GPT Image 2.6 TeamThe short answer: pick Nano Banana 2.1 when the job is high-volume image making and the bill decides the answer. Google charges per token, and one 1K image works out to about $0.0336. Pick GPT Image 2.6 when you want a still or an animated GIF without an API key. Here a 1K image costs about $0.20, so 2.6 is the pricier side, and neither model wins overall.
GPT Image 2.6 vs Nano Banana 2.1 at a glance
The table below is the whole decision, and two rows carry most of the weight: price and animated output.
Most published comparisons still set 2.1 against GPT Image 2.5, so the 2.6 numbers here come from this site's own catalogue and OpenAI's API docs.
| Nano Banana 2.1 | GPT Image 2.6 | |
|---|---|---|
| Model ID | gemini-nano-banana-2.1 |
gpt-image-2.6-flare, -sunburst |
| Output size | 1K (default), 2K, 4K | 1K, 2K, 4K here |
| Aspect ratios | Seam fix listed for 1:4, 4:1, 1:8, 8:1 | 11 ratios here, widest 21:9 |
| Reference images | Up to 14 (4 characters, 10 objects) | Up to 16 here |
| Text and infographics | Named improvement | quality low to high here |
| Transparent background | Not listed on the model page | API documents transparent; not exposed here |
| Animated output | Not listed on the model page | GIF here; SVG on API generations only |
| Search grounding | Google Search and Image Search | Not offered here |
| Thinking levels | minimal / medium / high | No such setting listed |
| Price per 1K image | About $0.0336, API equivalent | About $0.20 in credits ($50 pack) |
| Price per 4K image | About $0.113, API equivalent | About $0.60 in credits ($50 pack) |
Sources for the API specs are listed at the end; the rows about this site come from its own catalogue.
Nano Banana 2.1 is cheaper at every size
Google's model is the cheaper one, and the gap is far wider than a rounding difference.
Nano Banana 2.1 bills per token: $1.50 per million input tokens and $30 per million image output tokens. Google turns that into an equivalent per-image price of about $0.0336 at 1K, $0.0504 at 2K and $0.113 at 4K.
This site bills per image in credits instead. Flare costs 20, 30 or 60 credits at 1K, 2K and 4K, and Sunburst costs 26, 39 or 78. The $50 pack holds 5,000 credits, which makes a credit a cent on that pack, so a Flare render works out to $0.20 at 1K, $0.30 at 2K and $0.60 at 4K.
At 1K that is roughly six times Google's equivalent price, and at 4K about five times. Both multiples come from Google's own equivalent prices, not from an estimate of ours.
Cheap and easy are still two different things. Google's price assumes a Cloud project, an API key, a billing account and somewhere to send the output. This site assumes a browser.
You pick a size, press generate, and credits come out of a pack that never expires. A failed render returns its credits, and no OpenAI account is needed.
The cost per keeper can also move in either direction. This breakdown of 2.6 cost per image covers when a cheaper model still loses on retries.
Pick by the job
The useful split is by task, because each model documents something the other does not.
| Your job | Start with | Why |
|---|---|---|
| 500 product shots this week | Nano Banana 2.1 over the API | About $0.03 per 1K image |
| An 8:1 or 1:8 website banner | Nano Banana 2.1 | Google lists seam fixes at 2K and 4K for these extremes; this site stops at 21:9 |
| A sticker or cutout with alpha | GPT Image 2.6 over the OpenAI API | Transparency is documented on both variants; not exposed on this site |
| An animated GIF | GPT Image 2.6 here | 2.1's page lists no animated output |
| A dense infographic or poster | Test both | 2.1 lists text and layout gains; 2.6 has quality tiers |
| One character across ten turns | Nano Banana 2.1 | Up to 4 characters and 10 objects held |
| No API key, no setup | GPT Image 2.6 here | Browser, credits, refunds on failure |
Panoramas. Google fixed a real seam problem in 2.1. Wide ratios like 1:4, 4:1, 1:8 and 8:1 no longer show tiling seams at 2K and 4K. This site's widest ratio is 21:9, which is why a true 8:1 strip is out of reach.
Cutouts. OpenAI's API takes background: transparent on both Flare and Sunburst. This site's form has no background option, so a browser render cannot request transparency. Nano Banana 2.1's model page lists no background setting at all, which is not the same as saying it cannot do it.
