Expired50% confidenceFactTime unknown
The Hybrid Compressed Attention mechanism in DeepSeek V4 compresses KV Cache by aggregating Key-Value pairs from multiple tokens into more compact representations.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
7/2/2026
First Seen
Valid until: 9/30/2026(expired)
Sources
DeepSeek V4 Deep Technical Breakdown: Million-Token Context and Extreme Cost Efficiency
bilibili码书z
Related Claims
UnverifiedDeepSeek-V2提出MLA（Multi-head Latent Attention），通过低秩压缩将KV Cache压缩至MHA的5%左右70% similarUnverifiedDeepSeek V4 introduces an N-gram memory architecture that stores static knowledge in CPU memory rather than GPU VRAM.69% similarVerifiedDeepSeek V4 adopts a proprietary hierarchical compressed attention strategy, featuring two alternating attention modes: CSA (Compressed Sink Attention) and HCA (Heavy Compressed Attention).69% similarVerifiedMLA (Multi-head Latent Attention) was first proposed by the DeepSeek team in DeepSeek-V2, and significantly reduces KV Cache memory usage by compressing Key-Value pairs into a low-dimensional latent space.68% similarUnverifiedDeepSeek's innovations in Multi-head Latent Attention (MLA) and FP8 mixed-precision training compress KV Cache memory usage to 5%–13% of standard multi-head attention.68% similar
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