加载中…
加载中…
transformer/1.safetensors 2.1 GBtransformer/4.safetensors 2.1 GBtext_encoder/5.safetensors 2.1 GBtext_encoder/3.safetensors 2.1 GBtext_encoder/1.safetensors 2.1 GBtransformer/0.safetensors 2.1 GBtransformer/3.safetensors 2.1 GBtransformer/5.safetensors 2.1 GBtransformer/2.safetensors 2.1 GBtext_encoder/0.safetensors 2.1 GBtext_encoder/4.safetensors 2.1 GBtext_encoder/2.safetensors 2.1 GBtext_encoder/6.safetensors 1.5 GBtransformer/6.safetensors 450 MBvae/0.safetensors 254 MBThis is a Q4 MFlux version of Qwen-Image-2512.
MFlux runs the latest state-of-the-art generative image models locally on your Mac in native MLX. MFlux is open source and free.
[!NOTE] Community conversion by MFlux-Community -- not an official release from the original model's authors. The original model's license applies unchanged, see License.
| QUANT | GB | Repo |
|---|---|---|
| BF16 | 55.3 | mflux-community/qwen-image-2512-mflux-bf16 |
| Q8 | 36.1 | mflux-community/qwen-image-2512-mflux-q8 |
| Q6 | 31.0 | mflux-community/qwen-image-2512-mflux-q6 |
| Q5 | 28.5 | mflux-community/qwen-image-2512-mflux-q5 |
| Q4 | 27.6 | this repo |
| Q3 | 23.4 | mflux-community/qwen-image-2512-mflux-q3 |
Converted with MFlux 0.22.0 on 2026-10-11.
Standard MFlux quantization uses MLX affine quantization (4-bit) across the text encoder, transformer and VAE. The quantization level is stored in the weights, so no --quantize flag is needed.
Install MFlux
uv tool install --upgrade mflux
Generate an image using Qwen-Image-2512 Q4:
mflux-generate-qwen \
--model mflux-community/qwen-image-2512-mflux-q4 \
--base-model qwen-image \
--prompt "A puffin standing on a cliff" \
--width 1024 \
--height 1024 \
--seed 42 \
--output image.png
The weights are downloaded from this repo on first use. To keep a local copy instead:
hf download mflux-community/qwen-image-2512-mflux-q4 --local-dir ./qwen-image-2512-mflux-q4
then pass --model ./qwen-image-2512-mflux-q4.
This repo inherits the license of the original model: apache-2.0. See the original model card for the full terms and any usage restrictions. The weights here were modified from the original release only by conversion to MLX and quantization.