Unverified50% confidenceFactExact time
Prefix caching splits the prompt into cache pages of a fixed size (e.g., 16 tokens), each page corresponding to a segment of KV, and builds a hash index; when a new request arrives, the input tokens are compared page by page, and a hit allows referencing the already-computed KV page and skipping the corresponding prefill computation.
1
Sources
50%
Confidence
Long-term
Relevance
10/16/2026
First Seen
Sources
Related Entities
Related Claims
VerifiedThe KV Cache mechanism can cache repeated prefix content, and the more concise the system prompt, the higher the cache hit rate.75% similarUnverifiedIn Anthropic's API billing system, prompt caching allows a stable prefix to be marked as cached content, and subsequent identical prefixes directly reuse the KV without recomputing attention, with these tokens recorded as "cache reads".74% similarUnverifiedKV Cache avoids redundant computation during autoregressive inference by caching the K and V values of historical tokens, so that new tokens only need to compute their own Q.71% similarUnverifiedPrompt Caching requires the prompt to meet a minimum cacheable length (typically 1024 tokens for Anthropic), and the prefix must be byte-for-byte identical for the cache to hit.70% similarUnverifiedWhen KV cache is reused, cached intermediate activations may produce different logit outputs for the same input when the batch size or sequence concatenation method changes.69% similar
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