Image-Text-to-Text
MLX
Safetensors
mistral3
mistral-common
ministral
ministral-3
vision-language
multimodal
quantized
edge
8-bit precision
base-model
Instructions to use mlx-community/Ministral-3-8B-Base-2512-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/Ministral-3-8B-Base-2512-8bit with MLX:
# Make sure mlx-vlm is installed # pip install --upgrade mlx-vlm from mlx_vlm import load, generate from mlx_vlm.prompt_utils import apply_chat_template from mlx_vlm.utils import load_config # Load the model model, processor = load("mlx-community/Ministral-3-8B-Base-2512-8bit") config = load_config("mlx-community/Ministral-3-8B-Base-2512-8bit") # Prepare input image = ["http://images.cocodataset.org/val2017/000000039769.jpg"] prompt = "Describe this image." # Apply chat template formatted_prompt = apply_chat_template( processor, config, prompt, num_images=1 ) # Generate output output = generate(model, processor, formatted_prompt, image) print(output) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
File size: 4,706 Bytes
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library_name: mlx
language:
- en
- fr
- es
- de
- it
- pt
- nl
- zh
- ja
- ko
- ar
license: apache-2.0
inference: false
extra_gated_description: If you want to learn more about how we process your personal
data, please read our <a href="https://mistral.ai/terms/">Privacy Policy</a>.
tags:
- mistral-common
- mlx
- ministral
- ministral-3
- vision-language
- multimodal
- quantized
- edge
- 8-bit
- base-model
pipeline_tag: image-text-to-text
base_model: mistralai/Ministral-3-8B-Base-2512
---
# mlx-community/Ministral-3-8B-Base-2512-8bit
This is, **Ministral 3 8B Base 2512** is a vision-language model: a text backbone paired
with a vision encoder, supporting image understanding alongside text. This is
the **base pre-trained** checkpoint — not instruction- or chat-tuned. For
chat/instruction-following use cases, use the
[Instruct variant](https://huggingface.co/mlx-community/Ministral-3-8B-Instruct-2512-8bit)
instead; this base checkpoint is intended for custom post-training/fine-tuning.
> **Community note.** Structural check confirms the vision tower and
> multimodal projector were carried over intact (not dropped, which is a real
> failure mode for text-only conversion tools on vision-language models).
> Functional check confirms both text-only and image+text generation produce
> coherent output. Converted and verified by a single maintainer running
> local MLX tooling -- not independently reviewed by anyone else; please open
> a discussion if you hit anything unexpected.
This is an MLX conversion of [`mistralai/Ministral-3-8B-Base-2512`](https://huggingface.co/mistralai/Ministral-3-8B-Base-2512),
converted with [mlx-vlm](https://github.com/Blaizzy/mlx-vlm). Refer to the
[original model card](https://huggingface.co/mistralai/Ministral-3-8B-Base-2512) for the full
description, capabilities, and license terms.
## Heads up
- **Base model, not instruct-tuned** — expect raw completion behavior, not
chat-following. Don't expect it to follow instructions well.
- **Vision retained at full precision** — only the language backbone is
quantized; the vision tower and multimodal projector are untouched bf16,
per mlx-vlm's standard policy of not quantizing multimodal modules.
- **Output size on disk: 10.42GB**
## Provenance
- Source: [`mistralai/Ministral-3-8B-Base-2512`](https://huggingface.co/mistralai/Ministral-3-8B-Base-2512) (BF16)
- Language model layers: **8-bit** affine quantization, group_size=64
- Vision tower + multimodal projector: kept at full precision (not quantized)
- Blended average: **9.312 bits per weight** across all parameters
## Ministral 3 family
| Model | Type | mlx-community (4-bit) |
|---|---|---|
| Ministral 3 3B Base 2512 | Base pre-trained | [mlx-community/Ministral-3-3B-Base-2512-4bit](https://huggingface.co/mlx-community/Ministral-3-3B-Base-2512-4bit) |
| Ministral 3 3B Instruct 2512 | Instruct post-trained | [mlx-community/Ministral-3-3B-Instruct-2512-4bit](https://huggingface.co/mlx-community/Ministral-3-3B-Instruct-2512-4bit) |
| Ministral 3 3B Reasoning 2512 | Reasoning capable | [mlx-community/Ministral-3-3B-Reasoning-2512-4bit](https://huggingface.co/mlx-community/Ministral-3-3B-Reasoning-2512-4bit) |
| Ministral 3 8B Base 2512 | Base pre-trained | [mlx-community/Ministral-3-8B-Base-2512-4bit](https://huggingface.co/mlx-community/Ministral-3-8B-Base-2512-4bit) |
| Ministral 3 8B Instruct 2512 | Instruct post-trained | [mlx-community/Ministral-3-8B-Instruct-2512-4bit](https://huggingface.co/mlx-community/Ministral-3-8B-Instruct-2512-4bit) |
| Ministral 3 8B Reasoning 2512 | Reasoning capable | [mlx-community/Ministral-3-8B-Reasoning-2512-4bit](https://huggingface.co/mlx-community/Ministral-3-8B-Reasoning-2512-4bit) |
| Ministral 3 14B Base 2512 | Base pre-trained | [mlx-community/Ministral-3-14B-Base-2512-4bit](https://huggingface.co/mlx-community/Ministral-3-14B-Base-2512-4bit) |
| Ministral 3 14B Instruct 2512 | Instruct post-trained | [mlx-community/Ministral-3-14B-Instruct-2512-4bit](https://huggingface.co/mlx-community/Ministral-3-14B-Instruct-2512-4bit) |
| Ministral 3 14B Reasoning 2512 | Reasoning capable | [mlx-community/Ministral-3-14B-Reasoning-2512-4bit](https://huggingface.co/mlx-community/Ministral-3-14B-Reasoning-2512-4bit) |
## Use with mlx
```bash
pip install -U mlx-vlm
```
```bash
python -m mlx_vlm.generate --model mlx-community/Ministral-3-8B-Base-2512-8bit --max-tokens 100 --temperature 0.0 --prompt "Describe this image." --image <path_to_image>
```
For text-only prompts, omit `--image`.
## License
Apache 2.0 — see the [original model card](https://huggingface.co/mistralai/Ministral-3-8B-Base-2512) for
the full license text and any usage terms.
|