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TEXT → 3D • CURATED • UPDATED FEB 5, 2026

Shap-E

OpenAI's conditional 3D model generation

Generates 3D objects from text prompts or images using OpenAI's Shap-E model, a conditional generative model for 3D assets. Produces high-quality 3D meshes, point clouds, and neural radiance fields (NeRFs) from natural language descriptions. Supports both text-to-3D and image-to-3D workflows, generating detailed 3D models with realistic geometry and textures suitable for game assets, product visualization, and 3D printing applications. Open-source model with comprehensive documentation and active community support, making it ideal for research, prototyping, and educational use.

Pricing Free
Platforms local, api
API No
Open Source Yes
Modalities Text → 3D, Image → 3D
Best For Best for Research
Date Added 2026-02-05

OpenAI's open-source 3D generation model with comprehensive documentation and active community, representing state-of-the-art conditional 3D asset generation from text and images.

Clone the Shap-E repository from GitHub. Follow installation instructions and set up dependencies. Download model weights and configure environment. For text-to-3D, enter detailed prompts describing 3D objects. For image-to-3D, upload reference images. Generate 3D models in desired format (mesh, point cloud, or NeRF). Review geometry and texture quality. Export in 3D formats. Free and open-source, suitable for research, prototyping, and educational use.

1 Review GitHub documentation thoroughly
2 Use detailed prompts for 3D object descriptions
3 Experiment with different output formats
4 Use for research and prototyping workflows
5 Join community for support and examples
GitHub Documentation
Hunyuan 3D Tripo AI v3 Luma Genie Meshy AI v3 SAM3D v2

Text-to-3D Model Generation

Generate 3D models from text descriptions.

STEPS:
  1. Clone repository and install dependencies
  2. Download model weights
  3. Enter detailed 3D object descriptions
  4. Generate 3D models in desired format
  5. Review geometry and quality
  6. Export for use in projects

Image-to-3D Reconstruction

Create 3D models from reference images.

STEPS:
  1. Set up Shap-E environment
  2. Upload reference images
  3. Generate 3D models from images
  4. Review reconstruction quality
  5. Export in 3D formats
  6. Use in 3D workflows
Free Completely free
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Q

Is Shap-E free?

A

Yes, Shap-E is completely free to use.

Q

Does Shap-E have an API?

A

No, Shap-E does not appear to offer a public API.

Q

What is Shap-E best for?

A

Shap-E is best for Research. Generates 3D objects from text prompts or images using OpenAI's Shap-E model, a conditional generative model for 3D assets. OpenAI's open-source 3D generation model with comprehensive documentation and active community, representing state-of-the-art conditional 3D asset generation from text and images.

Q

What platforms does Shap-E support?

A

Shap-E supports local, api.

Q

Is Shap-E open source?

A

Yes, Shap-E is open source. You can access the source code on GitHub at https://github.com/openai/shap-e.

Q

How do I get started with Shap-E?

A

Clone the Shap-E repository from GitHub. Follow installation instructions and set up dependencies. Download model weights and configure environment. For text-to-3D, enter detailed prompts describing 3D objects. For image-to-3D, upload reference images. Generate 3D models in desired format (mesh, poi...

Q

How do I create 3D models with Shap-E?

A

Shap-E supports both text-to-3D and image-to-3D generation. You can create 3D models from text descriptions or convert reference images into 3D assets.

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