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Setup Kimi-K2.7-Code on AMD/Nvidia GPU 5-Minute Setup

Setup Kimi-K2.7-Code on AMD/Nvidia GPU 5-Minute Setup

The fastest method for installing this model locally is by using Docker.

Kindly follow the on-screen instructions below.

The client handles the setup, pulling gigabytes of data automatically.

To guarantee smooth performance, the process auto-selects the best options.

📘 Build Hash: d20f35ed3a5aaafc928eae9a7cf0e721 • 🗓 2026-06-28



  • CPU: AVX2/AVX-512 instruction set required for llama.cpp
  • RAM: 32 GB highly recommended for 26B+ GGUF models
  • Disk Space: free: 80 GB on system drive for scratch space
  • GPU: modern architecture (Ada Lovelace / Ampere minimum)

Kimi-K2.7-Code is a large language model specifically optimized for code generation and software development tasks. It leverages an innovative architecture that combines attention mechanisms with efficient memory usage, enabling it to handle complex programming languages while maintaining fast inference speeds. The model supports a broad spectrum of multilingual coding environments, making it a versatile tool for global development teams. In benchmarks, Kimi-K2.7-Code achieves state-of-the-art scores in code completion, bug fixing, and refactoring challenges.

Parameter Count7.5B
Training Tokens3 trillion
Supported Languages30
Inference Speed>200 tokens/s

Developers can integrate the model via standard APIs for seamless workflow incorporation.

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