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GPT-image-2 vs Nano-banana 2: which image model for product ads?

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Bohdan Kossak · @bohdanDJA
Updated July 16, 2026 · 3 min read
GPT-image-2 vs Nano-banana 2: which image model for product ads?
Verdict — updated July 16 2026

Not rivals — stages. GPT-image-2 is the generator: new compositions, recomposed angles, 9:16-friendly framings, consistent campaign backgrounds — when you need an image that doesn't exist yet. Nano-banana 2 is the editor: targeted changes to an existing image — background swaps, clutter removal, vertical recomposition — with the product preserved exactly. The production pattern uses both in order: generate or fix the input image cheaply, then spend video credits animating it. Images are the cheapest place to fix quality; a $0.10-scale edit beats regenerating a $2.44 video because the source frame was cluttered.

Choose by job

Job Use
No usable product shot at the right angle GPT-image-2
PDP photo is right but background is wrong Nano-banana 2
Campaign-consistent backgrounds across SKUs GPT-image-2
Remove marketplace clutter / recompose to 9:16 Nano-banana 2
Seasonal variant of an existing hero image Either — edit if the base is good

The preservation rule

Both must keep the product honest — exact shape, color, materials. Prompts should state what stays ("keep the sneaker exactly as is") before what changes. Review before animating; errors compound downstream.

Paste a product link. The brief builds itself.

Generate product videos, UGC-style ads and hooks in about 5 minutes.

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FAQs

Which is cheaper?

Both cost a small fraction of a video generation — iterate freely at the image stage.

Can I skip images and go straight to video?

The URL flow does it for you when your PDP photos are good; fix or generate first when they're not.

Facts checked July 16, 2026. Competitor claims from public pricing pages; verify before relying on them.