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Announcing the llm-d community!

· 11 min read
Robert Shaw
Director of Engineering, Red Hat
Clayton Coleman
Distinguished Engineer, Google
Carlos Costa
Distinguished Engineer, IBM

Announcing the llm-d community

llm-d is a Kubernetes-native high-performance distributed LLM inference framework
- a well-lit path for anyone to serve at scale, with the fastest time-to-value and competitive performance per dollar for most models across most hardware accelerators.

With llm-d, users can operationalize gen AI deployments with a modular, high-performance, end-to-end serving solution that leverages the latest distributed inference optimizations like KV-cache aware routing and disaggregated serving, co-designed and integrated with the Kubernetes operational tooling in Inference Gateway (IGW).