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Hunyuan3D-2GP: 3D Generation for the GPU Poor

GPU Poor version by DeepBeepMeep. This great video generator can now run smoothly with less than 6 GB of VRAM.

This is another integration of the mmgp module that allows easy to setup advanced and fast offloading.
https://github.com/deepbeepmeep/mmgp

πŸ”₯ News

  • Mar 18, 2025: πŸ’¬ Hunyuan3D-2.0GP by Deepbeepmeep: Support for Hunyuan3D turbo models

  • Mar 18, 2025: πŸ’¬ Hunyuan3D-2.0GP by Deepbeepmeep: Support for Hunyuan3D-2mv and Hunyuan3D-2mini

  • Jan 25, 2025: πŸ’¬ Hunyuan3D-2.0GP by Deepbeepmeep: Synced code with original repo.Many thanks to YanWenKun for the work.

  • Jan 23, 2025: πŸ’¬ Hunyuan3D-2.0GP by Deepbeepmeep: added lighning fix in rendering window

  • Jan 23, 2025: πŸ’¬ Hunyuan3D-2.0GP by Deepbeepmeep: added Windows support thanks to MrForExample and sdbds + omitted optimization that keeps under VRAM 6GB with profile 4 or 5

  • Jan 22, 2025: πŸ’¬ Hunyuan3D-2.0GP by Deepbeepmeep: low VRAM support and unlocked text to 3D generator

  • Jan 21, 2025: πŸ’¬ Release Hunyuan3D 2.0. Please give it a try!

  • Mar 19, 2025: πŸ€— Release turbo model Hunyuan3D-2-Turbo, Hunyuan3D-2mini-Turbo and FlashVDM.

  • Mar 18, 2025: πŸ€— Release multiview shape model Hunyuan3D-2mv and 0.6B shape model Hunyuan3D-2mini.

  • Feb 14, 2025: πŸ› οΈ Release texture enhancement module, please obtain high-definition textures via here!

  • Feb 3, 2025: 🐎 Release Hunyuan3D-DiT-v2-0-Fast, our guidance distillation model that could half the dit inference time, see here for usage.

  • Jan 27, 2025: πŸ› οΈ Release Blender addon for Hunyuan3D 2.0, Check it out here.

  • Jan 23, 2025: πŸ’¬ We thank community members for creating Windows installation tool, ComfyUI support with ComfyUI-Hunyuan3DWrapper and ComfyUI-3D-Pack and other awesome extensions.

  • Jan 21, 2025: πŸ’¬ Enjoy exciting 3D generation on our website Hunyuan3D Studio!

  • Jan 21, 2025: πŸ€— Release inference code and pretrained models of Hunyuan3D 2.0. Please give it a try via huggingface space and our official site!

Abstract

We present Hunyuan3D 2.0, an advanced large-scale 3D synthesis system for generating high-resolution textured 3D assets. This system includes two foundation components: a large-scale shape generation model - Hunyuan3D-DiT, and a large-scale texture synthesis model - Hunyuan3D-Paint. The shape generative model, built on a scalable flow-based diffusion transformer, aims to create geometry that properly aligns with a given condition image, laying a solid foundation for downstream applications. The texture synthesis model, benefiting from strong geometric and diffusion priors, produces high-resolution and vibrant texture maps for either generated or hand-crafted meshes. Furthermore, we build Hunyuan3D-Studio - a versatile, user-friendly production platform that simplifies the re-creation process of 3D assets. It allows both professional and amateur users to manipulate or even animate their meshes efficiently. We systematically evaluate our models, showing that Hunyuan3D 2.0 outperforms previous state-of-the-art models, including the open-source models and closed-source models in geometry details, condition alignment, texture quality, and e.t.c.

