Unverified70% confidenceTradeoffExact time
Cache expiration is essentially a trade-off providers make between GPU memory pressure and user experience, as maintaining large KV Caches over a long period consumes inference capacity.
2
Sources
70%
Confidence
Long-term
Relevance
8/12/2026
First Seen
Sources
Related Claims
UnverifiedGPU solutions use batching technology to combine multiple user requests for computation, which can greatly increase overall throughput and represents a trade-off between latency and throughput.77% similarUnverified长上下文在首次推理时需完整计算KV Cache，消耗GPU计算资源并占用显存带宽，拉长首token延迟（TTFT）75% similarVerifiedThe KV Cache (Key-Value Cache) strategy stores already-computed attention key-value pairs in GPU memory for reuse, which consumes a large amount of GPU memory resources.75% similarUnverifiedThe server side can reuse already-computed parts through the KV cache (key-value cache), significantly reducing repeated computation; the higher the cache hit rate, the more requests the same hardware can handle.75% similarUnverifiedSession state needs to be managed in tiers across GPU memory, host memory, and even external storage, otherwise it will either blow up the GPU memory or drag down latency due to frequent swapping in and out.75% similar
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