AI 3D Model Generator

3D content creation has been the workflow AI most struggled to crack. The first generation of "photo-to-3D" tools mostly produced depth-mapped images dressed up as 3D — fine for casual filter use, useless for actual production where teams need scene depth, dimensional camera moves, and reusable spatial references. Real production pipelines (game art, animation pre-viz, virtual set work, AR concept design) need 3D-aware outputs that can drive downstream rendering, motion, and reference work.

The newer generation of cinematic-class video models — Sora 2, Kling 3, Veo — has implicit 3D awareness baked into their motion handling. They understand spatial relationships, camera moves through volume, and scene depth in ways that earlier video models did not. Combined with reference-image models like Nano Banana 2 that produce 3D-style renders and dimensional concept art, the building blocks for AI-assisted 3D production now exist — but they live across separate tools that do not chain.

And then there is the integration problem with real 3D workflows. AI-generated 3D-style references and pre-viz video are valuable inside the larger production pipeline — concept exploration, set design, motion reference, virtual location scouting — but only if they connect to the rest of the work. Standalone 3D tools that dead-end at a render undo their own value by forcing manual handoffs back to the production team.

Martini chains the 3D-adjacent models onto one canvas where their outputs feed real downstream work. Use Nano Banana 2 to generate dimensional reference renders and concept art with consistent perspective. Use Flux for editorial-grade 3D-styled visuals. Push those references into Sora 2 and Kling 3 video nodes for camera moves through the scene that respect spatial depth. Pair with the world-node workflow for image-to-3D-world scene exploration. Each model handles what it is best at, and the canvas treats the whole pipeline as one 3D-aware production surface.

Multi-model chaining is the unlock for production-grade 3D pre-viz and concept work. Generate the asset reference in an image node, push it into a video node for a turntable or orbit move, then chain into a sequence builder that orders the camera moves into a virtual location scout. For game art and animation pre-viz, use the canvas to explore the scene from multiple angles without rendering frames in a 3D engine. The output drives downstream production decisions — set design, blocking, storyboard validation — with much faster iteration than traditional 3D pipelines.

Sequence and reference integration finishes the workflow. The 3D-aware references stay pinned on the canvas and feed into video, lip-sync, and avatar nodes for character work that respects the spatial context. NLE export drops the pre-viz and reference video into Premiere, DaVinci, or Final Cut for further refinement. Save the canvas as a template and the next 3D pre-viz project reuses the model chain — concept-to-pre-viz becomes a repeatable pipeline rather than a one-off exploration.