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base_model: Qwen/Qwen3.5-9B
library_name: mlx
pipeline_tag: image-text-to-text
tags:
- mlx
- qwen3.5
- vision-language-model
- quantized
- 4bit
license: apache-2.0
---
# Qwen3.5-9B-MLX-4bit
This is a quantized MLX version of [Qwen/Qwen3.5-9B](https://huggingface.co/Qwen/Qwen3.5-9B) for Apple Silicon.
## Model Details
- **Original Model:** [Qwen/Qwen3.5-9B](https://huggingface.co/Qwen/Qwen3.5-9B)
- **Quantization:** 4-bit (~5.059 bits per weight)
- **Group Size:** 64
- **Format:** MLX SafeTensors
- **Framework:** [mlx-vlm](https://github.com/Blaizzy/mlx-vlm)
## Conversion Details
This model was converted using `mlx-vlm` with 4-bit quantization.
**Conversion command:**
```bash
python3 -m mlx_vlm convert \
--hf-path "Qwen/Qwen3.5-9B" \
--mlx-path "./mlx_models/Qwen3.5-9B-MLX-4bit" \
-q --q-bits 4 --q-group-size 64
```
## Important Note
A better, more optimized conversion may be available from **@Prince** ([@Blaizzy](https://huggingface.co/Blaizzy)) in the MLX VLM community. Check the [mlx-community](https://huggingface.co/mlx-community) organization for updated versions as official Qwen3.5 support is merged into the main `mlx-vlm` branch.
## Usage
```python
from mlx_vlm import load, generate
model, processor = load("mlx-community/Qwen3.5-9B-MLX-4bit")
output = generate(
model,
processor,
prompt="Describe this image in detail",
image="path/to/image.jpg",
max_tokens=200
)
print(output)
```
Or from the command line:
```bash
mlx_vlm generate \
--model mlx-community/Qwen3.5-9B-MLX-4bit \
--prompt "Describe this image" \
--image path/to/image.jpg \
--max-tokens 200
```
## Performance
- **Disk Size:** ~5.6 GB
- Runs efficiently on Apple Silicon Macs (M1/M2/M3/M4)
- Lower memory footprint compared to 8-bit quantization
## License
This model inherits the [Apache 2.0 license](https://huggingface.co/Qwen/Qwen3.5-9B/blob/main/LICENSE) from the original Qwen3.5-9B model.
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