AI Potluck
Infrastructure / Compilers & Model Optimization

DeepGEMM

DeepSeek

DeepGEMM is a tensor-core kernel library gathering the computation primitives modern large language models depend on - FP8, FP4 and BF16 GEMMs, fused mixture-of-experts with overlapped communication, and MQA scoring - into one CUDA codebase. Kernels compile at runtime through a lightweight JIT module, so installation needs no CUDA toolchain. It borrows concepts from CUTLASS and CuTe without depending on their templates.

Verified 2026-08-18 via the GitHub API and the LICENSE body.

Openness

5 high confidence
5.0
license
MIT(OSI)
source
public
core-gated
ungated

MIT license body confirmed. The repository is public and unarchived and builds the whole product, and the README describes no paid tier, enterprise edition or license-gated build beside it, so source is public and the core ungated.

Adoption

2 low confidence
2.0

7,700 GitHub stars, which lands in the 1K-10K stars band of the stars scale, level 2. Built from source rather than published to a package registry, so no download figure exists and the stars scale applies with its cap of 3.

Capability

3 medium confidence
3.0

Banded on the category feature matrix as performance-critical kernel and operator library. Placed two bands below the apache-tvm anchor, on a matrix that bands on how much of the model-to-hardware transformation pipeline a product performs, over how many inputs and targets.

Verified 2026-08-18