MiMo-V2.5 310B — VRAM, Speed & Local Setup

Autor: Jakub Rusinowski · Ostatnia aktualizacja: 6 września 2026

Model library → MiMo-V2.5 → MiMo-V2.5 310B

310B total, 15B active per token, MIT, 1M context. Every one of the 310B must be resident — 188 GB at Q4_K_M, so a 192 GB Mac Studio or a small multi-GPU box — while per-token bandwidth is that of a 15B model. The standard variant rather than the flagship, and the cheaper of the two to serve.

MiMo-V2.5 310B needs about 188 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

Parameters310 Billion (15B active)
Context window1,000,000
ArchitectureMixture-of-Experts
ProviderXiaomi
LicenceMIT
Specified atQ4_K_M
System RAM256 GB
Record updated2026-09-06

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.

QuantWeightsVRAM neededEst. speedFit on 24 GB
Q2_K101.9 GB102.7 GB—Won't fit
Q3_K_M132.1 GB132.9 GB—Won't fit
Q4_K_M187.2 GB188.0 GB—Won't fit
Q5_K_M219.7 GB220.5 GB—Won't fit
Q6_K254.2 GB255.0 GB—Won't fit
Q8_0329.4 GB330.2 GB—Won't fit
F16620.0 GB620.8 GB—Won't fit

Want the memory numbers alone, at every quantization level and your own context length? Use the MiMo-V2.5 310B VRAM calculator.

Buy This HardwareApple Mac Studio M2 Ultra — 192 GB VRAM · 60 W board powerDeploy in the Cloud NowRunPod

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Recommended GPU

The cheapest catalogued GPU that runs MiMo-V2.5 310B is the Apple M2 Ultra (192 GB).

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Apple Mac Studio M2 Ultra
192 GB VRAM · 60 W board power
Ceny w 2026 są niestabilne — sprawdź aktualną ofertę.
Sprawdź cenę na Amazon

How to Run MiMo-V2.5 310B

Install Ollama, then run:

ollama run mimo-v2-5

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

Best for: long context, agentic tasks, enterprise, cost efficient.

Can I Run MiMo-V2.5 310B on My GPU?

Other MiMo-V2.5 Sizes

MiMo-V2.5 310B — Frequently Asked Questions

How much VRAM does MiMo-V2.5 310B need?
About 188 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 310B run on an RTX 4090 (24 GB)?
No. MiMo-V2.5 310B needs about 188 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 310B 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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