Which AI image model is best for rendering text and design elements accurately?

GPT-Image-2 is the best image model for rendering text and design elements accurately — it beats Nano Banana Pro on typography, UI screens, and layout fidelity, while Nano Banana Pro wins on lighting. In documented ad localizations, GPT-Image-2 regenerated translated app UI screens with 100% product and text consistency across two markets.

Use GPT-Image-2 whenever the frame contains words, logos, app interfaces, or layout-driven design — it renders text and design elements more accurately than Nano Banana Pro, which is the stronger model for lighting. The practical split across the current image stack: GPT-Image-2 for text, design, and realistic environments (it also accepts reference image attachments, which makes it the preferred model for location and character reference sheets, each generated in about 5 minutes); Nano Banana Pro for lighting-critical hero frames; Recraft for character skin texture during casting. All of these models run inside invideo, so you choose per task, not per platform.

The strongest documented proof of GPT-Image-2's text accuracy comes from an ad localization run: the model regenerated 5 app UI screens per market with fully translated on-screen copy — including a Japanese CTA reading "up to 45% off on first purchase" — and the workflow held 100% product and text consistency across 3 ads in 2 completely different markets (Japan and Spain).

You don't have to make the model call manually. The invideo agent routes each generation to the right model automatically — in the documented case it switched to GPT-Image-2 for the text-heavy design stage without being asked. If you want to verify the choice yourself, generate the same keyframe across multiple image models in one chat and compare the text rendering side by side before locking.

One rule for video work: bake your text at the image stage, not the video stage. Text artifacting in AI video is a model-level limitation of Seedance, not a workflow failure — so generate the text-bearing frame with GPT-Image-2 first, lock it, then animate that frame. For shots where exact product fidelity matters alongside design, a two-model pass — GPT-Image-2 for the base aesthetic, then Nano Banana to lock the exact product into the frame — is a documented option.

Watch some of these to see what works for you:

Nano Banana is unmatched when it comes to image lighting rendering... while Nano Banana Pro is better at lighting, GPT is much better at text and design rendering, which is way more important for this part of the process. Again, the agent already knew that, so I didn't even have to ask for a model swap.

— invideo's creative team