---
base_model: MiniMaxAI/MiniMax-M2.5
language: en
library_name: mlx-lm
license: apache-2.0
model_name: MiniMax-M2.5-mix3-6bit
tags:
- quantization
- mixed_3_6
- minimax
- mlx
---
---
base_model: MiniMaxAI/MiniMax-M2.5
language: en
library_name: mlx-lm
license: modified-mit
model_name: MiniMax-M2.5-mix3-6bit
tags:
- quantization
- mixed_3_6
- minimax
- mlx
---

# MiniMax-M2.5-mix3-6bit

Mixed precision quantized version of MiniMax M2.5 using mlx-lm with `--quant-predicate mixed_3_6`.

## Model Details

| Property | Value |
|----------|-------|
| **Base Model** | [MiniMaxAI/MiniMax-M2.5](https://huggingface.co/MiniMaxAI/MiniMax-M2.5) |
| **Quantization** | mlx-lm v0.30.7 with `--quant-predicate mixed_3_6` |
| **Library** | [mlx-lm](https://github.com/huggingface/mlx-lm) |
| **License** | modified-mit |

## Inference Parameters

| Parameter | Value |
|-----------|-------|
| **temperature** | 1.0 |
| **top_p** | 0.95 |
| **top_k** | 40 |

## Usage

```python
import mlx_lm
from mlx_lm.sample_utils import make_sampler

model_path = "petergilani/MiniMax-M2.5-mix3-6bit"
model, tokenizer = mlx_lm.load(model_path)

sampler = make_sampler(temp=1.0, top_p=0.95, top_k=40)

prompt = "Your prompt here"
response = mlx_lm.generate(
    model, 
    tokenizer, 
    prompt=prompt,
    sampler=sampler,
    max_tokens=512
)
print(response)
```