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Kwon and colleagues: PagedAttention for language-model serving

Contribution grade

Language-model inference systems · Human-designed research method or resource

Reference score190,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Managed attention key-value caches with paged blocks, flexible sharing and copy-on-write, supporting higher-throughput serving in the vLLM system.

Scientific scope

Managed attention key-value caches with paged blocks, flexible sharing and copy-on-write, supporting higher-throughput serving in the vLLM system. PagedAttention and the original vLLM system are one package. Throughput comparisons depend on hardware, model, requests and sampling strategy; later vLLM features are not included.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. PagedAttention and the original vLLM system are one package. Throughput comparisons depend on hardware, model, requests and sampling strategy; later vLLM features are not included.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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