GPT Image 2 vs. Nano Banana Pro: GPT has the edge, but it is not a knockout

First, make sure it is the right matchup

OpenAI lists GPT Image 2 in its API documentation with the model ID gpt-image-2-2026-04-21 . On Google’s side, Nano Banana Pro is also known as Gemini 3 Pro Image; Google describes it as its highest-quality image generation model, while Nano Banana 2, also called Gemini 3.1 Flash Image, is positioned as the high-volume, high-efficiency, lower-price option .

Google’s Gemini model page describes Nano Banana Pro Preview as a professional design engine for studio-quality 4K visuals, complex layouts, and precise text rendering . In other words, this is a comparison between two premium image-generation systems, not a flagship model versus a lightweight alternative.

What the direct benchmarks show

The fair reading is simple: GPT Image 2 has the edge in the public direct tests cited here, but the margin is thin. These results are best treated as directional signals, not as a definitive league table .

Where GPT Image 2 looks safer: text and layout

If the final asset contains important text, GPT Image 2 is the lower-risk choice based on the available comparisons. That includes menus, posters, product labels, UI mockups, manga panels, infographics, and device screens.

In AI Video Bootcamp’s test, GPT Image 2.0 beat Nano Banana Pro on in-image typography, manga dialogue panels, a bilingual menu, and a silkscreen gig poster . Pixazo also reported that GPT-Image-2 rendered the text “72°F” correctly on a phone screen in five out of six generations in one hands-with-device test .

That matters because text errors are often hard blockers in commercial images. A single wrong character in a label, price, measurement, headline, or app screen can make an otherwise beautiful render unusable.

A separate hands-on comparison looked at GPT Image 2 against Nano Banana 2, not Nano Banana Pro. It found GPT Image 2 had a narrow edge on precise text and technical terminology, while Nano Banana 2 had a narrow edge on Chinese/Japanese/Korean typography polish and dramatic lighting . Because that source did not directly test Nano Banana Pro, it should be treated as supporting context rather than proof about the Pro model.

Where Nano Banana Pro stays strong: realism and lighting

Nano Banana Pro is not being left behind. In AI Video Bootcamp’s benchmark, it beat GPT Image 2.0 on photorealism, skin texture, and lighting for the hyperreal portrait, UGC selfie, and athletic ad prompts . If your workflow is focused on lifestyle advertising, portraits, hero visuals, social-style creative, or camera-like lighting, that is a practical advantage.

Google also positions Nano Banana Pro/Gemini 3 Pro Image as its highest-quality image generation model . Its model page describes Nano Banana Pro Preview as supporting studio-quality 4K visuals, complex layouts, and precise text rendering . So the current picture is not that GPT Image 2 is better at everything; it is that GPT Image 2 shows a measurable advantage in some small public tests, while Nano Banana Pro remains a serious competitor for premium visual quality and Gemini-native workflows.

Refusals are not the same as bad renders

One important caveat: a refused prompt and a poorly rendered prompt are different failure modes.

AI Video Bootcamp reported that GPT Image 2.0 completed all 10 prompts, while Nano Banana Pro completed 9/10 because it refused a prompt involving an Elon Musk CV under a prominent-person policy message . That does not necessarily mean Nano Banana Pro lacked the image-generation ability to handle the visual task. It may reflect a stricter or different safety policy around real or famous people .

If your product involves portraits, public figures, news-like imagery, or potentially sensitive identity use cases, measure refusal rate separately from visual quality. Lumping both into one score can hide the real product decision.

Hands, objects, and geometry still need testing

Neither model should be assumed to have solved difficult anatomy or object geometry.

Pixazo found that GPT-Image-2 produced anatomically correct hands in four out of six generations in a phone-holding test, while also noting that hands remained a general problem and no model cleared the test cleanly . That is an improvement, but it is not a guarantee.

The cited direct sources do not provide enough matching detail to conclude that Nano Banana Pro is clearly weaker than GPT Image 2 on hands, multi-object scenes, or technical structures. If your workflow includes hands, several people, mechanical products, layered objects, or reference-sensitive edits, those should be part of your own benchmark.

API and production considerations

For OpenAI, GPT Image 2 is documented with the model ID gpt-image-2-2026-04-21 . OpenAI’s pricing page lists gpt-image-2 at $8 per 1M image input tokens, $2 per 1M cached image input tokens, and $30 per 1M image output tokens; text input is listed at $5 per 1M tokens and cached text input at $1.25 per 1M tokens .

For Google, the Gemini documentation identifies Nano Banana Pro as Gemini 3 Pro Image and notes that Gemini 3 models are currently in preview . OpenRouter has a separate listing for google/gemini-3-pro-image-preview with pricing on that platform . If you plan to buy through Gemini API, OpenRouter, or another provider, do not assume the same price or limits apply everywhere.

Which one should you choose?

How to run your own benchmark before switching

Before putting either model into production, test with prompts that look like your real workload:

1. Build a representative prompt set. Include text-heavy assets, photoreal images, product shots, infographics, edits, multi-character scenes, difficult hands, and likely policy-edge cases.
2. Run more than one generation for critical prompts. A single lucky output can make any model look better than it is.
3. Score separate failure modes. Track text accuracy, layout, prompt adherence, aesthetics, anatomy, reference fidelity, refusal rate, speed, and cost.
4. Separate refusals from bad renders. They lead to different product decisions.
5. Price through your actual production channel. Direct API pricing, routers, subscription layers, and preview access can differ .

Bottom line

GPT Image 2 is the better default if your biggest risks are wrong text, broken labels, layout drift, or poor prompt adherence. Nano Banana Pro is still a strong choice if you care most about photorealism, lighting, premium visual polish, 4K output, and integration with the Gemini ecosystem .

The most accurate verdict is: GPT Image 2 leads slightly overall in the small public head-to-heads available here, but Nano Banana Pro is very much still in the race. Treat the public benchmarks as a starting point, then validate with your own production prompts before committing .