Unverified70% confidenceFactExact time
PagedAttention divides the KV Cache into fixed-size blocks, allocates them dynamically on demand, and allows blocks from different requests to be stored non-contiguously.
2
Sources
70%
Confidence
Long-term
Relevance
9/11/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedPagedAttention cuts the KV Cache into fixed-size blocks, allocated on demand and stored non-contiguously, raising VRAM utilization from the traditional 20%–40% to over 90%.79% similarUnverifiedvLLM's PagedAttention mechanism divides the KV cache into blocks of a fixed number of tokens (usually 16), and records the mapping from logical positions to physical blocks through a block table.77% similarUnverifiedPagedAttention divides the KV Cache into fixed-size blocks, with each block typically storing the key-value pairs of 16 tokens.74% similarVerifiedThe size of the KV cache is determined by three multiplied dimensions: the size of each record, how many tokens are combined into one record, and whether layers can share caches with each other.72% similarVerifiedPagedAttention技术借鉴操作系统虚拟内存的分页思想，将KV Cache切分为固定大小的物理块动态分配71% similar
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