GoKawiilDeepSeek's KV cache compression techniques adopted industry-wide, cutting AI serving costs
DeepSeek has published a series of KV cache optimizations—including MLA architecture, Compressed Sparse Attention, and now CSA2 with cross-layer reuse and FP4 caching—that reportedly shrink cache memory footprint per token by roughly 437x compared to its earlier V1 model. These techniques reduce the VRAM needed to serve long-context sessions such as coding assistants, and the report says other labs have begun using similar approaches without crediting DeepSeek.