Unverified50% confidenceSolutionExact time
What local inference frameworks can do is optimize KV cache management (such as paged attention and prefix caching), so that long conversations are not interrupted by running out of VRAM, thereby remaining stable in multi-turn scenarios.
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50%
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Long-term
Relevance
10/15/2026
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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.75% similarUnverifiedSome feature flag SDKs cache evaluation results locally to reduce latency; if the cache does not expire after an impersonation session ends, real users may briefly see incorrect feature states.75% similarUnverifiedThe 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.75% similarUnverified上下文缓存机制对多轮对话、长文档处理和批量任务等场景尤为有利72% similar
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