Kimi K2.7 Code is positioned as a coding-focused agentic model built on the earlier Kimi K2.6, continuing Moonshot AI's line of developer-oriented releases. It ships as one of two models offered through the Kimi Code product family alongside Kimi K3, available across four selectable model IDs that integrate with coding clients and third-party agent tools. Open weights are published by Moonshot AI under a Modified MIT license, hosted on Hugging Face, with additional mirrors and community channels on ModelScope, Discord, and Twitter.

The model targets real-world long-horizon coding work, emphasizing end-to-end completion of complex software engineering tasks and improved token efficiency compared with its predecessor. The model card reports roughly a thirty percent reduction in thinking-token usage relative to Kimi K2.6, helping multi-step agent workflows stay within budget during extended sessions. Its architecture is a one-trillion-parameter Mixture-of-Experts design with thirty-two billion activated parameters, sixty-one layers (including one dense layer), sixty-four attention heads, and three hundred eighty-four experts per token, giving it the scale needed for repository-scale refactors and tool-driven development while keeping per-token activation costs lean.