MoBA (Mixture of Block Attention) is an innovative attention mechanism specifically designed for large language models dealing with long text contexts. It achieves efficient long sequence processing by dividing the context into blocks and allowing each query token to learn to focus on the most relevant blocks. MoBA's main advantage is its ability to seamlessly switch between full attention and sparse attention, ensuring performance while improving computational efficiency. This technology is suitable for tasks that require processing long texts, such as document analysis and code generation, and can significantly reduce computational costs while maintaining high model performance. The open-source implementation of MoBA provides researchers and developers with a powerful tool, driving the application of large language models in long text processing.