Shap E
Shap-E is a conditional generative model developed by OpenAI, capable of generating 3D images from text prompts through a diffusion process. It is genuinely best at producing complex and diverse 3D assets, including textured meshes and neural radiance fields, in a matter of seconds.
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Frequently asked questions about Shap E
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
OpenAI has not published a context window for Shap E, so the catalog shows it as not available rather than estimating one.
Yes. Shap E is an open-weight model released under the MIT license, so the weights can be downloaded and self-hosted within that license's terms.
Shap E accepts Text and Image and produces Image. The capabilities card on this page lists which API features each deployment honours, such as function calling and structured output, with the source each was checked against.
No published benchmark result for Shap E is in the catalog yet, so the model is shown as unmeasured. It is not ranked or estimated; the router treats it as unknown for every task until a suite measures it.
Not on the managed pool today; Shap E is listed for reference and comparison. Connect your own provider key or endpoint that serves it and the gateway runs it on your account, with routing decisions recorded the same way.
OpenAI has not published a parameter count for Shap E, so the catalog cannot estimate its memory footprint. The capacity planner can size it from a parameter count you supply.
Fields collected from public registries, host APIs and benchmark publishers, each tagged with its source.
Last updated: Aug 28, 2026
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