---
license: other
license_name: minimax-community
license_link: LICENSE
library_name: mlx
pipeline_tag: text-generation
base_model: MiniMaxAI/MiniMax-M3.1-Flash
tags:
- moe
- agent
- coding
- mlx
---

# mlx-community/MiniMax-M3.1-Flash-Text-3bit

This model [mlx-community/MiniMax-M3.1-Flash-Text-3bit](https://huggingface.co/mlx-community/MiniMax-M3.1-Flash-Text-3bit) was converted to MLX format from [MiniMaxAI/MiniMax-M3.1-Flash](https://huggingface.co/MiniMaxAI/MiniMax-M3.1-Flash) using mlx-lm with [ml-explore/mlx-lm#2003](https://github.com/ml-explore/mlx-lm/pull/2003). Refer to the [original model card](https://huggingface.co/MiniMaxAI/MiniMax-M3.1-Flash) for more details on the model.

This is a text-only conversion. The vision tower is not included.

The original weights were dequantized and then quantized to 3-bit affine with group size 64 (3.5 bits per weight). The router is kept at 8 bits. Peak memory was about 187 GB in a short generation test.

Tested with mlx-lm 0.32.2.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("mlx-community/MiniMax-M3.1-Flash-Text-3bit")

prompt = "hello"

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

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