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Modelplane

@modelplaneai.bsky.social

The open source control plane for AI inference

Modelplane @modelplaneai.bsky.social · 10/09/2026

The stack is a per-cluster choice in Modelplane v0.4, and it's immutable, so adoption is incremental. Stand up a @nvidiabot.bsky.social Dynamo cluster next to the ones you already run. Same ModelDeployment on both. modelplane.ai/blog/modelpl... #AI #NVIDIA #Kubernetes

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Modelplane @modelplaneai.bsky.social · 14/08/2026

Modelplane v0.3 is out. Serve the Anthropic Messages API end to end and point Claude Code at your own GPUs. Plus Vultr as a fifth cluster provider, per-cluster credentials for multi-account fleets, and a local end-to-end test that needs no cloud and no GPU. → modelplane.ai/blog/modelpl...

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Modelplane @modelplaneai.bsky.social · 20/07/2026

Cluster-level inference tooling is fine. It just doesn't help you orchestrate the GPUs you own. Nobody at scale runs one cluster. The fix: treat the ones you own as one pool. That's the fleet-level API we designed. How we built it → modelplane.ai/blog/how-we-...

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Modelplane @modelplaneai.bsky.social · 16/07/2026

Modelplane v0.2 is out. Two new providers (Nebius, @microsoft.com Azure AKS), weighted routing for canarying model versions, and cluster taints to reserve or drain capacity. The clusters you own, one pool. Building in the open. → modelplane.ai/blog/modelplane-v0-2

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