---
license: other
license_name: nsclv1
license_link: LICENSE
tags:
- image-generation
- text-to-image
- diffusion
- pixel-space
- dit
library_name: pytorch
pipeline_tag: text-to-image
---

<p align="center">
  <img src="https://raw.githubusercontent.com/NVlabs/PixelDiT/master/assets/pixeldit-logo.png" height="60" />
</p>

<h2 align="center">PixelDiT: Pixel Diffusion Transformers for Image Generation</h2>

<p align="center">
  <a href="https://www.yongshengyu.com/">Yongsheng Yu</a><sup>1,2</sup> &nbsp;
  <a href="https://wxiong.me/">Wei Xiong</a><sup>1†</sup> &nbsp;
  <a href="https://weilinie.github.io/">Weili Nie</a><sup>1</sup> &nbsp;
  <a href="https://shengcn.github.io/">Yichen Sheng</a><sup>1</sup> &nbsp;
  <a href="http://behindthepixels.io/">Shiqiu Liu</a><sup>1</sup> &nbsp;
  <a href="https://www.cs.rochester.edu/u/jluo/">Jiebo Luo</a><sup>2</sup>
</p>
<p align="center">
  <sup>1</sup>NVIDIA &nbsp; <sup>2</sup>University of Rochester
  <br>
  <sup>†</sup>Project Lead and Main Advising
</p>

<p align="center">
  <a href="https://pixeldit.github.io/"><img src="https://img.shields.io/badge/Website-Project_Page-2ea44f" /></a>
  &nbsp;
  <a href="https://arxiv.org/abs/2511.20645"><img src="https://img.shields.io/badge/arXiv-2511.20645-b31b1b.svg" /></a>
  &nbsp;
  <a href="https://github.com/NVlabs/PixelDiT"><img src="https://img.shields.io/badge/GitHub-Code-blue" /></a>
</p>

### Key Features

- **VAE-free**
- **Dual-level architecture**: Patch-level DiT + Pixel-level DiT
- **MM-DiT text-image fusion**: Joint attention between text and image tokens
- **Text encoder**: Gemma-2-2B-IT
- **Multi-aspect-ratio**: Supports various aspect ratios at 1024px

## Usage

### Installation

```bash
pip install -r requirements.txt
```

### Inference

```python
# See the full inference script at: https://github.com/NVlabs/PixelDiT
cd t2i/
python inference.py \
  --config configs/PixelDiT_1024px_pixel_diffusion_stage3.yaml \
  --model_path PixelDiT-T2I-v1.pth \
  --txt_file prompts.txt \
  --custom_height 1024 --custom_width 1024 \
  --cfg_scale 2.75 --seed 2025 \
  --negative_prompt "low quality, worst quality, over-saturated, blurry, deformed, watermark" \
  --work_dir "."
```

### Inference Parameters

| Parameter | Default | Description |
|-----------|---------|-------------|
| `--cfg_scale` | 3.5 | Classifier-free guidance scale |
| `--step` | 50 | Number of sampling steps (25 for fast, 50 for quality) |
| `--seed` | 0 | Random seed |
| `--negative_prompt` | `""` | Negative prompt for CFG |
| `--interval_guidance` | [0, 1] | CFG application interval |
| `--sampling_algo` | flow_dpm-solver | Sampling algorithm |

## Model Architecture

| Component | Value |
|-----------|-------|
| Parameters | 1.3B |
| Patch size | 16 |
| Hidden size | 1536 |
| Attention heads | 24 |
| Patch-level depth | 14 |
| Pixel-level depth | 2 |
| Pixel hidden size | 16 |
| Pixel attention hidden size | 1152 |
| Text embedding dim | 2304 |
| Text max length | 300 |
| Text encoder | Gemma-2-2B-IT |

## Citation

```bibtex
@inproceedings{yu2026pixeldit,
      title={PixelDiT: Pixel Diffusion Transformers for Image Generation},
      author={Yongsheng Yu and Wei Xiong and Weili Nie and Yichen Sheng and Shiqiu Liu and Jiebo Luo},
      booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
      year={2026},
}
```

## License

This model is released under the [NSCLv1 License](LICENSE). The work and any derivative works may only be used for non-commercial (research or evaluation) purposes.