Unverified50% confidenceFactExact time
Prompt caching is an inference optimization mechanism introduced by mainstream large-model API providers: when the prefix portion of a request is exactly identical to that of a previous request, the server can directly reuse the already-computed KV cache without re-running the forward computation.
1
Sources
50%
Confidence
Long-term
Relevance
10/27/2026
First Seen
Sources
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Related Claims
UnverifiedA cache hit means the model server recognizes that the prefix of the current request highly overlaps with a previous request, and directly reuses the already-computed KV cache without re-running inference, thereby reducing the actual computation load.80% similarVerifiedThe core principle of prompt caching is cross-request reuse of the KV Cache, where already-computed KV states can be cached and reused when multiple requests share the same prefix.79% similarUnverifiedPrompt caching is a capability of the Anthropic API: when the prefix portion of a request is exactly identical to the previous request, the server can reuse the already-computed intermediate state and skip redundant prefill computation.78% similarUnverifiedPrompt Caching is an optimization across requests, users, and conversations: as long as the prompt prefixes of different requests are completely identical, the corresponding KV results can be shared globally.76% similarVerifiedConventional KV caching is an optimization within a single request: within the same conversation round, the KV generated from historical messages does not need to be recomputed, and only the newly input content is computed incrementally.75% similar
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