---
title: nunchaku-flux.1-krea-dev
canonical_url: "https://www.modelscope.cn/models/nunchaku-tech/nunchaku-flux.1-krea-dev"
md_url: "https://www.modelscope.cn/models/nunchaku-tech/nunchaku-flux.1-krea-dev.md"
repository: nunchaku-tech/nunchaku-flux.1-krea-dev
last_updated: 2026-01-10
license: other
pipeline_tag: text-to-image-synthesis
tasks:
  - text-to-image-synthesis
base_model:
  - black-forest-labs/FLUX.1-Krea-dev
base_model_relation: quantized
parameters: 10.7B
tensor_type:
  - BF16
  - I8
  - F8_E4M3
  - I32
library_name:
  - lora
  - safetensors
  - pytorch
frameworks:
  - PyTorch
language:
  - en
downloads: 4041
stars: 6
tags:
  - text-to-image
  - SVDQuant
  - FLUX.1-Krea-dev
  - FLUX.1
  - Diffusion
  - Quantization
  - ICLR2025
---

# nunchaku-flux.1-krea-dev

> nunchaku-flux.1-krea-dev - nunchaku-tech 在 ModelScope 开源的模型。Model Card for nunchaku-flux.1-krea-dev

nunchaku-tech/nunchaku-flux.1-krea-dev 是 ModelScope 魔搭社区上的 10.7B 参数text-to-image-synthesis模型，采用 other 许可，基于 black-forest-labs/FLUX.1-Krea-dev 构建。

- **Repository**: nunchaku-tech/nunchaku-flux.1-krea-dev
- **License**: other
- **Tasks**: text-to-image-synthesis
- **Parameters**: 10.7B
- **Base model**: black-forest-labs/FLUX.1-Krea-dev
- **Tags**: text-to-image, SVDQuant, FLUX.1-Krea-dev, FLUX.1, Diffusion, Quantization, ICLR2025
- **Downloads**: 4041
- **Stars**: 6
- **Last updated**: 2026-01-10

Source: https://www.modelscope.cn/models/nunchaku-tech/nunchaku-flux.1-krea-dev

---

<p align="center" style="border-radius: 10px">
  <img src="https://huggingface.co/datasets/nunchaku-tech/cdn/resolve/main/nunchaku/assets/nunchaku_v2.png" width="30%" alt="Nunchaku Logo"/>
</p>

<div align="center">
  <a href=https://discord.gg/Wk6PnwX9Sm target="_blank"><img src=https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fdiscord.com%2Fapi%2Finvites%2FWk6PnwX9Sm%3Fwith_counts%3Dtrue&query=%24.approximate_member_count&logo=discord&logoColor=white&label=Discord&color=green&suffix=%20total height=22px></a>
  <a href=https://huggingface.co/datasets/nunchaku-tech/cdn/resolve/main/nunchaku/assets/wechat.jpg target="_blank"><img src=https://img.shields.io/badge/WeChat-07C160?logo=wechat&logoColor=white height=22px></a>
</div>

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

![visual](https://huggingface.co/datasets/nunchaku-tech/cdn/resolve/main/ComfyUI-nunchaku/workflows/nunchaku-flux.1-krea-dev.png)
This repository contains Nunchaku-quantized versions of [FLUX.1-Krea-dev](https://huggingface.co/black-forest-labs/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](https://huggingface.co/black-forest-labs/FLUX.1-Krea-dev/blob/main/LICENSE.md)
- **Quantized from model:** [FLUX.1-Krea-dev](https://huggingface.co/black-forest-labs/FLUX.1-Krea-dev)

### Model Files

- [`svdq-int4_r32-flux.1-krea-dev.safetensors`](./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`](./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](https://github.com/nunchaku-tech/nunchaku)
- **Quantization Library:** [deepcompressor](https://github.com/nunchaku-tech/deepcompressor)
- **Paper:** [SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models](http://arxiv.org/abs/2411.05007)
- **Demo:** [demo.nunchaku.tech](https://demo.nunchaku.tech)

## Usage

- Diffusers Usage: See [flux.1-krea-dev.py](https://github.com/nunchaku-tech/nunchaku/blob/main/examples/flux.1-krea-dev.py). Just replace the safetensors with the ones from this repository. Check our [tutorial](https://nunchaku.tech/docs/nunchaku/usage/basic_usage.html) for more advanced usage.
- ComfyUI Usage: See [nunchaku-flux.1-dev.json](https://nunchaku.tech/docs/ComfyUI-nunchaku/workflows/flux.html#nunchaku-flux-1-dev-json). Just replace the safetensors with the ones from this repository.

## Performance

![performance](https://huggingface.co/datasets/nunchaku-tech/cdn/resolve/main/nunchaku/assets/efficiency.jpg)

## 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.