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FlashMLA is a library of high-performance attention kernels specifically designed to power DeepSeek-V3 and DeepSeek-V3.2 models. It provides optimized implementations for both sparse and dense attention mechanisms during prefill and decoding stages. The library supports advanced features like FP8 KV cache and is compatible with various GPU architectures including SM90 and SM100.
FlashMLA is a library of high-performance attention kernels specifically designed to power DeepSeek-V3 and DeepSeek-V3.2 models. It provides optimized implementations for both sparse and dense attention mechanisms during prefill and decoding stages. The library supports advanced features like FP8 KV cache and is compatible with various GPU architectures including SM90 and SM100.