Mistral AI · First MLX build 18 Jul 2026
Ministral-3-8B-Base-2512
MLX
TextVision apache-2.0
A 8.9B parameter vision and text model from Mistral AI, with 4 MLX builds, from 4-bit to bf16.
- Parameters
- 8.9B From Hugging Face
- Quantisation
- 4-bit Ministral-3-8B-Base-2512-4bit
- Memory needed
- 8 GB Estimate, unified memory
- Download
- 4.8 GB Weights, estimated
- Downloads
- 111 This build, last 30 days
- Task
- Vision and text Text, Vision
- MLX builds
- 4 On mlx-community
- Devices
- Mac Apple silicon
Memory
Will it fit?Needs about 8 GB at 4-bit
8 GB
16 GB
24 GB
32 GB
64 GB
128 GB
Fits with headroomTight, close other appsWon’t fit
Estimated from the size of the weights, plus a fifth for context and working memory and 2 GB for macOS and your apps. Long contexts need more.
Run it
Terminal · mlx-vlm$ pip install -U mlx-vlm
$ python -m mlx_vlm.generate --model mlx-community/Ministral-3-8B-Base-2512-4bit --image photo.jpg --prompt "Describe this image"MLX builds
4 on mlx-community| Ministral-3-8B-Base-2512-4bit | 4-bit | 4.8 GB | 8 GB | 111 |
|---|---|---|---|---|
| Ministral-3-8B-Base-2512-6bit | 6-bit | 8.4 GB | 12 GB | 38 |
| Ministral-3-8B-Base-2512-8bit | 8-bit | 10.4 GB | 14 GB | 53 |
| Ministral-3-8B-Base-2512-bf16 | bf16 | 17.8 GB | 22 GB | 52 |
Sizes are estimated from Hugging Face’s parameter counts and the quantisation. Downloads are for the last 30 days.