HubLens › Compare › FlashMLA vs FlashMLA

FlashMLA vs FlashMLA

Side-by-side comparison of stars, features, and trends

shared:DeepSeekAttentionCUDAPyTorchLLM
FlashMLAmetricFlashMLA
12,617Stars12,617
93Score93
AICategoryAI
github-zh-incSourcegithub-zh-inc

// FlashMLA

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.

use cases
  • 01Token-level sparse attention for prefill and decoding stages
  • 02Dense attention kernels for high-performance prefill and decoding
  • 03FP8 KV cache support for optimized memory and compute efficiency

// FlashMLA

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.

use cases
  • 01Token-level sparse attention for prefill and decoding stages
  • 02Dense attention kernels for high-performance prefill and decoding
  • 03FP8 KV cache support for optimized memory and compute efficiency