AI-Generated 3D Models Are Becoming Software, Not Just Shapes

The next 3D asset on your phone or in your game engine may not be a file you render. It may be a small program that knows where its own axles are. That is the promise of Nova3D, an open-source system from Raresense that generates 3D objects as hierarchical, editable code rather than the monolithic mesh blobs most AI 3D tools still produce.

The paper, "Code-Native Generation of Programmable 3D Assets," was posted July 22, 2026 by Muhammad Bilal, Abdullah Hussain, and Hassan Baig, all affiliated with Raresense, with Bilal also at the University of Edinburgh. In the authors' framing, a generated object arrives with named parts, placed pivots, and unwrapped UVs, the way a 3D modeler would build it by hand, rather than as a single fused surface that needs to be sliced back into pieces before anything can move. The full HTML version of the paper and the open-source release on GitHub let anyone read or run the system today. The authors' demo site shows a go-kart whose wheels turn without anyone rigging them; the caption under the demo reads, "Nobody rigged it. The wheels turn because the kart already knows where its own axles are."

What does a 3D object look like when it is code rather than a mesh file? A mesh is a static list of triangles: a frozen description of a shape that only "knows" what an animator, a game engine, or a downstream tool programs into it afterward. Nova3D's output is hierarchical in the way a CAD assembly is hierarchical, with parts labeled, joints declared, and relationships between pieces explicit. The authors' own description, posted on r/MachineLearning, is that the assets are "animation-ready and programmable from inception" and can "contain the logic, at birth, to appear differently in weak compute environments (e.g. mobiles) vs powerful environments (e.g. sophisticated game engines)." That last claim is the one with consequence: a 3D asset authored in code can ship with a built-in decision about how to render itself, so a single artifact can scale from a low-end phone to a high-end game engine without a separate hand-tuned low-poly version sitting next to a high-poly version in a content management system.

The shift has obvious stakes in the industries the authors name: game development, industrial design, simulations, and AR/VR/XR. Game studios that already maintain multi-platform art pipelines stand to save the manual work of generating low- and high-poly variants and rigging them by hand. Industrial designers who want to iterate on a part's geometry without losing parametric history could treat the output more like a feature tree than a frozen surface. AR/VR/XR teams, where asset weight directly controls framerate, have the most to gain from a single artifact that decides for itself how much detail to show. None of that is guaranteed. Adoption will turn on how robust the generated code is, how editable it is to non-AI tools, and whether studios are willing to wire a new pipeline into a process they have already invested in.

The honest limits are the authors' own. The paper acknowledges that Nova3D "lags behind traditional AI 3D generators in creating complex organic shapes," the same caveat repeated on the r/MachineLearning post, and that gap is the one external press has picked up on. SiliconSnark frames the work as making AI 3D "editable, not just pretty blobs," a fair summary that lands the same point: the format is the story, not visual fidelity. That framing also leaves a clean open question. If a future version closes the organic-shape gap, the format shift from mesh to spatial code becomes a real category change for 3D content. If it does not, Nova3D is a useful specialized tool for hard-surface and mechanical objects, and the wire-grade "AI makes 3D models now" framing still rules the rest of the field.