Instructions to use mlx-community/Qwen-Image-2.1-mflux-q4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- mflux
How to use mlx-community/Qwen-Image-2.1-mflux-q4 with mflux:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- MLX
How to use mlx-community/Qwen-Image-2.1-mflux-q4 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Qwen-Image-2.1-mflux-q4 mlx-community/Qwen-Image-2.1-mflux-q4
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Qwen-Image-2.1 mflux q4
Native MLX/mflux q4 conversion of Qwen/Qwen-Image-2.1 for Apple silicon.
The transformer and Qwen3-VL text encoder are both stored in MLX affine 4-bit
format; the VAE uses the mflux Qwen Image 2.1 layout.
This checkpoint was converted from upstream revision
790c92633540aa0cb11d9abf19eb46d861714758 with mflux 0.20.0 and MLX 0.32.2.
It is intended for the reviewed low-memory loader in Rapid-MLX. Stock mflux
0.20.0 skips text-encoder quantization and cannot load this pack without that
loader change.
Measured during feasibility testing on a Mac Studio:
- 512x512, 40 steps: 4.68 GiB peak MLX memory
- 1024x1024, 4 steps: 5.14 GiB peak MLX memory
- packaged size: approximately 8.9 GB
These measurements used prompt materialization, encoder/transformer eviction, a zero MLX cache, and tiled VAE decoding. Physical 8 GB and 16 GB Mac release qualification is still required.
The original model and this conversion are licensed under Apache-2.0. See
LICENSE and the upstream model.
- Downloads last month
- 39
Quantized
Model tree for mlx-community/Qwen-Image-2.1-mflux-q4
Base model
Qwen/Qwen-Image-2.1