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SceneWorks/qwen-image-edit-2511-mlx
qwen-image-edit-2511-mlx is a text-to-image model from SceneWorks. Use it when you need an image from a text prompt. It is set up for diffusers. The card lists the license as apache-2.0.
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…
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Updated Jun 30, 2026
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From the Hugging Face model README
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).
Apache License 2.0, inherited from the upstream Qwen-Image-Edit-2511 release. The model weights are
© 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