---
title: "Which AI Image Model Is Best? | ImageQuarry"
url: https://www.imagequarry.com/faq/which-ai-image-model-is-best/
last_updated: 2026-10-20
---

# Which AI image model is best?

No single model is best for every image. The right choice depends on the task, the subject and the style, and the reliable test is your own request, run through two models and compared side by side.

Makers describe their models for different jobs, but that is positioning, not independent test results. Results also vary with the subject and the style, so a model that suits product shots may not suit illustration. Pick a starting point, run your own request, and compare the outputs.

ImageQuarry works with four image models: Nano Banana 2.1, the default, and Nano Banana Pro, which are Google image models, plus GPT Image 2.5 Flare and GPT Image 2.5 Sunburst. You can choose a different model when you want a different result for the same request.

_Sources: Google Gemini image generation documentation; OpenAI image generation guide; ImageQuarry homepage. Checked October 20, 2026._

Next step: [Why do different AI models give different results from the same prompt?](https://www.imagequarry.com/faq/why-do-different-ai-models-give-different-results/)

## Related questions

- [Which AI image generator is most realistic?](https://www.imagequarry.com/faq/which-ai-image-generator-is-most-realistic/): None for every subject; compare your own prompt.
- [Does the model matter for image editing?](https://www.imagequarry.com/faq/does-the-model-matter-for-editing/): Yes, partly; a clear instruction matters on any model.
- [Which AI models does ImageQuarry use?](https://www.imagequarry.com/faq/which-ai-models-does-imagequarry-use/): Nano Banana 2.1, Nano Banana Pro and two GPT Image 2.5 models.
- [How much does AI image generation cost?](https://www.imagequarry.com/faq/how-much-does-ai-image-generation-cost/): It depends on the tool, the plan and the work.

Last reviewed 2026-10-20 by ImageQuarry.

## Compare models on your own request

Run the same request through more than one model in ImageQuarry and keep the result that fits.