Verified80% confidenceFactExact time
vLLM uses PagedAttention for KV Cache management
4
Sources
80%
Confidence
Long-term
Relevance
9/11/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedKV Cache is the Key and Value tensor data from each layer of Attention that the model saves.68% similarVerifiedvLLM is one of the most mainstream open-source inference serving frameworks, implementing efficient KV cache management through its PagedAttention technology.67% similarUnverifiedvLLM是由UC Berkeley开发的高吞吐量推理框架，采用PagedAttention技术提升KV Cache的内存利用率66% similarUnverifiedvLLM's core selling point is PagedAttention, which significantly improves memory utilization and throughput.63% similarUnverifiedThe KV cache is the Key/Value tensors caching historical tokens during large model inference, and its size grows linearly with the number of concurrent requests x sequence length x number of layers, often taking up more VRAM than the weights in long-context multi-user scenarios.63% similar
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