Unverified50% confidenceBenchmarkExact time
Compared to traditional contiguous allocation, PagedAttention can increase the number of concurrent requests on the same GPU by 2–4 times.
1
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50%
Confidence
Long-term
Relevance
9/7/2026
First Seen
Sources
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Related Claims
VerifiedPagedAttention divides the KV cache into fixed-size pages allocated on demand, and can improve VRAM utilization by 2–4×.77% similarUnverifiedGPU 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.76% similarUnverifiedFlash Attention reduces the number of reads and writes to GPU high-bandwidth memory by reorganizing the computation order, achieving a 2–4× speed improvement without changing the computation results.71% similarUnverifiedPagedAttention 使显存利用率提升至接近 100%，实现同等硬件下并发吞吐量提升 2-4 倍68% similarUnverifiedCompared to traditional methods, PagedAttention enables vLLM to increase batch size by 2–4 times and achieve close to 100% memory utilization.67% similar
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