Kimi-K2.7-Code with Native FP4 5-Minute Setup Windows

The most rapid route to a local installation of this model is through WSL2.

Kindly follow the on-screen instructions below.

The script takes care of fetching the multi-gigabyte model weights.

The engine benchmarks your hardware to apply the most effective operational mode.

📊 File Hash: 2608be7a7235d481b833686bb109a278 — Last update: 2026-06-29
  • Processor: Intel i7 / Ryzen 7 for heavy Quantized models
  • RAM: required: 16 GB absolute minimum for small models
  • Disk Space: at least 100 GB for multiple local LLM variants
  • Graphics: CUDA Compute Capability 8.0+ required for flash-attention

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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