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PQCache: Product Quantization-based KVCache for Long Context LLM Inference

Summary: PQCache uses PQ to compress KVCache for long-context LLM inference, treating KVCache as embedding retrieval. During prefilling and autoregressive decoding, PQ codes and centroids approximate key selection to fetch K/V, reducing overhead. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
7319
Venue
SIGMOD
Year
2025
Pagerank
6.7091071e-05
Overall Rank
4,430 | 69.61%
DOI
10.1145/3725338

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{zhang_sigmod25,
        title = {{PQCache: Product Quantization-based KVCache for Long Context LLM Inference}},
        author = {Zhang, Hailin and Ji, Xiaodong and Chen, Yilin and Fu, Fangcheng and Miao, Xupeng and Nie, Xiaonan and Chen, Weipeng and Cui, Bin},
        series = {{SIGMOD} '25},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3725338},
        url = {https://dl.acm.org/doi/10.1145/3725338},
        year = {2025}
}

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