#kimik2

Learn how Kimi K2 distinguishes itself as a premier open-weight coding model. We dive into its one-trillion-parameter Mixture-of-Experts (MoE) architecture, which efficiently uses only 32 billion active parameters. Find out how its unique approach—applying reinforcement learning directly to tool use—enables its impressive single-attempt accuracy on SWE-bench and allows it to outperform proprietary models in agentic coding tasks.