MoBA
MoBA: Mixture of Block Attention for Long-Context LLMs
MoBA is an open-source local AI project on GitHub under the MIT license (permissive), with 2.2k stars. It is built with CPython, Transformers and PyTorch. Its last push was 2 years ago.
- Stars
- 2.2k
- License
- MIT
- Activity
- Quiet
Judgement
- What it is
- Building block
- What it does
- Research code for Mixture of Block Attention, a trainable sparse attention method that lets each query attend only to the most relevant blocks of a long context.
- Adopt it when
- You train or continue-train long-context language models and want to test block sparse attention in place of full attention.
- Watch out
- Models must be further trained to benefit, so it does nothing for an existing pretrained model, and the repo has not been updated since April 2025.
- Ready for
- Experimental
- Runs as
- Library
- Built with
- Python, PyTorch and Hugging Face Transformers
- How established
- Young: started 20 months ago, no tagged release yet.
- What the license allows
- You can build it into a product you sell, as long as you keep its copyright notice.
Judged on 2026-11-06 from the project's README and GitHub data. The license and age lines are worked out directly.
Built from
Follow it down: MoBA → CPython → GCC → LLVM project → runs on a microchip
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