Kimi K2.7 Code NVFP4 v4

--- tags: - compressed-tensors license: other license_name: modified-mit library_name: transformers pipeline_tag: image-text-to-text --- <div align="center"> <picture> <img src="figures/kimi-logo.png" width="30%" alt="Kimi K2.7 Code"> </picture> </div> <hr> <div align="center" style="line-height:1"> <a href="https://www.kimi.com/code" target="_blank"><img alt="Chat" src="https://img.shields.io/badge/🤖-Kimi--Code-ff6b6b?color=1783ff&logoColor=white"/></a> <a href="https://www.moonshot.ai" target="_blank"><img alt="Homepage" src="https://img.shields.io/badge/Homepage-Moonshot%20AI-white?logo=Kimi&logoColor=white"/></a> </div> <div align="center" style="line-height: 1;"> <a href="https://huggingface.co/moonshotai" target="_blank"><img alt="Hugging Face" src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Moonshot%20AI-ffc107?color=ffc107&logoColor=white"/></a> <a href="https://twitter.com/kimi_moonshot" target="_blank"><img alt="Twitter Follow" src="https://img.shields.io/badge/Twitter-Kimi.ai-white?logo=x&logoColor=white"/></a> <a href="https://discord.gg/TYU2fdJykW" target="_blank"><img alt="Discord" src="https://img.shields.io/badge/Discord-Kimi.ai-white?logo=discord&logoColor=white"/></a> <a href="https://modelscope.cn/organization/moonshotai" target="_blank"><img alt="ModelScope" src="https://img.shields.io/badge/ModelScope-Moonshot%20AI-white?labelColor=rgb(99%2C%2074%2C%20255)"/></a> </div> <div align="center" style="line-height: 1;"> <a href="https://huggingface.co/moonshotai/Kimi-K2.7-Code/blob/main/LICENSE"><img alt="License" src="https://img.shields.io/badge/License-Modified_MIT-f5de53?&color=f5de53"/></a> </div> ## 1. Model Introduction Kimi K2.7 Code is a coding-focused agentic model built upon Kimi K2.6. With substantial improvements on real-world long-horizon coding tasks, it strengthens end-to-end task completion across complex software engineering workflows while improving token efficiency, reducing thinking-token usage by approximately 30% compared with Kimi K2.6. ## 2. Model Summary <div align="center"> | | | |:---:|:---:| | **Architecture** | Mixture-of-Experts (MoE) | | **Total Parameters** | 1T | | **Activated Parameters** | 32B | | **Number of Layers** (Dense layer included) | 61 | | **Number of Dense Layers** | 1 | | **Attention Hidden Dimension** | 7168 | | **MoE Hidden Dimension** (per Expert) | 2048 | |...