---
license: apache-2.0
language:
- en
datasets:
- AIDC-AI/Ovis-dataset
base_model:
- AIDC-AI/Ovis2-2B
pipeline_tag: any-to-any
---

# Ovis-U1

<div align="center">
  <img src=https://cdn-uploads.huggingface.co/production/uploads/637aebed7ce76c3b834cea37/3IK823BZ8w-mz_QfeYkDn.png width="30%"/>
</div>

<p align="center">
  <a href="https://github.com/AIDC-AI/Ovis-U1/blob/main/docs/Ovis_U1_Report.pdf"><img src="https://img.shields.io/badge/Paper-Tech_Report-b31b1b" alt="paper"></a>
  <a href="https://github.com/AIDC-AI/Ovis-U1"><img src="https://img.shields.io/badge/GitHub-AIDC--AI/Ovis--U1-blue?style=flat&logo=github" alt="code"></a>
  <a href="https://huggingface.co/spaces/AIDC-AI/Ovis-U1-3B"><img src="https://img.shields.io/badge/🎨_HF_Spaces-AIDC--AI/Ovis--U1--3B-lightblack" alt="demo"></a>
  <a href="https://huggingface.co/AIDC-AI/Ovis-U1-3B"><img src="https://img.shields.io/badge/🤗_Model-AIDC--AI/Ovis--U1--3B-yellow" alt="model"></a>
</p>


<p align="left">
Building on the foundation of the Ovis series, Ovis-U1 is a 3-billion-parameter unified model that  seamlessly integrates <b>multimodal understanding</b>, <b>text-to-image generation</b>, and <b>image editing</b> within a single powerful framework. 
</p>


<p align="center">
  <img src="https://cdn-uploads.huggingface.co/production/uploads/636f4c6b5d2050767e4a1491/EmEEGmot9JzaBfHP2uWld.jpeg" width="95%">
  <br>
  <em>The overall architecture of Ovis-U1 (cf. Fig.2 in our report).</em>
</p>


## 📦 Installation

Ovis-U1 has been tested with Python 3.10, Torch 2.4.0, Transformers 4.51.3, and DeepSpeed 0.15.4. For a comprehensive list of package dependencies, please consult the requirements.txt file.

```bash
git clone git@github.com:AIDC-AI/Ovis-U1.git
conda create -n ovis-u1 python=3.10 -y
conda activate ovis-u1
cd Ovis-U1
pip install -r requirements.txt
pip install -e .

```


## 🛠️ Inference

For multimodal understanding, please run

```bash
python test_img_to_txt.py
```

For text-to-image, please run
```bash
python test_txt_to_img.py \
    --height 1024 \
    --width 1024  \
    --steps 50 \
    --seed 42 \
    --txt_cfg 5  
```

For image editing, please run
```bash
python test_img_edit.py \
    --steps 50 \
    --img_cfg 1.5 \
    --txt_cfg 6  
```

## 📊 Performance

#### OpenCompass Multi-modal Academic Benchmarks

| Model | Avg | MMB | MMS | MMMU | MathVista | Hallusion | AI2D | OCRBench | MMVet | 
|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
| GPT-4o | **75.4** | **86**  |**70.2** | **72.9** | **71.6** | **57** | **86.3** | 82.2 | **76.9** | 
| InternVL2.5-2B | 59.9 | 70.9 | 54.3 | 43.2 | 51.1 | 42.3 | 74.9 | 80.2 | 62.6 | 
| SAIL-VL-2B | 61 | 73.7 |56.5 | 44.1 | 62.8 | 45.9 | 77.4 | 83.1 | 44.2 | 
| InternVL3-2B | 61.1 | 78 |61.1 | 48.7 | 57.6 | 41.9 | 78.6 | 83.1 | <ins>67</ins> | 
| Qwen2.5-VL-3B | 64.5 | 76.8 | 56.3 | 51.2 | 61.2 | 46.6 | 81.4 | 82.8 | 60 | 
| Ovis2-2B | 65.2 | 76.9 | 56.7 | 45.6 | 64.1 | 50.2 | 82.7 | 87.3 | 58.3 | 
| SAIL-VL-1.5-2B | 67  | 78.5 | 62.6 | 46.4 | 67 | 50 | 83.7 | **89.1** | 58.8 | 
| Ristretto-3B | 67.7 | <ins>80.2</ins> | <ins>62.8</ins> | <ins>51.3</ins> | 67.6 | 50.2 | 84.2 | 84.7 | 60.7 | 
| Ovis-U1 |  <ins>69.6</ins>  | 77.8 |61.3 | 51.1 | <ins>69.4</ins> | <ins>56.3</ins> | <ins>85.6</ins> |  <ins>88.3</ins> | 66.7 | 

