AnalysisAI ModelsAugust 29, 2026

HyQuant targets low-bit LLM attention quantization errors

HyQuant keeps critical vertical-line tokens and local windows in high precision while quantizing the rest, aiming to hold accuracy at very low bit-widths with low overhead. The paper addresses attention quantization errors that grow at low bit-widths, with KV-cache compression across prefill and decode stages.

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