How to Install Kimi-K2.7-Code Windows 10 with Native FP4

How to Install Kimi-K2.7-Code Windows 10 with Native FP4

The fastest way to get this model running locally is via Docker.

Make sure to follow the instructions below.

The installer automatically pulls the model (could be multiple GBs).

You don’t need to tweak anything, as the installer will automatically pick the highest performing setup for you.

🧾 Hash-sum — 50453b7291776cf32c3140a4614d7177 • 🗓 Updated on: 2026-06-27



  • CPU: multi-threading optimized for fast prompt processing
  • RAM: fast 5600MHz+ required to avoid memory bottlenecks
  • Storage: extra room for future model updates and datasets
  • Graphics: TensorRT-LLM / vLLM inference engine compatible chip

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 Count 7.5B
Training Tokens 3 trillion
Supported Languages 30
Inference Speed >200 tokens/s

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

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