Advanced Prompt Caching at Scale

Introduction Prompt caching is the process of reusing already computed KV states across inference requests in order to save money and reduce latency. Within a single replica, modern inference engines like vLLM , SGLang , and TensorRT-LLM handle it automatically. Incoming prompts are matched against cached prefixes and recomputed only where necessary, without requiring user configurations The problem nobody talks about is what happens when you scale to many replicas.