MiMo-V2-Pro — Local AI Model by Xiaomi

Autor: Jakub Rusinowski · Ostatnia aktualizacja: 10 lipca 2026

Xiaomi's 1T+ MoE model originally launched anonymously as 'Hunter Alpha' in March 2026 before being revealed as MiMo-V2-Pro. Led by ex-DeepSeek engineer Luo Fuli. Was the largest model on OpenRouter at launch. Strong on PinchBench and ClawEval agentic benchmarks with ~42B active parameters per token. Available via API through Xiaomi and OpenRouter.

Hardware Requirements

MiMo-V2-Pro 1T+Min 605 GB VRAM · Q4_K_M · 1,000,000 ctx ·

How to Run Locally

Install Ollama then run: ollama run

Minimum VRAM: 605 GB. For best results use Q4_K_M quantization.

MiMo-V2-Pro — Frequently Asked Questions

How much VRAM does MiMo-V2-Pro need?

MiMo-V2-Pro needs about 605 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: MiMo-V2-Pro 1T+ (605 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.

Can I run MiMo-V2-Pro on an RTX 4090 (24 GB)?

MiMo-V2-Pro's smallest variant needs about 605 GB, which exceeds a single RTX 4090 (24 GB). Use multiple GPUs, a higher-VRAM card, or Apple Silicon with large unified memory.

What quantization should I use for MiMo-V2-Pro?

Q4_K_M is the best balance of quality and VRAM for MiMo-V2-Pro 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 MiMo-V2-Pro with Ollama?

Install Ollama, then run: ollama run . This downloads MiMo-V2-Pro and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.

Can I Run MiMo-V2-Pro on My GPU?