The October 30, 2025 technical report details the development and evaluation of Kimi Linear, a novel hybrid linear attention architecture for large language models (LLMs). The core innovation is the Kimi Delta Attention (KDA) module, which refines existing linear attention mechanisms to achieve superior performance and efficiency compared to traditional full attention, particularly in long-context scenarios. Empirical results from extensive pretraining and fine-tuning experiments demonstrate that Kimi Linear outperforms baselines across various tasks, including general reasoning and code generation, while significantly reducing memory usage and increasing decoding throughput. The report also includes a complexity analysis and a detailed discussion of KDA's relationship to other efficient attention and state-space models. Source: https://arxiv.org/pdf/2510.26692