Disclosure: I work with SUAPP AI, so this is an employee perspective rather than an independent product review. The workflow below is tool-agnostic.
If control is the priority, I would not choose a tool by its best-looking first render. I would test every candidate on the same scene in three passes:
Baseline: use the same SketchUp camera, crop, resolution, and prompt. Compare rooflines, openings, repeated windows, railings, furniture, and scale against the source model.
Local edit: mask one material or object and request one small change. Check the mask boundary and confirm that geometry, camera, lighting, and unselected areas remain unchanged.
Second edit: make another isolated change without regenerating the whole image. If the first correction is lost, the workflow is difficult to control in a real project.
For material-specific editing, a flat JPG is the main limitation: the AI does not actually know which pixels belong to a SketchUp material. A practical workaround is to export a clean beauty image plus a material-ID or simple color mask pass, then use the mask for local editing. Clear material groups and high-contrast boundaries help.
One workflow documented at SUAPP AI is to start from a clear, centered source view and default settings, review the result, then adjust design weight, style, and prompts one at a time. The same testing discipline applies to any tool.
My stopping rule is simple: if a local material edit changes major geometry, camera, scale, or untouched areas, I would treat that output as concept exploration, not a verified render. For comparisons, score geometry preservation, mask accuracy, iteration history, export limits, privacy, and cost separately.
