Cube 3D is our first step towards 3D intelligence, which involves a shape tokenizer and a text-to-shape generation model. We are unlocking the power of generating 3D assets and enhancing creativity for all artists. Our latest version of Cube 3D is now accessible to individuals, creators, researchers and businesses of all sizes so that they can experiment, innovate and scale their ideas responsibly.

This release includes model weights and starting code for our v0.5 model. With this update, we introduce two upgrades to the auto-regressive base model for 3D geometry generation from text: higher fidelity 3D compositions and bounding box conditioning

The example gif above shows the model's capacity to generate 3D shapes capturing mixtures of concepts expressed in text, for example mechanical lobster with mechanical tank treads. The v0.5 model also shows significantly better text adherence, for example the lowpoly paper craft victorian rabbit.

With bounding box conditioning, we observe novel 3D generations where the model balances between the two conditioning inputs -- text prompt and global aspect ratio. In the gif below, notice how the model creatively interprets the the seashell or tall pagoda prompts into distinct 3D shapes. The model sometimes struggles when the bounding box is too extreme for a given prompt, for example the cat, where it can produce disconnected components or generates it along a diagonal to fit the bounding box constraints.

For code and details on how to use the models, please refer to our Github repository.

For technical details, please see our tech report