AI inference glossary
Serving

Prefix cache hit rate

Also known as cache hit rate, KV reuse rate

In plain English

The hit rate is the share of prompt tokens served from cache instead of being recomputed, which on long sessions is most of the prompt.

Technical definition

Prefix cache hit rate is the fraction of input tokens satisfied from cached KV state rather than recomputed during prefill.

Engineering details

A hit rate is only meaningful next to the tier that produced it, since a token served from accelerator memory and one fetched back from host memory cost very differently. It also depends on more than capacity: eviction can discard a prefix that is still wanted, and routing can send a request to a worker that never held it.

Why it matters

On multi-turn traffic the hit rate largely determines prefill cost, because each turn resends the whole conversation plus a little more. Once reuse is high, the remaining prefill work is dominated by genuinely new tokens, and the bottleneck moves from computation to cache management.

How to read it in InferenceX

The AgentX point view reports hit rate over time, separated by cache tier, alongside the prompt token source breakdown. A run that reports high aggregate throughput on a low hit rate is doing far more prefill work than a well-cached deployment would.