FlashMLA ported to consumer Blackwell sm_120, 2-3x faster MLA attention vs SDPA
smashedshanky · reddit · 2026-08-30
While building an open-source LLM training repo supporting arbitrary architectures (GQA/MLA/Dense), a developer found DeepSeek's FlashMLA kernel only compiled for data-center sm100/sm90, so they ported and open-sourced a Windows/Linux build for consumer Blackwell sm120.
Inference vs PyTorch SDPA: sparse fp8 decode 2.62x faster; sparse serving 5x; sparse prefill (sq=512, skv=8192) 2.61x; FP8 KV cache gives -8% latency and 1.84x less cache memory (SDPA: +1.8%). Model-level bf16 decode roughly at parity.
Training (fwd+bwd): Dense seq 1024/4096/8192 at 3.29x / 2.40x / 3.04x, sparse prefill 3.01x.
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