Written by Jakub Rusinowski · Last updated September 6, 2026
The edge tier of the Mistral 3 family — 3B, 8B and 14B dense, every size shipped in base, instruct and reasoning variants with image understanding, all Apache 2.0. Built for laptops, phones, drones and anywhere a datacenter is not. The 3B runs in about 4 GB of video memory; the 14B reasoning variant scores 85% on AIME 2025.
| Licence | What it permits | Applies to |
|---|---|---|
Apache-2.0 | Commercial use permitted Commercial use permitted. No usage restrictions beyond attribution. | Ministral 3 3B, Ministral 3 8B, Ministral 3 14B |
| Ministral 3 3B | Min 3 GB VRAM · Q4_K_M · 131,072 ctx · ollama run ministral-3:3b |
| Ministral 3 8B | Min 6 GB VRAM · Q4_K_M · 131,072 ctx · ollama run ministral-3:8b |
| Ministral 3 14B | Min 9 GB VRAM · Q4_K_M · 131,072 ctx · ollama run ministral-3:14b |
The cheapest GPU that runs Ministral 3 locally (min 3 GB VRAM) is the Intel Arc B570 (10 GB).
Install Ollama then run: ollama run ministral-3:3b
Minimum VRAM: 3 GB. For best results use Q4_K_M quantization.
Ministral 3 needs about 3 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: Ministral 3 3B (3 GB, Q4_K_M); Ministral 3 8B (6 GB, Q4_K_M); Ministral 3 14B (9 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.
Yes — Ministral 3 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.
Q4_K_M is the best balance of quality and VRAM for Ministral 3 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.
Install Ollama, then run: ollama run ministral-3:3b. This downloads Ministral 3 and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.