clusters by mapping Anthropic model tiers to locally served models. Users can follow Modelplane’s Vultr getting-started materials or review release notes, while unsupported providers and instance classes can be requested or contributed through GitHub.

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