AnalysisAI ModelsSeptember 30, 2026

Blog: Western labs adopt DeepSeek KV cache optimizations

Read original source →insufferable.dev

DeepSeek's KV cache work cut long-context cache footprint roughly 437x versus DeepSeek-V1, starting with MLA's ~15x compression, then Compressed Sparse Attention and Heavily Compressed Attention. DeepSeek-V4.1-Flash adds CSA2, cross-layer cache reuse, a causal encoder-decoder architecture, and FP4 caching, bringing the global KV cache to 890 bytes per token.

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Blog: Western labs adopt DeepSeek KV cache optimizations