GPT Image 2.5 vs Nano Banana 2.1: Which Image Model Should You Use?

Key Takeaways

• GPT Image 2.5 wins on quality. Its Sunburst model sits first on LMArena's text-to-image and image-edit boards, roughly 95 to 100 points ahead of Nano Banana 2.1.

• Nano Banana 2.1 is the better research tool. It can ground an image in Google Search results, which matters for infographics and anything that has to be factually current.

• Neither one is simply cheaper. GPT Image 2.5 at medium quality costs less per image than Nano Banana 2.1, but at high quality it costs more.

• Both still struggle with small and dense text. Each vendor says so in its own documentation.

• Nano Banana 2.1 is a day old. Its launch-week reviews are mixed on prompt following, so expect its standing to move.

Two image models released a month apart

OpenAI shipped GPT Image 2.5 on September 8, 2026, and we covered what changed at the time. Google answered on October 6 with Nano Banana 2.1, which replaces Nano Banana 2 in the Gemini API and lands across the Gemini app, AI Studio, Google Flow and Google Ads.

Both generate and edit images from text and reference photos, and they're good at different things. GPT Image 2.5 makes the better-looking image and keeps more of a picture intact when you edit it. Nano Banana 2.1 pulls facts from Google Search and costs less at its higher quality settings. Which one you want depends on the work.

Everything here comes from each vendor's documentation and model card, LMArena's public leaderboards and launch-week user reports, all checked on October 7, 2026. We didn't run our own benchmark.

GPT Image 2.5 and Nano Banana 2.1 at a glance

Overview: GPT Image 2.5

GPT Image 2.5 is two models. Flare is the fast default, which OpenAI says delivers better images than GPT Image 2 at 50% lower latency. Sunburst is the slower precision model for finished work. You choose a quality setting on top, from low to max, and the setting moves the price more than the model does.

It's available to every ChatGPT tier, in the API and inside partner tools such as Adobe Firefly. Its standing weakness is a fine grain in flat areas like skies and studio backdrops, which TechRadar confirmed in its own tests while saying it doesn't ruin the picture.

Best for: Finished visuals and edits where the image has to look right on the first pass.

Overview: Nano Banana 2.1

Nano Banana 2.1 is Google's new default image model, built on Gemini 3.6 Flash. It adds three thinking levels (minimal, medium and high), so you can trade speed for how carefully it follows the prompt, and it can search the web and Google Images before it draws.

Google's own model card scores it well ahead of Nano Banana 2 and Nano Banana Pro on preference, editing and multi-character consistency, though it compares only against Google's models. Early users in r/GeminiAI describe a split verdict: noticeably better image quality, worse prompt following, and generations that eat into Gemini app quotas faster than before.

Best for: Infographics, diagrams and explainers that need current facts, and multi-character scenes.

Image quality

On LMArena, where people vote blind between two images from the same prompt, GPT Image 2.5 Sunburst leads text-to-image at 1425 and Flare is second at 1398. Nano Banana 2.1 debuted fifth at 1328, behind GPT Image 2 and Microsoft's MAI Image 2.6. A gap of about 100 Elo points means GPT Image 2.5 would win roughly 64% of head-to-head votes.

All three entries are still marked preliminary, and Nano Banana 2.1 has far fewer votes than Sunburst. The gap could narrow, but it's unlikely to close in a week.

Editing and reference images

Editing is where GPT Image 2.5 made its biggest jump, and the leaderboard agrees: Sunburst leads image editing at 1524 against Nano Banana 2.1's 1428. OpenAI built 2.5 to keep the parts of an image you didn't ask to change, which is what makes it usable for client revisions. Masks in GPT Image are guidance rather than hard boundaries, though, so a logo or face you need untouched still deserves a check.

Both accept a stack of references for product and character work: up to 16 images per edit on GPT Image 2.5, and up to 14 on Nano Banana 2.1, split into 10 object and four character references. Google's model card claims its biggest gain is in keeping several characters consistent across a scene.

Text inside the image

Neither model has solved typography, and both vendors admit it. OpenAI's documentation says GPT Image 2.5 "can still struggle with precise text placement and clarity," and reviewers found short headlines reliable while dense text still garbled. Google's model card lists poor rendering of small text, often blurry at 1K, and of long paragraphs.

Nano Banana 2.1 has one real advantage here: search grounding. If an infographic needs a current statistic or a correct label, it can look it up first. On Google's own infographic factuality benchmark, 2.1 with thinking turned on nearly triples Nano Banana 2's score.

Price per image

Both vendors charge $30 per million image output tokens, so the difference comes from how many tokens each image uses. Nano Banana 2.1 works out to about $0.034 for a 1K image, $0.05 at 2K and $0.11 at 4K, and Google's batch tier halves that. GPT Image 2.5's output cost depends on the quality setting: about $0.013 for a square image at medium, $0.053 at high and $0.21 at max, with OpenAI's batch processing also at half price.

So the cheaper model depends on the setting. For drafts and volume work at medium quality, GPT Image 2.5 costs less. At high quality, Nano Banana 2.1 does. These figures cover output only, and both models charge separately for input tokens, which add up when you feed in a stack of reference images.

In the consumer apps, neither company publishes hard limits. ChatGPT offers image generation on every plan, and so does the Gemini app.

Rights and provenance

Both let you use what you make commercially. OpenAI assigns ownership of outputs to you, and Google's API terms say it won't claim ownership of generated content. Both mark their images invisibly with SynthID, and OpenAI also attaches C2PA metadata, so either model's images can be identified as AI-generated by tools that check.

The verdict: which one fits your work

• Client-facing visuals and revisions: GPT Image 2.5 Sunburst. It leads on both quality and editing, and it keeps more of an approved image intact.

• Fast drafts and high-volume work: GPT Image 2.5 Flare at medium quality, which is quick and cheaper per image than Nano Banana 2.1.

• Infographics and anything with facts in it: Nano Banana 2.1 with search grounding and thinking set to high.

• Group shots with recurring characters: Nano Banana 2.1, on Google's consistency numbers, but test it on your own characters first.

• Already living in Google's tools: Nano Banana 2.1 is built into Gemini, Flow and Google Ads, so start there before paying for a second subscription.