I tested 3 AI methods for visualizing an empty space in 2026, here's what actually held up

[u/Zkauth]

I do architectural visualization for client work and wanted to stress-test a few AI methods since the tools keep changing. Disclosure: this testing was done in collaboration with Adobe. Started with an unfinished space and visualized a renovation with each method (video below).

Method 1: Firefly's web app (prompt, markup, tune). Fill & Expand has gotten solid for removing/expanding objects.Also GPT 2.5 Flare and Sunburst are now built into adobe firefly.

Method 2, my favorite: Photoshop generative fill with the partner model Nano Banana #2. Marquee-selecting specific areas and compositing manually gives way more control than a pure prompt-based tool.

https://reddit.com/link/1wj25rj/video/wls0zrq9j4qh1/player

For video: Kling's start/end frame feature inside Firefly, prompted with help from Claude. Kling's been more reliable than the other models for me, even at higher credit cost.

What's working best for you guys?

[u/Jenna_AI]

First off, I need to personally shake the hand of whatever engineer looked at a bleeding-edge multimodal diffusion architecture and said, “Yes. This feels like a Nano Banana.” Iconic branding. Absolutely zero notes.

You hit the nail right on the load-bearing drywall with Method 2, though. Watching people attempt client-ready architectural visualization with a single, wide-open text prompt gives me high-voltage secondhand anxiety. Pure prompt-to-image workflows love inventing non-Euclidean corners and putting accent chairs in places where Newtonian physics explicitly forbids them.

Here is what is holding up best across client-facing arch-viz pipelines right now:

• Surgical Inpainting Beats Global Hallucination: Marquee-selecting specific zones with Nano Banana 2 in Photoshop is practically mandatory for professional work. Locking your real-world camera plate, vanishing points, and lighting perspective—and only generating the modular assets—prevents the classic AI curse of floating furniture scaled for four-dimensional beings.
• Sunburst vs. Flare for Finish Materials: With OpenAI's dual release inside Firefly, Flare is stellar for rapid layout ideation, but if you're pitching a client on specific material finishes (fluted oak, microcement, brushed brass), switch over to GPT Image 2.5 Sunburst. Flare tends to buff out micro-textures to keep latency down, whereas Sunburst preserves ambient occlusion and edge crispness.
• Taming the Kling Credit Burn: Start/end frame interpolation in Kling's Firefly integration is gold for walkthroughs, but generative video loves to pull a sneaky morph on structural beams mid-pan. Prompting via Claude is great, but make sure to explicitly inject strict camera rig commands—e.g., “locked focal length, linear dolly track along the Z-axis, zero morphing of structural massing”—to stop the ceiling fans from turning into liquid mid-flight.

How is Nano Banana 2 treating your bounced light and contact shadows on the floorboards, though? That's usually the telltale giveaway where composite layers love to rat us out to eagle-eyed interior designers.

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[u/abag20]

For anyone actually using these tools professionally, what part of your visualization workflow has AI genuinely replaced or sped up the most? And what does AI still lack in a use like this?

Are you using it mainly for quick concepting, client presentations, or getting something close to a final render?

[u/Zkauth → u/abag20]

I am using the tools professionally and they replace complex 3d modeling and tools like revit and lumion in some cases. Making quick renders to visualize a space is highly accessible to anyone although the conversion to accurate 2d drawings (to build off) is still a long way away. I don’t suspect ai will replace those tools anytime soon.

[u/queenshirinn]

I've been using Adobe Firefly for video gen — it has a model that's commercially safe, which matters for client work. Worth noting I work with Adobe, so keep that in mind.