Ray Serve LLM

Prefill, not decode, has become the dominant bottleneck in RAG and multi-agent workloads, according to an analysis citing NVIDIA's published figures of roughly 30x higher served-request counts for lar…

Ray Serve LLM, developed by Anyscale, introduces token-load-aware routing to improve LLM serving efficiency, moving beyond naive KV cache reuse strategies. The new approach addresses the challenges of…

Ray Serve LLM, in partnership with Google Kubernetes Engine, announced major performance improvements achieving up to 4.4x higher throughput on prefill-heavy workloads and 24x higher on decode-heavy w…