LLM-D

Summary from the TLDR AI newsletter

llm-d is a Kubernetes-native stack for distributed LLM inference. It runs vLLM, SGLang, and more across clusters, turning single-node engines into production-grade serving on local hardware. llm-d provides tested deployment recipes for common production patterns that are adaptable starting points across models, hardware, and workloads. It runs production LLM inference across GPUs, TPUs, XPUs, CPUs, and emerging NPUs with consistent performance patterns, so teams can deploy once and scale anywhere with predictable cost and behavior.