Instructions to use SceneWorks/qwen-image-edit-2511-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SceneWorks/qwen-image-edit-2511-mlx with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SceneWorks/qwen-image-edit-2511-mlx", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - MLX
How to use SceneWorks/qwen-image-edit-2511-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir qwen-image-edit-2511-mlx SceneWorks/qwen-image-edit-2511-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Draw Things
- DiffusionBee
Qwen-Image-Edit-2511 โ MLX quant matrix (bf16 / Q8 / Q4)
Pre-quantized, MLX-ready repackagings of Qwen/Qwen-Image-Edit-2511
for the SceneWorks native Apple-Silicon worker (mlx-gen).
Each tier is a complete, self-contained turnkey snapshot that loads directly with no in-app
conversion peak (epic 8506).
| Tier | Subdir | What's packed | Approx. size |
|---|---|---|---|
| Q4 | q4/ |
transformer packed to 4-bit (group 64); dense bf16 TE + VAE | ~26 GB |
| Q8 | q8/ |
transformer packed to 8-bit (group 64); dense bf16 TE + VAE | ~36 GB |
| bf16 | bf16/ |
dense bf16 transformer + TE + VAE (full precision) | ~55 GB |
Only the transformer is quantized. The Qwen2.5-VL text encoder is skip_quantization
(quantization degrades its semantics) and the VAE is all-convolution (no quantizable leaves), so both
stay dense bf16 in every tier. Q4/Q8 use plain asymmetric group-affine quantization (group size 64),
byte-identical to the worker's load-time quantization.
This repo also backs qwen_image_edit_2511_lightning (same checkpoint, Lightning-distilled sampling).
License & attribution
Apache License 2.0, inherited from the upstream Qwen-Image-Edit-2511 release. The model weights are
ยฉ Alibaba Cloud / the Qwen team; this repository only re-packages them (quantization + MLX layout) and
adds no new training. See LICENSE. Original model card: https://huggingface.co/Qwen/Qwen-Image-Edit-2511
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Base model
Qwen/Qwen-Image-Edit-2511