Shap E


AI model preview image
Shap-e is a model that generates conditional 3D implicit functions. These functions can be used to create detailed 3D shapes based on input conditions. The model uses neural networks to learn the relationship between input conditions and the shape of the object. It can be used in various applications such as 3D modeling, computer graphics, and virtual reality.

Use cases

Shap-e has the potential to revolutionize the field of 3D modeling and computer graphics. With this AI model, designers and artists can easily create detailed 3D shapes by simply inputting the desired conditions. For example, it can be used to generate realistic and customized 3D objects for video games, animations, and virtual reality environments. Architects and industrial designers can also benefit from Shap-e by quickly generating complex 3D models based on specific design criteria. Additionally, this model can be used in scientific simulations to generate accurate 3D representations of objects or environments. In terms of practical applications, companies can develop products that leverage Shap-e to enable users to easily create and customize their own 3D models for various purposes, such as personalized gaming avatars, virtual home design, or even 3D printed prototypes of custom-made products. Overall, Shap-e offers a wide range of possibilities in the field of 3D shape generation and has the potential to greatly enhance the creative and practical capabilities of designers, artists, and developers.



Cost per run
Avg run time
Nvidia T4 GPU

Creator Models

Pix2pix Zero$?4,206
Night Enhancement$0.0104520,721
Mindall E$?1,645
Compositional Vsual Generation With Composable Diffusion Models Pytorch$0.01155774

Similar Models

Try it!

You can use this area to play around with demo applications that incorporate the Shap E model. These demos are maintained and hosted externally by third-party creators. If you see an error, message me on Twitter.

Currently, there are no demos available for this model.


Summary of this model and related resources.

Model NameShap E
Generating Conditional 3D Implicit Functions
Model LinkView on Replicate
API SpecView on Replicate
Github LinkView on Github
Paper LinkView on Arxiv


How popular is this model, by number of runs? How popular is the creator, by the sum of all their runs?

Model Rank
Creator Rank


How much does it cost to run this model? How long, on average, does it take to complete a run?

Cost per Run$0.05775
Prediction HardwareNvidia T4 GPU
Average Completion Time105 seconds