Moonshot AI just dropped Kimi-K2.7-Code, an open-source coding model that wants to make AI-assisted programming less wasteful and more capable. The Beijing-based company claims the model cuts reasoning token usage by 30% compared to its predecessor, which in practical terms means developers burn through fewer compute resources while getting better results.
The model is live on Moonshot AI’s Kimi platform APIs and hosted on Hugging Face under a Modified MIT License. That license permits commercial use with attribution for large-scale deployments, a detail that matters for any company thinking about building products on top of it.
The numbers behind the upgrade
Kimi-K2.7-Code is a Mixture-of-Experts architecture packing 1 trillion total parameters with 32 billion active parameters.
The benchmark improvements over the previous K2.6 model are hard to ignore. Moonshot AI reports a 21.8% gain on Kimi Code Bench v2, an 11.0% improvement on Program Bench, and a 31.5% jump on MLS Bench Lite.
