Unverified50% confidenceFactExact time
The prefill phase processes the complete input context, computes attention for all input tokens, and generates the KV cache; it is a compute-intensive operation whose time consumption is strongly correlated with input length.
1
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50%
Confidence
Long-term
Relevance
10/12/2026
First Seen
Sources
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Related Claims
UnverifiedPrefix Cache optimization refers to the API server's ability to cache the KV computation results of an unchanged system prompt prefix across multi-turn conversations for reuse by subsequent requests, reducing redundant computation and lowering latency and token costs.79% similarUnverifiedThe prefill phase requires processing all input tokens at once and is a compute-intensive operation, whereas the decode phase generates only one token per step and is a memory-bandwidth-intensive operation.78% similarUnverifiedConventional 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.74% similarUnverifiedThe caching mechanism is technically commonly referred to as KV Cache or Prompt Caching73% similarVerifiedKV Cache通过将已计算的键值对持久化存储，使相同Prompt前缀的后续请求可直接复用，跳过重复的矩阵运算71% similar
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