How to run the Gradio app

  1. Follow the installation instructions below

  2. Enter either one of the commande lines in bash session

To run the Hunyuan3D-2mini (low VRAM) image to 3D generator:

python gradio_app.py 

To run the Hunyuan3D-2mv (multi views) image to 3D generator:

python gradio_app.py --mv

To run the text to 3D generator (an extension of the mini generator):

python gradio_app.py --enable_t23d

To run the original Hunyuan3D-2 image to 3D generator:

python gradio_app.py --h2

To use the Turbo version of one specific model, add --turbo. For instance to run the turbo Hunyuan3D-2mv (multi views) image to 3D generator:

python gradio_app.py --mv --turbo

By default the memory profile assumes 9 GB of VRAM (profile 3). If you have less but at least 6 GB of VRAM add --profile 4

To run the image to 3D generator with optimized memory management:

python gradio_app.py --profile 3

To run the text to 3D generator with optimized memory management:

python gradio_app.py --enable_t23d --profile 4

You can choose between 5 profiles depending on your hardware:

  • HighRAM_HighVRAM (1)
  • HighRAM_LowVRAM (2)
  • LowRAM_HighVRAM (3)
  • LowRAM_LowVRAM (4)
  • VerylowRAM_LowVRAM (5)

Each profile's name describes the targeted level of RAM and VRAM consumptions.
Usualy the lower the profile number the faster the generation.

Other GPU Poor Applications

Architecture

Hunyuan3D 2.0 features a two-stage generation pipeline, starting with the creation of a bare mesh, followed by the synthesis of a texture map for that mesh. This strategy is effective for decoupling the difficulties of shape and texture generation and also provides flexibility for texturing either generated or handcrafted meshes.

Performance

We have evaluated Hunyuan3D 2.0 with other open-source as well as close-source 3d-generation methods. The numerical results indicate that Hunyuan3D 2.0 surpasses all baselines in the quality of generated textured 3D assets and the condition following ability.

Model CMMD(⬇) FID_CLIP(⬇) FID(⬇) CLIP-score(⬆)
Top Open-source Model1 3.591 54.639 289.287 0.787
Top Close-source Model1 3.600 55.866 305.922 0.779
Top Close-source Model2 3.368 49.744 294.628 0.806
Top Close-source Model3 3.218 51.574 295.691 0.799
Hunyuan3D 2.0 3.193 49.165 282.429 0.809

Generation results of Hunyuan3D 2.0:

🎁 Models Zoo

It takes 6 GB VRAM for shape generation and 24.5 GB for shape and texture generation in total.

Hunyuan3D-2mini Series

Model Description Date Size Huggingface
Hunyuan3D-DiT-v2-mini-Turbo Step Distillation Version 2025-03-19 0.6B Download
Hunyuan3D-DiT-v2-mini-Fast Guidance Distillation Version 2025-03-18 0.6B Download
Hunyuan3D-DiT-v2-mini Mini Image to Shape Model 2025-03-18 0.6B Download

Hunyuan3D-2mv Series

Model Description Date Size Huggingface
Hunyuan3D-DiT-v2-mv-Turbo Step Distillation Version 2025-03-19 1.1B Download
Hunyuan3D-DiT-v2-mv-Fast Guidance Distillation Version 2025-03-18 1.1B Download
Hunyuan3D-DiT-v2-mv Multiview Image to Shape Model 2025-03-18 1.1B Download

Hunyuan3D-2 Series

Model Description Date Size Huggingface
Hunyuan3D-DiT-v2-0-Turbo Step Distillation Model 2025-03-19 1.1B Download
Hunyuan3D-DiT-v2-0-Fast Guidance Distillation Model 2025-02-03 1.1B Download
Hunyuan3D-DiT-v2-0 Image to Shape Model 2025-01-21 1.1B Download
Hunyuan3D-Paint-v2-0 Texture Generation Model 2025-01-21 1.3B Download
Hunyuan3D-Delight-v2-0 Image Delight Model 2025-01-21 1.3B Download

πŸ€— Get Started with Hunyuan3D 2.0

You may follow the next steps to use Hunyuan3D 2.0 via:

