File size: 1,491 Bytes
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license: apache-2.0
library_name: mlx
tags:
- language
- granite-4.1
- mlx
base_model: ibm-granite/granite-4.1-8b
pipeline_tag: text-generation
---
# granite-4.1-8b-mxfp8-mlx
Brainwaves
```brainwaves
arc arc/e boolq hswag obkqa piqa wino
mxfp8 0.486,0.666,0.875,0.636,0.450,0.766,0.631
```
# Other models in this size
gemma-4-E4B-it
```brainwaves
arc arc/e boolq hswag obkqa piqa wino
bf16 0.490,0.674,0.793,0.612,0.416,0.756,0.669
mxfp8 0.480,0.656,0.797,0.608,0.400,0.755,0.665
mxfp4 0.455,0.607,0.851,0.585,0.402,0.744,0.651
```
Qwen3.5-9B
```brainwaves
mxfp8 0.417,0.458,0.623,0.634,0.338,0.737,0.639
mxfp4 0.419,0.472,0.622,0.634,0.352,0.739,0.644
q8-hi 0.413,0.455,0.622,0.642,0.346,0.746,0.654
q8 0.418,0.455,0.622,0.643,0.342,0.748,0.659
```
This model [granite-4.1-8b-mxfp8-mlx](https://huggingface.co/granite-4.1-8b-mxfp8-mlx) was
converted to MLX format from [ibm-granite/granite-4.1-8b](https://huggingface.co/ibm-granite/granite-4.1-8b)
using mlx-lm version **0.31.3**.
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("granite-4.1-8b-mxfp8-mlx")
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)
```
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