Verified80% confidenceFactExact time
vLLM's PagedAttention draws on the operating system concept of virtual memory paging to manage KV caches, reducing GPU memory fragmentation overhead from approximately 30% to near 0.
4
Sources
80%
Confidence
Long-term
Relevance
7/8/2026
First Seen
Sources
Related Claims
VerifiedPagedAttention was proposed by the vLLM team in 2023; drawing on the virtual memory paging mechanism of operating systems, it reduced the KV Cache memory waste rate from over 60% to close to 4%.84% similarUnverifiedvLLM's PagedAttention splits the KV cache into fixed-size physical blocks (typically 16 tokens), improving GPU memory utilization from below 40% to close to 90%.74% similarUnverifiedvLLM的PagedAttention将KV Cache划分为固定大小物理块，通过块表实现地址映射，将碎片化率从60-80%降至不足4%，吞吐量提升可达24倍74% similarUnverifiedvLLM的PagedAttention将KV Cache碎片化率从传统方案的60-80%降至不足4%，吞吐量提升可达24倍73% similar
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