Kimi K2.5 / K2.6 — Local AI Model by Moonshot AI

Name: LLM Configurator — GPU VRAM Checker
Author: LLM Configurator

作者： Jakub Rusinowski · 最后更新： 2026年7月10日

Moonshot AI's cutting-edge coding and agentic model series. Kimi K2.5 and K2.6 rank among the top models globally for coding tasks, multimodal understanding, and autonomous agent workflows. Built for developers who need a model that can reason, use tools, browse the web, write and debug code end-to-end.

Hardware Requirements

Kimi K2.5	Min 20 GB VRAM · Q4_K_M · 128,000 ctx · `ollama run hf.co/moonshotai/Kimi-K2.5-Instruct-Q4_K_M`
Kimi K2.6	Min 20 GB VRAM · Q4_K_M · 128,000 ctx · `ollama run hf.co/moonshotai/Kimi-K2.6-Instruct-Q4_K_M`
Kimi K2.5 1T (32B Active)	Min 605 GB VRAM · Q4_K_M · 200,000 ctx · `ollama run hf.co/moonshotai/Kimi-K2.5`

Recommended GPU

The cheapest GPU that runs Kimi K2.5 / K2.6 locally (min 20 GB VRAM) is the AMD Radeon RX 7900 XT (20 GB).

联盟营销声明: 本页部分链接为联盟推广链接——如果你通过它们购买，LLM Configurator 可能会获得佣金，而你无需支付任何额外费用。作为亚马逊联盟成员（Amazon Associate），LLM Configurator 会从符合条件的购买中获得收益。

AMD Radeon RX 7900 XT 20GB

首发建议零售价：$899

2026年价格波动较大——请以当前商品页价格为准。

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How to Run Locally

Install Ollama then run: ollama run hf.co/moonshotai/Kimi-K2.5-Instruct-Q4_K_M

Minimum VRAM: 20 GB. For best results use Q4_K_M quantization.

Kimi K2.5 / K2.6 — Frequently Asked Questions

How much VRAM does Kimi K2.5 / K2.6 need?

Kimi K2.5 / K2.6 needs about 20 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: Kimi K2.5 (20 GB, Q4_K_M); Kimi K2.6 (20 GB, Q4_K_M); Kimi K2.5 1T (32B Active) (605 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.

Can I run Kimi K2.5 / K2.6 on an RTX 4090 (24 GB)?

Yes — Kimi K2.5 / K2.6 runs on an RTX 4090 (24 GB) and other 24 GB cards such as the RTX 3090. Smaller variants also fit comfortably on 8–16 GB GPUs at Q4_K_M.

What quantization should I use for Kimi K2.5 / K2.6?

Q4_K_M is the best balance of quality and VRAM for Kimi K2.5 / K2.6 in most cases. Choose Q8_0 for near-lossless quality if you have spare VRAM, or smaller quants (Q3/Q2) only when memory is tight.

How do I run Kimi K2.5 / K2.6 with Ollama?

Install Ollama, then run: ollama run hf.co/moonshotai/Kimi-K2.5-Instruct-Q4_K_M. This downloads Kimi K2.5 / K2.6 and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.