---
title: MiniMax-M2-5bit
canonical_url: "https://www.modelscope.cn/models/mlx-community/MiniMax-M2-5bit"
md_url: "https://www.modelscope.cn/models/mlx-community/MiniMax-M2-5bit.md"
repository: mlx-community/MiniMax-M2-5bit
last_updated: 2025-10-29
license: mit
pipeline_tag: text-generation
tasks:
  - text-generation
model_type:
  - minimax
architectures:
  - MiniMaxM2ForCausalLM
base_model:
  - MiniMaxAI/MiniMax-M2
base_model_relation: quantized
parameters: 42.9B
tensor_type:
  - BF16
  - F32
  - U32
library_name:
  - mlx
  - safetensors
  - pytorch
frameworks:
  - pytorch
downloads: 62
stars: 0
tags:
  - mlx
---

# MiniMax-M2-5bit

> MiniMax-M2-5bit - mlx-community 在 ModelScope 开源的模型。mlx-community/MiniMax-M2-5bit

mlx-community/MiniMax-M2-5bit 是 ModelScope 魔搭社区上的 42.9B 参数text-generation模型，采用 mit 许可，基于 MiniMaxAI/MiniMax-M2 构建。

- **Repository**: mlx-community/MiniMax-M2-5bit
- **License**: mit
- **Tasks**: text-generation
- **Parameters**: 42.9B
- **Base model**: MiniMaxAI/MiniMax-M2
- **Tags**: mlx
- **Downloads**: 62
- **Stars**: 0
- **Last updated**: 2025-10-29

Source: https://www.modelscope.cn/models/mlx-community/MiniMax-M2-5bit

---

# mlx-community/MiniMax-M2-5bit

This model [mlx-community/MiniMax-M2-5bit](https://huggingface.co/mlx-community/MiniMax-M2-5bit) was
converted to MLX format from [MiniMaxAI/MiniMax-M2](https://huggingface.co/MiniMaxAI/MiniMax-M2)
using mlx-lm version **0.28.4**.

## Use with mlx

```bash
pip install mlx-lm
```

```python
from mlx_lm import load, generate

model, tokenizer = load("mlx-community/MiniMax-M2-5bit")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)
```