Unverified50% confidenceFactExact time
KV Cache is a core optimization technique during the inference phase of large language models, essentially a space-for-time strategy that avoids redundant computation by caching the Key and Value vectors of historical tokens.
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9/15/2026
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Related Claims
VerifiedThe KV Cache mechanism can cache repeated prefix content, and the more concise the system prompt, the higher the cache hit rate.80% 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.76% similarUnverifiedDecode 阶段属于访存密集型操作，每生成一个新 token 需从显存读取全部历史 token 的 KV Cache72% similarVerifiedKV Cache reduces inference complexity from O(n²) to O(n) by caching the already-computed Key/Value matrices.70% similarUnverifiedMainstream model providers (such as Anthropic and DeepSeek) support prompt caching mechanisms, and reusing the KV Cache of identical prefix contexts can save 50%–90% of input costs.68% similar
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