nunchaku-ai/nunchaku-flux.1-kontext-dev

Model

Model Card for nunchaku-flux.1-kontext-dev

66

7 commits

3 linked in READMEs

updated Nov 16, 2025

See the code

README

Nunchaku Logo

Model Card for nunchaku-flux.1-kontext-dev

visual This repository contains Nunchaku-quantized versions of FLUX.1-Kontext-dev, capable of editing images based on text instructions. It is optimized for efficient inference while maintaining minimal loss in performance.

Model Details

Model Description

Model Files

Model Sources

Usage

Performance

performance

Citation

@inproceedings{
  li2024svdquant,
  title={SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models},
  author={Li*, Muyang and Lin*, Yujun and Zhang*, Zhekai and Cai, Tianle and Li, Xiuyu and Guo, Junxian and Xie, Enze and Meng, Chenlin and Zhu, Jun-Yan and Han, Song},
  booktitle={The Thirteenth International Conference on Learning Representations},
  year={2025}
}

Attribution Notice

The FLUX.1 [dev] Model is licensed by Black Forest Labs Inc. under the FLUX.1 [dev] Non-Commercial License. Copyright Black Forest Labs Inc. IN NO EVENT SHALL BLACK FOREST LABS INC. BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH USE OF THIS MODEL.

diffusers
Diffusion
FLUX.1
FLUX.1-Kontext-dev
ICLR2025
image-to-image
Quantization
SVDQuant

Contributors

Lmxyy

7 commits

nunchaku-ai/nunchaku-flux.1-kontext-dev

Model

Model Card for nunchaku-flux.1-kontext-dev

66

7 commits

3 linked in READMEs

updated Nov 16, 2025

See the code

README

Nunchaku Logo

Model Card for nunchaku-flux.1-kontext-dev

visual This repository contains Nunchaku-quantized versions of FLUX.1-Kontext-dev, capable of editing images based on text instructions. It is optimized for efficient inference while maintaining minimal loss in performance.

Model Details

Model Description

Model Files

Model Sources

Usage

Performance

performance

Citation

@inproceedings{
  li2024svdquant,
  title={SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models},
  author={Li*, Muyang and Lin*, Yujun and Zhang*, Zhekai and Cai, Tianle and Li, Xiuyu and Guo, Junxian and Xie, Enze and Meng, Chenlin and Zhu, Jun-Yan and Han, Song},
  booktitle={The Thirteenth International Conference on Learning Representations},
  year={2025}
}

Attribution Notice

The FLUX.1 [dev] Model is licensed by Black Forest Labs Inc. under the FLUX.1 [dev] Non-Commercial License. Copyright Black Forest Labs Inc. IN NO EVENT SHALL BLACK FOREST LABS INC. BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH USE OF THIS MODEL.

diffusers
Diffusion
FLUX.1
FLUX.1-Kontext-dev
ICLR2025
image-to-image
Quantization
SVDQuant

Contributors

Lmxyy

7 commits