Kimi-K2.7-Code 开源，编程与智能体性能大幅提升
Kimi-K2.7-Code 在编程和智能体任务上显著超越前代，且推理更高效，做 AI 编程或智能体开发的团队可以直接通过 API 或 Kimi Code 试用，值得关注。
月之暗面发布并开源了最新编程模型 Kimi-K2.7-Code，相比 K2.
6 在 Kimi Code Bench v2 上提升 21.8%，在 Program Bench 上提升 11.
0%，在 MLS Bench Lite 上提升 31.5%。
该模型减少了过度思考，推理 token 使用量降低 30%，同时改进了长时编程任务中的指令遵循和成功率。模型已通过 Kimi API 和 Kimi Code 可用，即将推出 6 倍高速模式。
🌘 Kimi-K2.7-Code, our latest coding model, is now released and open-sourced!
🔷 Improved coding & agent performance over K2.6: +21.8% on Kimi Code Bench v2, +11.0% on Program Bench, and +31.5% on MLS Bench Lite. 🔷 Reasoning efficiency: Less overthinking, with 30% lower reasoning-token usage compared to K2.6. 🔷 Long-horizon coding: Improved instruction following, higher end-to-end coding task success rates.
⚡️ 6x High-Speed Mode coming soon! 🔌 Available today via Kimi API and Kimi Code.
🔗 Kimi Code: https://t.co/uvoSJKyGCY 🔗 API: https://t.co/EOZkbOwCN4
This report is categorized under AITOP's "Models" desk, focusing on China's AI industry and domestic foundation model ecosystem. Within our cross-regional analytical framework, it directly maps to AI developer toolchains, coding agents, and engineering workflows and US-China foundation model benchmarks and commercialization comparison. Key entities and technical topics under continuous tracking include 编程模型, 开源/仓库, 推理效率, 智能体.
Source attribution: curated from kimi_moonshot (@kimi_moonshot).
