Kimi K3 is a 2.8T parameter open-weight multimodal reasoning model from Moonshot AI, designed for complex coding, knowledge work, and long-horizon agentic tasks. Its architecture combines KDA and Attention Residuals to improve computational efficiency while supporting very long contexts. The model is positioned for workflows that require careful reasoning over extended inputs, including navigating large repositories, calling tools, and iterating against images, logs, tests, and runtime feedback. Weights are publicly hosted, and the model accepts text and image inputs while producing text outputs.

In practical terms, Kimi K3 fits teams building coding agents, debugging pipelines, or analytical assistants that need to reason over long documents and visual inputs in the same session. It performs well at repository-scale understanding and tool-augmented problem solving, where it can read code, inspect screenshots, and act on test results over many turns. The Kimi Code documentation exposes both a 1M context variant and a 256k variant that delivers equivalent results within its window at roughly half the quota cost, giving developers flexibility between maximum reach and everyday efficiency for routine completion and small-file edits.