Testing reveals that the fastest AI tool for text-to-3D generation is the slowest for image-to-3D, and vice versa. This performance inversion means that benchmarks for one input mode are irrelevant and misleading for evaluating the other, as they are effectively different systems.
The AI 3D generator producing the mesh with the highest face count did not win on geometry quality. More polygons can simply mean an inefficient distribution of triangles, increasing VRAM costs at runtime without actually improving the visual detail or shape accuracy.
While game engines can handle messy mesh topology, AI-generated models with poor structure (triangles and n-gons) are unusable for artists in tools like Blender or Maya. This necessitates a time-consuming retopology pass, adding significant hidden labor costs to the production pipeline.
The ranking of AI 3D generators changes dramatically when textures are considered. A tool leading in 'white mesh' shape accuracy can fall behind others in textured output quality. This forces teams to evaluate tools separately for geometry and texturing based on their specific pipeline needs.