Modelplane

New to the AI inference stack? Start here. 🛠️ Viktor Farcic closes Inference Day with Inference 101, a practical look at the emerging inference stack and what platform engineers need to know. Nov 5, 10:30 AM PT / 7:30 PM CET. Free and virtual. Register here 👉 modelplane.ai/inference-day

Kelsey Hightower. Live. Your questions. 🔥 Kelsey opens our Inference Day with a fireside chat on how inference is changing infrastructure and what platform teams should build now. Bring your questions. Starts Nov 5, 8 AM PT / 5 PM CET. Free and virtual. modelplane.ai/inference-day

Introducing Inference Day. 🚀 A free, live virtual event on the future of AI infrastructure. Nov 5, 8 to 11 AM PT. Kelsey Hightower, Viktor Farcic, and builders from NVIDIA, Red Hat, Tetrate, Ericsson, Qualcomm and Dash0. Every session is live. Save your spot 👉 modelplane.ai/inference-day

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

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...

We measured our Claude Code usage at API prices: 13x our seat cost on average, 52x for our heaviest engineer. Nothing broke. That's Claude Code working as intended, once you see the meter. What's your subsidy multiple? → modelplane.ai/blog/ai-codi...

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-...

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

Modelplane is here: an open source control plane for AI inference. Any model, any engine, any infra, from one GPU to multi-node. It's v0.1 and built in the open. Spin it up on a kind cluster, then tell us where it breaks. ⭐ → modelplane.ai