This paper proposes GLU Attention, a new attention mechanism that utilizes GLU (Gated Linear Units) to improve the performance of existing attention mechanisms. GLU Attention introduces nonlinearity to the attention value to improve model performance and convergence speed, and has minimal computational cost without additional parameters. It has been shown to be effective in text and vision modalities, and is also easy to integrate with other technologies such as Flash Attention, RoPE, and GQA. It has been released as open source on GitHub.