• Jun 19, 2025: 👋 We present the technical report of Hunyuan3D-2.1, please check out the details and spark some discussion!
• Jun 13, 2025: 🤗 We release the first production-ready 3D asset generation model, Hunyuan3D-2.1!

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Tencent Hunyuan3D-2.1 is a scalable 3D asset creation system that advances state-of-the-art 3D generation through two pivotal innovations: Fully Open-Source Framework and Physically-Based Rendering (PBR) Texture Synthesis. For the first time, the system releases full model weights and training code, enabling community developers to directly fine-tune and extend the model for diverse downstream applications. This transparency accelerates academic research and industrial deployment. Moreover, replacing the prior RGB-based texture model, the upgraded PBR pipeline leverages physics-grounded material simulation to generate textures with photorealistic light interaction (e.g., metallic reflections, subsurface scattering).

We have evaluated Hunyuan3D 2.1 with other open-source as well as close-source 3d-generation methods. The numerical results indicate that Hunyuan3D 2.1 surpasses all baselines in the quality of generated textured 3D assets and the condition following ability.

Model	ULIP-T(⬆)	ULIP-I(⬆)	Uni3D-T(⬆)	Uni3D-I(⬆)
Michelangelo	0.0752	0.1152	0.2133	0.2611
Craftsman	0.0745	0.1296	0.2375	0.2987
TripoSG	0.0767	0.1225	0.2506	0.3129
Step1X-3D	0.0735	0.1183	0.2554	0.3195
Trellis	0.0769	0.1267	0.2496	0.3116
Direct3D-S2	0.0706	0.1134	0.2346	0.2930
Hunyuan3D-Shape-2.1	0.0774	0.1395	0.2556	0.3213

Model	CLIP-FiD(⬇)	CMMD(⬇)	CLIP-I(⬆)	LPIPS(⬇)
SyncMVD-IPA	28.39	2.397	0.8823	0.1423
TexGen	28.24	2.448	0.8818	0.1331
Hunyuan3D-2.0	26.44	2.318	0.8893	0.1261
Hunyuan3D-Paint-2.1	24.78	2.191	0.9207	0.1211

It takes 10 GB VRAM for shape generation, 21GB for texture generation and 29GB for shape and texture generation in total.

Model	Description	Date	Size	Huggingface
Hunyuan3D-Shape-v2-1	Image to Shape Model	2025-06-14	3.3B	Download
Hunyuan3D-Paint-v2-1	Texture Generation Model	2025-06-14	2B	Download

Hunyuan3D 2.1 supports Macos, Windows, Linux. You may follow the next steps to use Hunyuan3D 2.1 via:

We test our model on an A100 GPU with Python 3.10 and PyTorch 2.5.1+cu124.

pip install torch==2.5.1 torchvision==0.20.1 torchaudio==2.5.1 --index-url https://download.pytorch.org/whl/cu124
pip install -r requirements.txt

cd hy3dpaint/custom_rasterizer
pip install -e .
cd ../..
cd hy3dpaint/DifferentiableRenderer
bash compile_mesh_painter.sh
cd ../..

wget https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth -P hy3dpaint/ckpt

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

import sys
sys.path.insert(0, './hy3dshape')
sys.path.insert(0, './hy3dpaint')
from textureGenPipeline import Hunyuan3DPaintPipeline
from textureGenPipeline import Hunyuan3DPaintPipeline, Hunyuan3DPaintConfig
from hy3dshape.pipelines import Hunyuan3DDiTFlowMatchingPipeline

# let's generate a mesh first
shape_pipeline = Hunyuan3DDiTFlowMatchingPipeline.from_pretrained('tencent/Hunyuan3D-2.1')
mesh_untextured = shape_pipeline(image='assets/demo.png')[0]

paint_pipeline = Hunyuan3DPaintPipeline(Hunyuan3DPaintConfig(max_num_view=6, resolution=512))
mesh_textured = paint_pipeline(mesh_path, image_path='assets/demo.png')

You could also host a Gradio App in your own computer via:

python3 gradio_app.py \
  --model_path tencent/Hunyuan3D-2.1 \
  --subfolder hunyuan3d-dit-v2-1 \
  --texgen_model_path tencent/Hunyuan3D-2.1 \
  --low_vram_mode

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

@misc{hunyuan3d2025hunyuan3d,
    title={Hunyuan3D 2.1: From Images to High-Fidelity 3D Assets with Production-Ready PBR Material},
    author={Tencent Hunyuan3D Team},
    year={2025},
    eprint={2506.15442},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}

@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}
}

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