GIFs. This site renders animated GIFs on 2.6 for 40 credits on Flare or 52 on Sunburst. SVG is a different story: the API accepts it on generations, but this site does not output SVG.
Text. Google lists better text rendering and infographic layout accuracy in 2.1. On this site, the 2.6 lever is a quality setting of low, medium or high, where high adds 50% to the price. OpenAI's API exposes more than that: quality also accepts auto, xhigh and max, and a separate complexity of low, medium or high defaulting to high. Neither the extra quality tiers nor complexity appear in this site's form.
What Nano Banana 2.1 actually lists
Google calls it a high-efficiency image generation and conversational editing model. It is an update to Nano Banana 2, which is Gemini 3.1 Flash Image, and Google positions it as a more efficient alternative to Gemini 3 Pro Image.
The listed changes are concrete:
- Higher quality and realism, at 1K, 2K or 4K with 1K as the default
- Fixed tiling seams on 1:4, 4:1, 1:8 and 8:1 at 2K and 4K
- More accurate text and infographic layout
- Up to 14 reference images, holding 4 characters and 10 objects
- Grounding through Google web and image search
- A configurable thinking level of minimal, medium (default) or high
Input covers text, image, video and PDF, and output is image plus text. The token limits are 131,072 in and 32,768 out. Structured outputs and URL context are not supported.
What GPT Image 2.6 gives you here
Two IDs do different jobs. Flare is the smaller, faster model; Sunburst is the base model for detail and precise edits. There is no plain gpt-image-2.6.
That split is a structural difference from Google. One ID, gemini-nano-banana-2.1, covers both generation and conversational editing. Here you pick a variant first, and Sunburst is the one documented for precise edits.
Sizes are 1K, 2K or 4K across 11 aspect ratios, with up to 16 reference images. Quality is low, medium or high: low and medium cost the same, and high adds 50%. Output is either a still or a GIF; there is no JPEG or WebP picker. The API reference lists the token rates.
The convenience has a limit: this site has no web search grounding, so 2.1's search hook has no equivalent here. On the form, transparency and SVG stay on the API side; here you pick a prompt, a size, a quality setting, a format and reference images. Pricing covers packs and subscriptions.
What the model pages do not list
Google's model page is a feature summary, not a full spec. It lists no background setting, no animated output and no SVG export. That is not evidence those are impossible. It means you should test before you promise them to a client.
The reverse holds too: the page does not say 2.1 cannot do transparency, only that it is unlisted.
Test the split with your own prompts
Take five prompts you already run, not five you invent for the test. Run them at the same size on both models. Then judge only the failure you care about: broken text, an untidy edge, or an edit that drifts.
Budget the test. Google's standard tier has no free quota, and this site needs credits, so twenty 1K renders cost money on both sides. Start in the browser generator, where the price shows before you commit.
FAQ
Which is cheaper, GPT Image 2.6 or Nano Banana 2.1?
Nano Banana 2.1, by a wide margin: about $0.0336 per 1K image from Google against about $0.20 in credits here. The catch is that Google's price needs an API key, a Cloud project and token metering.
Can Nano Banana 2.1 output a transparent PNG?
Google's model page does not list a background setting, so the honest answer is that it is undocumented. OpenAI documents transparency on both 2.6 variants at the API level, but this site's form does not expose it.
Can Nano Banana 2.1 make an animated GIF?
Its model page lists no animated output. This site renders GIFs on GPT Image 2.6 only, at 40 credits for Flare and 52 for Sunburst. Anything beyond that would be speculation.
How many reference images does each model take?
Nano Banana 2.1 accepts up to 14, holding 4 characters and 10 objects. This site accepts up to 16 on GPT Image 2.6.
Do I need an API key to use GPT Image 2.6 here?
No. You pick a model, a size and a ratio in the browser, and credits are deducted per image. Google's side needs a key and a billing account, with no free tier.
Sources
- Gemini Nano Banana 2.1 model page — positioning, listed changes, sizes, reference limits, token limits and thinking levels.
- Gemini Developer API pricing — token rates and the equivalent per-image prices at 1K, 2K and 4K.
- OpenAI image generation guide — output formats,
background,qualityandcomplexitysettings. - OpenAI API pricing — image input and output token rates.
Revision log
- November 5, 2026 — Page published.
- November 5, 2026 — Fact check: transparency and
complexityscoped to the API, site rows aligned with what the form actually exposes.