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DeepSeek avatar

FlashMLA

Optimized attention kernels for DeepSeek model inference on GPUs and NPUs

  • AI models and runtimes
View on GitHub

What it is

DeepSeek's library of Multi-head Latent Attention kernels, used to serve DeepSeek-V4.1 on NVIDIA Blackwell GPUs and Huawei Ascend 950 NPUs. It offers token-level sparse attention for both the prefill and decode stages, using KV caches stored in FP8 or FP4, along with a fused norm-RoPE-attention-RoPE-cast kernel and dense attention kernels for forward and backward passes. Engineers building inference engines or training stacks call it from PyTorch to speed up attention on supported hardware.

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Facts

Stars
13,114 GitHub stars.
13,114

Forks
1,202
Commits
66
Contributors
18
Language
C++
License
MIT
Last commit
Oct 15, 2026
On GitHub since
February 2025
Platforms
Linux, library
Self-hostable
No
Tags
  • machine-learning
  • llm-inference
  • model-optimization
  • gpu-computing

Last synced from GitHub on Oct 20, 2026

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What people are saying

Updated Oct 21, 2026
  • Hacker NewsDeepSeek Open Source FlashMLA – MLA Decoding Kernel for Hopper GPUsFeb 24, 2025 · 441 points · 108 comments (opens Hacker News in a new tab)