Nano Banana 2.1 vs GPT Image 2: What I Pay Per Image, and What Google Gives Away

Google’s free image tier looks like a bargain. The fee for an AI image is a few cents. Your time is the bill.

Every article on this blog carries seven images. I generate them with GPT Image 2 at 2 credits each, so a full set costs me 14 credits. A credit has no fixed euro price, because it depends on your plan, so read 14 as my yardstick, not as a bill.

I have not run Nano Banana 2.1 myself, and I have no side-by-side result. This article rests on Google’s documentation and OpenAI’s pricing page, which I read and checked on October 14, 2026, on my own credit costs, and on a test you can run in an afternoon. Where a number is mine, I say so.

If you already pay for GPT Image 2 or Nano Banana Pro and your hit rate is high, do not switch on price. If you pay nothing yet, start with the free model for drafts, and test Nano Banana 2.1 at 2K on three prompts before you commit. Count your review minutes, not the fee.

Key Takeaways

• Nano Banana 2.1 costs $0.0336 for a 1K image and $0.0504 for 2K through the Gemini API. That is half of Nano Banana 2 at both sizes, and well under Nano Banana Pro at $0.134.
• “Free” in Google Flow means 50 credits a day, and one image model is stated as free. That model is Nano Banana 2 Lite, and through the API it makes 1K images only.
• I could not find how many images 50 credits buy. Flow’s credit table lists no image model.
• Reference slots are a spec, not a result. Nano Banana 2.1 takes up to 10 object images and 4 character images. Whether they hold a brand together is what a test shows.
• Compare cost per usable image with your review time counted. The fee barely moves the answer.
• On my platform the price list changed my mind about one thing: GPT Image 2.5 costs half of GPT Image 2 at medium quality, so it goes through my test first.

Google’s Image Ladder in One Table

Google now sells four image models through the Gemini API. Here are the Standard prices from its pricing page, per image.

The Batch API halves the Nano Banana 2.1 price, to $0.0168 for 1K and $0.0252 for 2K. Google describes the model as “an update to Nano Banana 2, serving as the primary high-efficiency workhorse model for image generation and conversational editing.”

Its docs recommend Nano Banana 2.1 over Nano Banana 2 “for all new projects.” The docs list it at 1K, 2K and 4K, and the smaller 512px size is not supported on it. I found no release date for 2.1 in Google’s pages.

What I Pay Per Image With GPT Image 2

I generate through Higgsfield’s command line. A preflight check tells me the cost before I spend anything, and I ran it today for every model in this article.

The table below shows the credits Higgsfield quoted on October 14 for a 16:9 image. These are estimates, and I generated nothing for this comparison.

Quality settings move GPT Image 2 a lot: at 2K it quoted 0.5 credits on low, 2 on medium and 6.5 on high. GPT Image 2.5 quoted 0.5 on low, 1 on medium, 2.75 on high, 4.5 on xhigh and 9 on max.

My last full sets were the CLAUDE.md article with 7 images for 14 credits, and the email tracking pixel articles with 14 images for 28 credits. Neither needed a regeneration.

These are illustrations in one style with a locked character, so that says my workflow works for my format. It says nothing about how Nano Banana 2.1 would do on your brief.

On my platform Nano Banana Pro at 2K costs the same 2 credits as my default, so for me the Pro question is quality, not price. If GPT Image 2.5 at medium holds my character as well, the same seven images would cost 7 credits.

OpenAI’s pricing page lists image models per million tokens and points to a calculator for per-image estimates. Its Standard table shows two 2.5 models, gpt-image-2.5-sunburst and gpt-image-2.5-flare, at $30 per million image output tokens. gpt-image-2 appears only in the Batch table, at $15.

I work with gpt-image-2, and the page does not say which model is best.

Token prices mislead. Nano Banana 2.1 has the same headline numbers, $30 Standard and $15 Batch.

But one 1K Google image consumes 1,120 tokens, and OpenAI’s page does not give a token count per image. Compare per-image prices, not per-token prices.

What “Free” Means in Google Flow

Google Flow is the creative tool where the free offer lives. Its help page on credits says “With or without a subscription, you receive 50 Google Flow credits per day.” A non-subscriber gets only those 50 credits “to try Google Flow.”

• Unused credits expire. “If you don’t use the full 50 Google Flow credits in a day, the unused Google Flow credits don’t roll over.” The daily refresh starts with your first generation.
• One image model is stated as free. Flow’s model page calls Nano Banana 2 Lite “the default model available at no charge.” It calls Nano Banana 2.1 “the standard model” and does not say what it costs in credits.
• The credit table has no image rows. It lists video models and upscaling, and the Google One page that Flow’s model page links for the latest credit costs lists none either. So I will not guess how many images 50 credits buy.
• Peak hours affect video, not images. Between about 2 PM and 5 PM UTC, free users may not generate videos, but they “can still generate images.”
• The limits can change. “Limits are subject to change at any time.”

The API is different. Nano Banana 2.1 has no free tier there: the pricing page lists the free-tier input price as not available.

Through the API, Lite makes 1K images only, and Higgsfield caps it at 1K too. Google’s Flow pages do not state its resolution, so check the setting in Flow.

If Flow follows the API limit, “free” mostly means 1K, which suits a social post or a storyboard draft. My blog hero images are exported at 2688 pixels wide, which needs a 2K source.

Reference Slots Are a Spec, Not a Result

For a marketer, the quality of one image matters less than whether the fifth image looks like the first. That depends on reference images, and the slot counts differ.

Google’s docs say its Nano Banana models “allow you to mix up to 14 reference images.” Nano Banana 2.1 takes up to 10 object images and up to 4 character images. Nano Banana Pro takes 6 objects, 5 characters and 3 style references.

