Benchmarks

Performance in LLM serving depends heavily on your specific workload characteristics and hardware stack. From a Ray Serve perspective, the focus is on orchestration overhead and the effectiveness of serving pattern implementations. The Ray team maintains the ray-serve-llm-perf-examples repository with benchmarking snapshots, tooling, and lessons learned. These benchmarks validate the correctness and effectiveness of different serving patterns. You can use these benchmarks to validate your production stack more systematically.