Install Requirements

To use the application on Windows (without WSL) you will need to install Microsoft Visual Studio 2022 or later. If you get an error during the execution of onr of the python setup.py below you will need to set the path to the C++ compiler by running the following script (once you have located the installation path of VS Studio which may differ):

"C:\Program Files\Microsoft Visual Studio\2022\Community\Common7\Tools\VsDevCmd" -arch=x64 

In any case please make sure you have Python 3.10 installed, you may create a conda environnment:

conda create -n Hunyuan3D-2GP python==3.10.9 

Then install the required libraries:

pip install torch==2.5.1 torchvision torchaudio --index-url https://download.pytorch.org/whl/test/cu124
pip install -r requirements.txt
# for texture
cd hy3dgen/texgen/custom_rasterizer
python3 setup.py install
cd ../../..
cd hy3dgen/texgen/differentiable_renderer
python3 setup.py install

Code Usage

We designed a diffusers-like API to use our shape generation model - Hunyuan3D-DiT and texture synthesis model - Hunyuan3D-Paint.

You could assess Hunyuan3D-DiT via:

from hy3dgen.shapegen import Hunyuan3DDiTFlowMatchingPipeline

pipeline = Hunyuan3DDiTFlowMatchingPipeline.from_pretrained('tencent/Hunyuan3D-2')
mesh = pipeline(image='assets/demo.png')[0]

The output mesh is a trimesh object, which you could save to glb/obj (or other format) file.

For Hunyuan3D-Paint, do the following:

from hy3dgen.texgen import Hunyuan3DPaintPipeline
from hy3dgen.shapegen import Hunyuan3DDiTFlowMatchingPipeline

# let's generate a mesh first
pipeline = Hunyuan3DDiTFlowMatchingPipeline.from_pretrained('tencent/Hunyuan3D-2')
mesh = pipeline(image='assets/demo.png')[0]

pipeline = Hunyuan3DPaintPipeline.from_pretrained('tencent/Hunyuan3D-2')
mesh = pipeline(mesh, image='assets/demo.png')

Please visit examples folder for more advanced usage, such as multiview image to 3D generation and * texture generation for handcrafted mesh*.

API Server

You could launch an API server locally, which you could post web request for Image/Text to 3D, Texturing existing mesh, and e.t.c.

python api_server.py --host 0.0.0.0 --port 8080

A demo post request for image to 3D without texture.

img_b64_str=$(base64 -i assets/demo.png)
curl -X POST "http://localhost:8080/generate" \
     -H "Content-Type: application/json" \
     -d '{
           "image": "'"$img_b64_str"'",
         }' \
     -o test2.glb

Blender Addon

With an API server launched, you could also directly use Hunyuan3D 2.0 in your blender with our Blender Addon. Please follow our tutorial to install and use.

blender_addon.mp4

Official Site

Don't forget to visit Hunyuan3D for quick use, if you don't want to host yourself.

πŸ“‘ Open-Source Plan

  • Inference Code
  • Model Checkpoints
  • ComfyUI
  • TensorRT Version

πŸ”— BibTeX

If you found this repository helpful, please cite our report:

@misc{hunyuan3d22025tencent,
    title={Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation},
    author={Tencent Hunyuan3D Team},
    year={2025},
    eprint={2501.12202},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}

@misc{yang2024hunyuan3d,
    title={Hunyuan3D 1.0: A Unified Framework for Text-to-3D and Image-to-3D Generation},
    author={Tencent Hunyuan3D Team},
    year={2024},
    eprint={2411.02293},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}

Community Resources

Thanks for the contributions of community members, here we have these great extensions of Hunyuan3D 2.0:

Acknowledgements

We would like to thank the contributors to the Trellis, DINOv2, Stable Diffusion, FLUX, diffusers, HuggingFace, CraftsMan3D, and Michelangelo repositories, for their open research and exploration.

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