--- base_model: Qwen/Qwen3.5-4B library_name: mlx tags: - mlx - qwen3.5 - vision-language-model - bf16 - bfloat16 license: apache-2.0 --- # Qwen3.5-4B-MLX-bf16 This is a full-precision (bfloat16) MLX version of [Qwen/Qwen3.5-4B](https://huggingface.co/Qwen/Qwen3.5-4B) for Apple Silicon. ## Model Details - **Original Model:** [Qwen/Qwen3.5-4B](https://huggingface.co/Qwen/Qwen3.5-4B) - **Precision:** bfloat16 (no quantization) - **Format:** MLX SafeTensors - **Framework:** [mlx-vlm](https://github.com/Blaizzy/mlx-vlm) - **Disk Size:** ~8.5 GB ## Conversion Details This model was converted using `mlx-vlm` from the [`pc/fix-qwen35-predicate`](https://github.com/Blaizzy/mlx-vlm/tree/pc/fix-qwen35-predicate) branch, which includes fixes for Qwen3.5 model support (proper handling of MoE gate layers, `shared_expert_gate`, and `A_log` casting). **Conversion command:** ```bash python3 -m mlx_vlm convert \ --hf-path "Qwen/Qwen3.5-4B" \ --mlx-path "./mlx_models/Qwen3.5-4B-MLX-bf16" ``` ## 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. ## Related Models - **8-bit quantized version:** [mlx-community/Qwen3.5-4B-MLX-8bit](https://huggingface.co/mlx-community/Qwen3.5-4B-MLX-8bit) ## Usage ```python from mlx_vlm import load, generate model, processor = load("mlx-community/Qwen3.5-4B-MLX-bf16") 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/Qwen3.5-4B-MLX-bf16 \ --prompt "Describe this image" \ --image path/to/image.jpg \ --max-tokens 200 ``` ## License This model inherits the [Apache 2.0 license](https://huggingface.co/Qwen/Qwen3.5-4B/blob/main/LICENSE) from the original Qwen3.5-4B model.