MiMo-V2.5-Pro 1T — VRAM, Speed & Local Setup

Written by Jakub Rusinowski · Last updated September 6, 2026

Model library → MiMo-V2.5 → MiMo-V2.5-Pro 1T

The flagship: 1 trillion total, 42B active per token, MIT, 1M context. Matches frontier coding models on published comparisons at a licence that imposes no revenue threshold. Datacenter-class to self-host at about 605 GB at Q4_K_M.

MiMo-V2.5-Pro 1T needs about 605 GB of VRAM at Q4_K_M — quantized weights plus framework overhead, before any KV cache. On Apple Silicon that figure comes out of unified memory.

Specifications

Parameters	1 Trillion (42B active)
Context window	1,000,000
Architecture	Mixture-of-Experts
Provider	Xiaomi
Licence	MIT
Specified at	Q4_K_M
System RAM	768 GB
Record updated	2026-09-06

Licence

MIT — commercial use permitted. Commercial use permitted. No usage restrictions beyond attribution.

VRAM and Speed by Quantization

Modelled on a reference NVIDIA RTX 4090 (24 GB), with no KV cache (this record has no published architecture). Speed figures are ESTIMATES from the memory-bandwidth roofline described on the methodology page, not benchmarks we ran — rows marked measured come from published or reader-submitted runs. VRAM here includes the KV cache, so it reads higher than the headline figure above, which does not.

Quant	Weights	VRAM needed	Est. speed	Fit on 24 GB
Q2_K	328.8 GB	329.6 GB	—	Won't fit
Q3_K_M	426.3 GB	427.1 GB	—	Won't fit
Q4_K_M	603.8 GB	604.5 GB	—	Won't fit
Q5_K_M	708.8 GB	709.5 GB	—	Won't fit
Q6_K	820.0 GB	820.8 GB	—	Won't fit
Q8_0	1062.5 GB	1063.3 GB	—	Won't fit
F16	2000.0 GB	2000.8 GB	—	Won't fit

Want the memory numbers alone, at every quantization level and your own context length? Use the MiMo-V2.5-Pro 1T VRAM calculator.

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How to Run MiMo-V2.5-Pro 1T

Install Ollama, then run:

ollama run mimo-v2-5

Weights on Hugging Face: XiaomiMiMo/MiMo-V2.5-Pro.

Best for: coding, agentic tasks, long context, enterprise.

Can I Run MiMo-V2.5-Pro 1T on My GPU?

Other MiMo-V2.5 Sizes

MiMo-V2.5 310B — about 188 GB VRAM at Q4_K_M

MiMo-V2.5-Pro 1T — Frequently Asked Questions

How much VRAM does MiMo-V2.5-Pro 1T need?

About 605 GB at Q4_K_M — quantized weights plus framework overhead, before any KV cache. The cache grows with context length and is added on top; the table above folds it in. Apple Silicon counts unified memory toward the same figure.

Does MiMo-V2.5-Pro 1T run on an RTX 4090 (24 GB)?

No. MiMo-V2.5-Pro 1T needs about 605 GB at Q4_K_M, more than a single RTX 4090's 24 GB. It needs a larger card, several GPUs, or Apple Silicon with enough unified memory — or it runs with part of the weights offloaded to system RAM, which is much slower.

How do I run MiMo-V2.5-Pro 1T locally?

Install Ollama and run `ollama run mimo-v2-5`. That pulls the weights and starts a local OpenAI-compatible endpoint; after the download nothing leaves the machine.

What other sizes does MiMo-V2.5 come in?

MiMo-V2.5 310B (188 GB), MiMo-V2.5-Pro 1T (605 GB). Every size shares the family's training and licence; the larger ones score higher and need proportionally more memory.

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