---
title: Ministral-3-3B-Instruct-2512-6bit
canonical_url: "https://www.modelscope.cn/models/mlx-community/Ministral-3-3B-Instruct-2512-6bit"
md_url: "https://www.modelscope.cn/models/mlx-community/Ministral-3-3B-Instruct-2512-6bit.md"
repository: mlx-community/Ministral-3-3B-Instruct-2512-6bit
last_updated: 2025-12-04
license: apache-2.0
model_type:
  - mistral3
architectures:
  - Mistral3ForConditionalGeneration
base_model:
  - mistralai/Ministral-3-3B-Base-2512
base_model_relation: quantized
library_name:
  - mlx
  - safetensors
  - pytorch
frameworks:
  - pytorch
language:
  - en
  - fr
  - es
  - de
  - it
  - pt
  - nl
  - zh
  - ja
  - ko
  - ar
inference_backends:
  - "deploy_task vlm/text/emb"
  - "sglang 0.5.2"
  - "vllm 0.9.2"
downloads: 32
stars: 0
tags:
  - mistral-common
  - mlx
---

# Ministral-3-3B-Instruct-2512-6bit

> Ministral-3-3B-Instruct-2512-6bit - mlx-community 在 ModelScope 开源的模型。mlx-community/Ministral-3-3B-Instruct-2512-6bit This model was converted to MLX format from mistralai/Ministral-3-3B-Instruct-2512 using mlx-vlm version 0.3.9. Refer to the original model…

mlx-community/Ministral-3-3B-Instruct-2512-6bit 是 ModelScope 魔搭社区上的机器学习模型，采用 apache-2.0 许可，基于 mistralai/Ministral-3-3B-Base-2512 构建，可用 deploy_task vlm/text/emb、sglang 0.5.2、vllm 0.9.2 部署。

- **Repository**: mlx-community/Ministral-3-3B-Instruct-2512-6bit
- **License**: apache-2.0
- **Base model**: mistralai/Ministral-3-3B-Base-2512
- **Inference backends**: deploy_task vlm/text/emb, sglang 0.5.2, vllm 0.9.2
- **Tags**: mistral-common, mlx
- **Downloads**: 32
- **Stars**: 0
- **Last updated**: 2025-12-04

Source: https://www.modelscope.cn/models/mlx-community/Ministral-3-3B-Instruct-2512-6bit

---

# mlx-community/Ministral-3-3B-Instruct-2512-6bit
This model was converted to MLX format from [`mistralai/Ministral-3-3B-Instruct-2512`]() using mlx-vlm version **0.3.9**.
Refer to the [original model card](https://huggingface.co/mistralai/Ministral-3-3B-Instruct-2512) for more details on the model.
## Use with mlx

```bash
pip install -U mlx-vlm
```

```bash
python -m mlx_vlm.generate --model mlx-community/Ministral-3-3B-Instruct-2512-6bit --max-tokens 100 --temperature 0.0 --prompt "Describe this image." --image <path_to_image>
```