Prefix caching is a self-hosted inference optimization that stores KV cache states for common prompt prefixes on the serving infrastructure, enabling instant context reuse without recomputation.
Prefix caching is a self-hosted inference optimization that stores KV cache states for common prompt prefixes on the serving infrastructure, enabling instant context reuse without recomputation. Unlike API-level prompt caching offered by providers, prefix caching is implemented in open-source serving engines for self-hosted deployments.
When serving models locally with engines like vLLM or SGLang, prefix caching uses a radix tree data structure to store KV cache blocks indexed by token sequences. When a new request arrives, the engine performs a longest-prefix match against cached sequences. Matching blocks are reused directly, and only the novel suffix requires computation. This is particularly effective for multi-turn conversations where each turn shares the entire previous conversation as a prefix.
The technique extends beyond simple prefix matching. SGLang's RadixAttention enables sharing across branching sequences — useful for tree-of-thought prompting, parallel tool calls, or beam search — where multiple generation paths share a common ancestor. Cache eviction follows LRU (least recently used) policies when GPU memory is exhausted.
For self-hosted deployments, prefix caching delivers the same economic benefits that API providers offer through managed caching. Multi-turn agents that accumulate 10,000+ tokens of conversation history see 3-5x throughput improvements because each turn only processes the new user message rather than the entire history.
A coding assistant deployed on vLLM with prefix caching enabled serves a team of 50 developers. Since all users share the same 4,000-token system prompt and most conversations run 10+ turns, prefix caching reduces average prefill time from 800ms to 50ms per request, enabling the service to run on 2 GPUs instead of 6.
Aaron is an engineering leader, software architect, and founder with 18 years building distributed systems and cloud infrastructure. Now focused on LLM-powered platforms, agent orchestration, and production AI. He shares hands-on technical guides and framework comparisons at fp8.co.