Kimi-K2-Instruct-0905 on AMD/Nvidia GPU

Using the Windows Package Manager is the quickest way to trigger the setup.

Carefully read and apply the steps described below.

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

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

🛠 Hash code: 0e0627cbeaa48dcf5831ce8182b5a426 — Last modification: 2026-06-24

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CPU: modern architecture (Zen 3 / Alder Lake minimum)
RAM: enough space for background apps and OS overhead
Disk Space:70 GB free space for full FP16 weights storage
GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats

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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