Unverified50% confidenceFactExact time
MLA将高维K、V矩阵投影至低秩潜在空间，压缩比可达8-16倍
1
Sources
50%
Confidence
Long-term
Relevance
7/12/2026
First Seen
Sources
DeepSeek自研AI芯片：算力自主背后的战略逻辑与挑战
hackernewshackernews7/9/2026
Related Claims
VerifiedMLA将KV对压缩到低维潜在空间中进行缓存，推理时通过上投影矩阵恢复完整的Key和Value，将KV缓存压缩了数倍79% similarUnverifiedMLA通过将KV矩阵压缩为低维潜在向量缓存，理论上可将KV Cache显存占用降低至标准MHA的5%至13%72% similarVerified多头潜在注意力机制（MLA）通过将KV投影到低维潜在空间压缩存储，将KV Cache显存占用降低至传统方法的5%至13%72% similarUnverifiedPQ乘积量化通过切分向量、局部聚类、编码替代，可将向量存储体积压缩约8倍（四维示例中从16字节压缩到2字节）69% similarUnverifiedDeepSeek V4通过MLA等压缩技术将KV Cache的显存占用压缩到前代的10%以下69% similar
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