#### GenEval

| Model | Overall |Single object | Two object | Counting | Colors | Position | Attribute binding | 
|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
| GPT-4o | 0.84 | <ins>0.99</ins> | 0.92 | <ins>0.85</ins> | 0.92 | 0.75 | 0.61 | 
| BAGEL | 0.82  | <ins>0.99</ins> | 0.94 | 0.81 | 0.88 | 0.64 | 0.63 | 
| BAGEL 📝 | <ins>0.88</ins> | 0.98 | 0.95 | 0.84 | <ins>0.95</ins> | <ins>0.78</ins> | **0.77** |
| UniWorld-V1 | 0.80 | <ins>0.99</ins> | 0.93 | 0.79 | 0.89 | 0.49 | 0.70 |
| UniWorld-V1 📝 | 0.84 | 0.98 | 0.93 | 0.81 | 0.89 | 0.74 | 0.71 | 
| OmniGen | 0.68 |  0.98 | 0.84 | 0.66 | 0.74 | 0.40 | 0.43 | 
| OmniGen2 |0.80 |  **1** | 0.95 | 0.64 | 0.88 | 0.55 | <ins>0.76</ins> | 
| OmniGen2 📝 | 0.86 | <ins>0.99</ins> | <ins>0.96</ins> | 0.74 | **0.98** | 0.71 | 0.75 | 
| Ovis-U1 |**0.89** |  0.98 | **0.98** | **0.90** | 0.92 | **0.79** | 0.75 | 

*📝 denotes using the rewritten prompts*

#### DPG-Bench

| Model | Overall | Global | Entity | Attribute | Relation | Other | 
|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
| BAGEL | **85.07** | **88.94** | **90.37** | **91.29** | <ins>90.82</ins> | <ins>88.67</ins> | 
| UniWorld-V1 |81.38 |  83.64 | 88.39 | 88.44 | 89.27 | 87.22 | 
| OmniGen |81.16 | 87.90 | 88.97 | 88.47 | 87.95 | 83.56 | 
| OmniGen2 |83.57 | <ins>88.81</ins> | 88.83 | <ins>90.18</ins> | 89.37 | **90.27** | 
| Ovis-U1 | <ins>83.72</ins> | 82.37 | <ins>90.08</ins> | 88.68 | **93.35** | 85.20 |

#### ImgEdit-Bench

| Model | Overall |Add | Adjust | Extract | Replace | Remove | Background | Style | Hybrid | Action | 
|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
| GPT-4o | **4.2** | **4.61** | **4.33** | <ins>2.9</ins> | <ins>4.35</ins> | <ins>3.66</ins> | **4.57** | **4.93** | **3.96** | **4.89** | 
| MagicBrush | 1.90 | 2.84 | 1.58 | 1.51 | 1.97 | 1.58 | 1.75 | 2.38 | 1.62 | 1.22 | 
| Instruct-P2P | 1.88 | 2.45 | 1.83 | 1.44 | 2.01 | 1.50 | 1.44 | 3.55 | 1.2 | 1.46 | 
| AnyEdit | 2.45 | 3.18 | 2.95 | 1.88 | 2.47 | 2.23 | 2.24 | 2.85 | 1.56 | 2.65 | 
| UltraEdit |2.7 | 3.44 | 2.81 | 2.13 | 2.96 | 1.45 | 2.83 | 3.76 | 1.91 | 2.98 | 
| OmniGen |  2.96 | 3.47 | 3.04 | 1.71 | 2.94 | 2.43 | 3.21 | 4.19 | 2.24 | 3.38 |
| Step1X-Edit |3.06 |  3.88 | 3.14 | 1.76 | 3.40 | 2.41 | 3.16 | 4.63 | 2.64 | 2.52 | 
| ICEdit |3.05 | 3.58 | 3.39 | 1.73 | 3.15 | 2.93 | 3.08 | 3.84 | 2.04 | 3.68 | 
| BAGEL |3.2 | 3.56 | 3.31 | 1.7 | 3.3 | 2.62 | 3.24 | 4.49 | 2.38 | 4.17 | 
| UniWorld-V1 |3.26 | 3.82 | 3.64 | 2.27 | 3.47 | 3.24 | 2.99 | 4.21 | 2.96 | 2.74 | 
| OmniGen2 | 3.44 | 3.57 | 3.06 | 1.77 | 3.74 | 3.2 | 3.57 | <ins>4.81</ins> | 2.52 | <ins>4.68</ins> |
| Ovis-U1 |<ins>4.00</ins> | <ins>4.13</ins> | <ins>3.62</ins> | **2.98** | **4.45** | **4.06** | <ins>4.22</ins> | 4.69 | <ins>3.45</ins> | 4.61 | 


