3D Generation

Text-to-3D, image-to-3D, and 3D reconstruction.

Capability Matrix

Provider	Input	Output	Quality	Use Case
Tripo AI	Image/Text	Mesh	Good	Quick prototypes
Meshy	Image/Text	Mesh	Good	Game assets
Rodin	Image	Mesh	Very Good	Characters
Luma Genie	Text	3D	Good	Concepts
NeRF	Images	Radiance field	Excellent	Reconstruction

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Stages of Maturity

Capability	Stage	Notes
Single object from image	Maturing	Production-viable
Text-to-3D objects	Early	Quality improving
Scene reconstruction	Maturing	NeRF, Gaussian splatting
Animated characters	Emerging	Limited options
Full environments	Early	Not yet reliable

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Tool Selection

Need	1st Choice	2nd Choice	Why
Text/image to 3D	Tripo	Meshy	Speed vs quality
Game-ready assets	Rodin	—	Topology optimization
Scene reconstruction	NeRF / Gaussian Splatting	—	Photorealistic capture

Context

• AI Modalities — All capability types
• NeRF — Neural radiance fields

Questions

When single-object-from-image hits production quality — which industry gets disrupted first?

• At what point does AI-generated 3D replace hand-modeled assets for game studios — cost threshold, quality threshold, or both?
• What separates "good enough for a prototype" from "good enough for production" in 3D generation?
• How does Gaussian splatting change the economics of 3D capture compared to traditional photogrammetry?