Mistral AI3B~3 GB VRAM at Q4_K_M

Ministral 3 3B — VRAM, speed & local setup

Written by Jakub Rusinowski · Last updated

The smallest Mistral 3: 2.6 GB at Q4_K_M, small enough for smartphones and IoT hardware, with image understanding and a 128K context. Base, instruct and reasoning variants all published under Apache 2.0.

Ministral 3 3B needs about 3 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.

Logic70
Creative68
Coding66

VRAM and speed by quantization

Quoted against NVIDIA RTX 4090 (24 GB). Weights plus overhead only: this model's architecture is unpublished, so no KV cache is added.

QuantVRAMSpeed (est.)Fit
Q2_K
2.63 bpw
1.8 GB~244 tok/sFits
Q3_K_M
3.41 bpw
2.1 GB~223 tok/sFits
Q4_K_M
4.83 bpw
2.6 GB~192 tok/sFits
Q5_K_M
5.67 bpw
2.9 GB~178 tok/sFits
Q6_K
6.56 bpw
3.3 GB~165 tok/sFits
Q8_0
8.50 bpw
4 GB~143 tok/sFits
F16
16.00 bpw
6.8 GB~93 tok/sFits

Black marker = usable memory on the NVIDIA RTX 4090 (24 GB). Estimates from the memory-bandwidth roofline on the methodology page. Ministral 3 3B VRAM calculator →

Get Ministral 3 3B running

The cheapest catalogued GPU that runs Ministral 3 3B is the Intel Arc B570 (10 GB).

Buy this hardware Intel Arc B570 10GB — 10 GB VRAM · 150 W board powerDeploy in the cloud now RTX 4090 on RunPod — from $0.34/hr · rate checked 2026-07

or compare on Vast.ai from $0.35/hr (typical low · varies)

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Intel Arc B570 10GB
10 GB VRAM · 150 W board power
2026 prices are volatile — check the current listing.

How to run Ministral 3 3B

Install Ollama, then run:

ollama run ministral-3:3b
Weights on Hugging Face: mistralai/Ministral-3-3B-Instruct ↗

Specifications

Verified — Checked against the primary source — the model card or the vendor spec page — and corroborated by a second independent source.

Parameters
3 Billion
Context window
131,072
Architecture
Dense Transformer (vision)
Provider
Mistral AI
Licence
Apache 2.0
Practical deployment
Edge device (phone, SBC)
Specified at
Q4_K_M
System RAM
8 GB
Record updated
2026-09-06
LicenceApache-2.0Commercial use permitted

Commercial use permitted. No usage restrictions beyond attribution.

Quality and use cases

Scores as published by the model’s authors or an independent evaluator — quality, not throughput, and not measured by us.

Best foredge devicesmultilingualmultimodalcpu inference

Can I run Ministral 3 3B on my GPU?

Other Ministral 3 sizes

Ministral 3 3B — frequently asked questions

How much VRAM does Ministral 3 3B need?

About 3 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 Ministral 3 3B run on an RTX 4090 (24 GB)?

Yes. Ministral 3 3B needs about 3 GB at Q4_K_M, inside a 24 GB card, at an estimated 192 tokens/sec.

How do I run Ministral 3 3B locally?

Install Ollama and run `ollama run ministral-3:3b`. That pulls the weights and starts a local OpenAI-compatible endpoint; after the download nothing leaves the machine.

What other sizes does Ministral 3 come in?

Ministral 3 3B (3 GB), Ministral 3 8B (6 GB), Ministral 3 14B (9 GB). Every size shares the family's training and licence; the larger ones score higher and need proportionally more memory.