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HomeLLMsnunchaku flux.1 krea dev

nunchaku flux.1 krea dev

by nunchaku-ai

Open source · 4k downloads · 120 likes

2.6
(120 reviews)ImageAPI & Local
About

Nunchaku Flux.1 Krea Dev is a text-to-image generation model optimized to produce high-quality visuals while remaining lightweight and efficient. Developed by the Nunchaku team, it is based on Black Forest Labs' FLUX.1-Krea-dev model but in a quantized version to reduce its memory footprint without sacrificing performance. It stands out for its ability to run on a variety of hardware configurations, including older GPUs, thanks to advanced compression techniques like SVDQuant. Ideal for artists, designers, or developers looking to integrate fast and precise image generation into their creative projects or applications, it offers a high-performance alternative to traditional models that consume more resources.

Documentation

Nunchaku Logo

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

visual This repository contains Nunchaku-quantized versions of FLUX.1-Krea-dev, designed to generate high-quality images from text prompts. It is optimized for efficient inference while maintaining minimal loss in performance.

Model Details

Model Description

  • Developed by: Nunchaku Team
  • Model type: text-to-image
  • License: flux-1-krea-dev-non-commercial-license
  • Quantized from model: FLUX.1-Krea-dev

Model Files

  • svdq-int4_r32-flux.1-krea-dev.safetensors: SVDQuant quantized INT4 FLUX.1-Krea-dev model. For users with non-Blackwell GPUs (pre-50-series).
  • svdq-fp4_r32-flux.1-krea-dev.safetensors: SVDQuant quantized NVFP4 FLUX.1-Krea-dev model. For users with Blackwell GPUs (50-series).

Model Sources

  • Inference Engine: nunchaku
  • Quantization Library: deepcompressor
  • Paper: SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models
  • Demo: demo.nunchaku.tech

Usage

  • Diffusers Usage: See flux.1-krea-dev.py. Just replace the safetensors with the ones from this repository. Check our tutorial for more advanced usage.
  • ComfyUI Usage: See nunchaku-flux.1-dev.json. Just replace the safetensors with the ones from this repository.

Performance

performance

Citation

Bibtex
@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.

Capabilities & Tags
diffuserstext-to-imageSVDQuantFLUX.1-Krea-devFLUX.1DiffusionQuantizationICLR2025en
Links & Resources
Specifications
CategoryImage
AccessAPI & Local
LicenseOpen Source
PricingOpen Source
Rating
2.6

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