> For the complete documentation index, see [llms.txt](https://metaverse-imagen.gitbook.io/ai-tools-research/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://metaverse-imagen.gitbook.io/ai-tools-research/ai-tools-main-categories/video-and-animation/3d-asset-creation-generative-ai-tools/point-e.md).

# Point-E

### [Point-E by OpenAI](https://openai.com/research/point-e)

Point-E Doesn’t generate 3D models in the traditional sense. Instead of generating robust and 3D-ready 3D models, it generates point clouds which are data points in a space that represent a 3D shape. Point-E is made of 2 model types: text-to-image and image-to-3D. In order to produce a 3D object from a text prompt, Point-E will sample an image using the text-to-image model.

Their team acknowledges the products limitations but believes it has a role in technical generative AI, “While our method still falls short of the state-of-the-art in terms of sample quality, it is one to two orders of magnitude faster to sample from, offering a practical trade-off for some use cases,” according to [this AI Business article](https://aibusiness.com/ml/openai-s-point-e-generates-3d-models-from-text).

**The OpenAI research team released the point cloud diffusion models and evaluation code on** [**Github here**](https://github.com/openai/point-e)**. echo3D** ([www.echo3D.com](http://www.echo3d.com/); Techstars 19) is a cloud platform for 3D asset management that provides tools and cloud infrastructure to help developers quickly build and deploy 3D/AR/VR games, apps, and content.