Lite takes up to 14 object images, no character references, and Google says it is “not optimized for multiple reference inputs.” Google’s launch post for Nano Banana 2 gives a different split, 5 characters and 14 objects. When a vendor’s own pages disagree, I trust the API table and test.

My own setup uses one or two references. Every scene gets the same reference PNG of my character, and the image model keeps the face. When a mascot joins a scene, I pass its cropped image as the second reference, and it comes back faithfully.

Every model in the table accepts more references than I use, so slot count tells me little. If your brand has a mascot, a product or a founder in your visuals, check how many references each model accepts. Then test whether the face stays the same.

Cost Per Usable Image

Here is the formula I would use:

Cost per usable image = (fee per attempt + review minutes per attempt x your hourly rate / 60) / share of attempts that pass.

I have no measured hit rate for Nano Banana 2.1, so I will not give you one. Here are two made-up cases to show how the formula behaves.

Say you value your time at $60 an hour (my placeholder) and each attempt costs two minutes of review. That is $2 per attempt, about 40 times the $0.0504 fee for a 2K image from Nano Banana 2.1.

The expensive model wins here, and I made up the hit rates. That is the point: the fee barely moves the answer.

Review time and hit rate do, and nobody has measured them for your brief. The three-prompt test below does.

Scale it to a blog that publishes one article a week for 50 weeks, so 350 images. In the first case the year costs about $2,150 and in the second about $1,120, and almost all of it is review time.

In these made-up cases, fees stay under $1.50 per article. The bill that matters is your attention.

A 3-Prompt Test You Can Run in an Afternoon

Leaderboards do not know your brand. Three prompts do.

1. A product on a surface with a printed label. Specify the exact label text. This tests text rendering and realism.
2. An infographic with a title and five short lines. Use real words from your business, and proofread every word. Google says the Nano Banana models can produce “legible, stylized text for infographics, menus, diagrams, and marketing assets,” and I use GPT Image 2 for infographics with text, so this is where claims meet your copy.
3. Your mascot, founder or product in a scene, using your real reference image. This tests identity.

Run each prompt three times on each model you are considering, with the same settings. Then score the nine images per model on five yes-or-no checks: text correct, colors on brand, identity kept, no visible defects, usable without editing.

Write down the cost per attempt and the minutes you spent. Then compute cost per usable image.

Date the sheet. When a model updates, rerun the nine images.

Labels, Watermarks and Your Lawyer

Google says all images made through the API carry a SynthID watermark. For Nano Banana 2 it also pairs SynthID with C2PA Content Credentials, and says C2PA verification is coming to the Gemini app. I found nothing on C2PA for 2.1.

Those marks sit inside the file. Your audience sees nothing unless they check.

The Swiss data protection commissioner writes that the use of programs that enable the manipulation of faces, images or voice messages of identifiable persons “must also always be clearly indicated; this may even be completely unlawful in a specific case due to prohibitions under criminal law.” That is a regulator’s reading under Swiss data protection law. If your image shows a real person, ask your lawyer before you publish.

For images with no real person, I give no legal view. Other markets, the EU included, have their own rules on AI-generated content. Decide when you label, write it down, and apply it to every image.

This is a reading of public texts, not legal advice. For the exact wording of labels and your privacy notice, ask your lawyer or data protection adviser.

GPT Image 2 or Nano Banana 2.1: Where I Would Start

Only one line below comes from my own work. The rest is Google’s positioning, which I have not tested.

From my work: GPT Image 2 stays my default for images with my character and for text I proofread word by word, because that workflow is tuned.

From Google’s documents: Nano Banana 2 Lite in Flow is the stated free option, so I would use it for drafts I will throw away. Nano Banana 2.1 is Google’s recommended model for new projects at $0.0504 for 2K, so it goes through the three-prompt test first. Nano Banana Pro is described for the hardest briefs, and on Higgsfield it costs the same 2 credits as my default, so I would test it on the same three prompts.

From the price list: GPT Image 2.5 quotes half the credits of GPT Image 2 at medium quality, so it is the first candidate for cutting my bill. I would run it through the same test.

Frequently Asked Questions

Is Nano Banana 2.1 free?

Not through the API, where Google lists no free tier. In Flow, Google states that Nano Banana 2 Lite is the default model available at no charge. It does not say what Nano Banana 2.1 costs in credits.

How much does Nano Banana 2.1 cost per image?

Through the Gemini API, $0.0336 for a 1K image, $0.0504 for 2K and $0.113 for 4K at Standard prices. The Batch API halves those figures. On Higgsfield it quoted 1.5, 2 and 3 credits on October 14.

Do I need to label AI images?

Google adds a SynthID watermark inside the file, but that does not label the image for your audience. For images of real, identifiable people, the Swiss data protection commissioner says manipulation must be clearly indicated. For anything else, ask your lawyer.

My Verdict

GPT Image 2 or Nano Banana 2.1? Stop comparing sticker prices and compare cost per usable image on your own three prompts, with your review time counted. Until I have run them, I stay on GPT Image 2 for my character and text work.

Five rules:

1. Use the free tier for drafts, expect changing limits, and check whether Flow caps you at 1K.
2. Test Nano Banana 2.1 at 2K and Nano Banana Pro on the same three prompts before you switch tools.
3. Check reference slots if a mascot or founder appears in your visuals, then test whether the face holds.
4. Proofread every word inside an image.
5. Date your results. These models change every few months.

Prices and features on this page are as of October 14, 2026. Google and OpenAI change both often, so check the dates before you rely on a number.

Want help setting up an image workflow that keeps your brand consistent across a month of posts, and knowing what it costs? The wider bill for running AI as a marketer is in my piece on using AI for marketing, and the design-software side is in my PhotoCraft audit. Get in touch.