Kimi K2 is a large-scale mixture-of-experts model that activates only a fraction of its parameters per token, making it efficient at handling long, complex reasoning tasks without proportional compute costs. It tends to shine in agentic workflows — multi-step tool use, code generation, and instruction-following chains — where it maintains coherence across many turns.