When adding GPUs doesn't fix LLM latency, routing is often the hidden problem. A request can hit a serving pod without the useful KV cache or queue behind prefill-heavy traffic. llm-d adds…

Keeping latency and accelerator utilization under control gets harder when LLM inference moves from one server to a Kubernetes cluster. llm-d is a distributed inference serving stack for teams…

Achieve SOTA inference with llm-d on Kubernetes See link below 👇

Google Cloud is showing major love to the OSS community! ❤️ Nightly CI for llm-d on TPUs is officially here for production K8s inferencing. #MachineLearning #AI #GoogleCloud #GKE #TPU #Kubernetes