Moonshot opensources FlashKDA, claiming 1.72×–2.22× H20 prefill gains
ctjlewis · x · 2026-07-27
Moonshot AI open-sourced FlashKDA, a high-performance CUTLASS-based implementation of Kimi Delta Attention kernels.
- The repo is designed as a drop-in backend for flash-linear-attention.
- The team says it delivers 1.72×–2.22× prefill speedup over the flash-linear-attention baseline on H20.
- Requirements listed in the repo include SM90+, CUDA 12.9+, and PyTorch 2.4+.
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