The runtime that turns a trained model into a fast, reliable API: how a request flows through the gateway, router, batching and KV cache to the GPU workers and back as a token stream — and the levers that decide throughput, latency and cost.
LLM Inference & Serving — gateway · router · batching · KV cache · GPU workers · streaming architecture by Blake Medulan · for more information contact blake@3halves-labs.com