#### GEdit-Bench-EN

|  Model | Avg | Background Change | Color Alteration   | Material Modification  | Motion Change | Portrait Beautification  | Style Transfer  | Subject Addition  | Subject Removal  | Subject Replacement  | Text Modification  | Tone Transformation  | 
|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
| GPT-4o |**7.534** | 7.205 |	6.491 |	**6.607** | **8.096** |	**7.768** |	<ins>6.961</ins> |	7.622 |	**8.331** |	**8.067** |	**7.427** |	**8.301** |	
| AnyEdit | 3.212 | 4.663	| 4.260 |	2.537 |	2.024 |	3.479	| 2.032 |	3.995 |	3.089 |	3.180 |	0.922 |	5.151 |	
| Instruct-Pix2Pix | 	3.684 | 3.825 |	5.182 |	3.688 |	3.509 |	4.339 |	4.560 |	3.461 |	2.031 |	4.237 |	0.955 |	4.733 |
| MagicBrush |4.518 |	5.637 |	5.136 |	5.078 |	4.513 |	4.487 |	4.439 |	5.252 |	3.704 |	4.941 |	1.384 |	5.130 |	
| OmniGen | 5.062 | 5.281 |	6.003 |	5.308 |	2.916 |	3.087 |	4.903 |	6.628 |	6.352 |	5.616 |	4.519 |	5.064 |	
| Gemini |6.315 | 	6.781 |	6.369 |	6.040 |	6.938 |	5.591 |	4.676 |	7.501 |	6.447 |	7.003 |	5.765 |	6.350 |	
| Step1X-Edit |	6.701 | 6.547 |	6.545 |	6.204 |	6.483 |	6.787 |	**7.221** |	6.975 |	6.512 |	7.068 |	<ins>6.921</ins> |	6.448 |	
| Doubao |<ins>6.754</ins> | 	<ins>7.430</ins> |	**7.095** |	6.339 |	<ins>6.973</ins> |	<ins>6.972</ins> |	6.767 |	<ins>7.674</ins> |	6.748 |	<ins>7.447</ins> |	3.471 |	<ins>7.383</ins> |	
| BAGEL | 6.519 | 7.324 |	<ins>6.909</ins> |	<ins>6.381</ins> |	4.753 |	4.573 |	6.150 |	**7.896** |	7.164 |	7.021 |	7.320 |	6.218 |	
| Ovis-U1 |6.420 | **7.486** |	6.879 |	6.208 |	4.790 |	5.981 |	6.463 |	7.491 |	<ins>7.254</ins> |	7.266 |	4.482 |	6.314 |	


## 📚 Citation

If you find Ovis-U1 useful, please cite our paper:

```bibtex
@inproceedings{wang2025ovisu1,
title={Ovis-U1 Technical Report},
author={Ovis Team},
year={2025}
}
```

## 🙏 Acknowledgments

The code is built upon [Ovis](https://github.com/AIDC-AI/Ovis) and [FLUX](https://github.com/black-forest-labs/flux).

## 📄 License

The project is released under Apache License 2.0 (http://www.apache.org/licenses/LICENSE-2.0, SPDX-License-identifier: Apache-2.0).

## 🚨 Disclaimer

We used compliance checking algorithms during the training process, to ensure the compliance of the trained model to the best of our ability. Due to complex data and the diversity of language model usage scenarios, we cannot guarantee that the model is completely free of copyright issues or improper content. If you believe anything infringes on your rights or generates improper content, please contact us, and we will promptly address the matter.