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  • 🆚 ChatGPT Image 2 vs Nano Banana Pro: Full Test & Comparison Across Every Use Case

🆚 ChatGPT Image 2 vs Nano Banana Pro: Full Test & Comparison Across Every Use Case

Did OpenAI beat Nano Banana Pro without anyone noticing? The results aren’t obvious and one hidden weakness changes everything. We use both but for different things!

Author

Max Anh
April 24, 2026

TL;DR BOX

OpenAI's Images 2 is much better at following instructions and making pictures in different shapes. It also keeps the same face in every picture. But it doesn't cleanly dethrone Nano Banana Pro yet.

It introduces a more step-by-step way of generating images inside ChatGPT, fixing some long-standing complaints around rigid canvas sizes and inconsistent faces. In testing, it handles spatial reasoning, text rendering and style transfer better than expected. However, it suffers from a notable degradation problem in long chat sessions, where output quality drops noticeably the more context piles up.

Key Points

  • Stat: Images 2 can generate images in virtually any aspect ratio, including ultra-wide cinematic formats and tall vertical layouts that older models refused to handle.

  • Mistake: Running dozens of prompts in the same chat thread. Quality degrades fast. Always start a fresh chat when outputs start looking noisy.

  • Action: Use weird, layered prompts (like "a pelican on a bicycle holding a wine glass") to stress-test any image model. If it can hold multiple constraints at once, it's actually reasoning, not guessing.

I. Introduction

So Nano Banana Pro has been sitting at the top of the AI image throne for a while. It generates clean visuals, renders text better than most and has become the go-to model for creators who need professional-grade outputs.

Now OpenAI has introduced Images 2. Naturally, the question is whether this new model can replace Nano Banana. The short answer is: not entirely. But it already performs better in several areas in real creative work.

We’ll check if it’s a good image model based on these things:

  1. Following rules: does it do exactly what you asked or does it just guess?

  2. Spatial reasoning: can it place objects correctly and respect physical logic?

  3. Text rendering: does it spell things right and keep fonts readable?

  4. Character consistency: does the same face look like the same person across generations?

  5. Aspect ratio flexibility: can it handle unusual canvas sizes without breaking?

  6. Style transfer: can it change the visual style while keeping the subject intact?

These reflect the exact skills you need for real creative tasks such as thumbnails, marketing visuals, product images or character design.

If you want to test everything yourself instead of just reading, you can copy the full set of prompts (link below) used in this post here and run them directly in your own workflow. I also included the images so you can see the results.

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