Kimi K2 (07/11)

Kimi K2 is a large-scale Mixture-of-Experts language model built to excel in agentic workflows, complex reasoning, and code synthesis. With a massive architecture totaling one trillion parameters, the model utilizes 32 billion active parameters per forward pass to balance computational efficiency with high-level performance. It is specifically engineered to handle demanding technical tasks, demonstrating strong capabilities across benchmarks such as LiveCodeBench for programming, SWE-bench for software engineering, and reasoning-focused evaluations like ZebraLogic and GPQA.

The model is supported by a novel training stack that incorporates the MuonClip optimizer, which ensures stability during the large-scale training of its Mixture-of-Experts architecture. Beyond its core reasoning strengths, Kimi K2 is optimized for long-context inference, allowing it to process information across a 128K token window. This design makes it a robust choice for developers and organizations requiring reliable tool-use and deep analytical processing, positioning it as a versatile tool for modern AI-driven agentic applications.