Nano Banana 2: Which Generation to Choose and How to Use It

TL;DR. "Nano Banana" is not one model but a Google family of four generations, and the choice between them changes both the result and the cost. Nano Banana 2 (internal name Gemini 3.1 Flash Image) is the working middle: up to 4096 pixels, up to 14 references, confident text in the frame. Pro is heavier and "thinks" over a complex scene. The first version is locked at 1024 pixels. In June the fourth generation arrived, 2 Lite: the fastest and the cheapest, but also capped at 1024. In Pixyn they all work in one place, from 3 tokens per image.

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Why there are four generations and why it matters

The name "nano banana" appeared as the code name of a single model, and by August 2026 it stands for a whole lineup. People still search for "nano banana" as one query and get a mix of articles about different generations. That is where the confusion comes from: the promised 4K is nowhere to be found, and multi-reference works differently than in someone else's guide.

Generation	Google internal name	Maximum resolution	References
Nano Banana	Gemini 2.5 Flash Image	1024 px	3
Nano Banana 2 Lite	Gemini 3.1 Flash-Lite Image	1024 px	few, not its use case
Nano Banana 2	Gemini 3.1 Flash Image	4096 px	up to 14
Nano Banana Pro	Gemini 3 Pro Image	4096 px	up to 14

The difference between 2 and Pro is not "quality in general". Pro spends longer on the scene and holds geometry better when the frame has several people and objects in a complex arrangement. On a single object you will most likely not see the difference, but you will pay more.

What Nano Banana 2 does well

• Resolution up to 4096 pixels. There are steps of 512, 1K, 2K and 4K, so you can take exactly what you need and not overpay for pixels nobody will see.
• Up to 14 references at once: ten for objects and four for characters. This is its main difference from the younger generations.
• Readable text in the frame. Lettering comes out legible, which is still rare for generative models.
• Pulling facts from search. The model can use web search when the prompt contains something it does not know by heart.

How to write a prompt

This scheme works: object, then material and detail, then light, then background, then frame format. The model responds well to specifics and poorly to evaluative words.

A matte white ceramic mug on a wooden table.
Close-up, the object takes up two thirds of the frame.
Soft diffused light from the left, a light shadow on the right.
Background: a blurred kitchen in light tones.
Format 4:5, vertical.

And this is what you should not do:

Anti-example: "beautiful mug, super quality, 8k, ultra detailed, masterpiece".

"Beautiful" and "masterpiece" carry no visual information: the model fills them in for you, and every run fills them in its own way. "8k" is simply ignored here, because resolution is set by a separate setting, not by words in the prompt. And without a description of light and background, two runs in a row give two different frames, and you will not be able to build a series out of them.

Need a series of similar cards? Fix the light, background and angle word for word and change only the object itself. This is the only way to get consistency between frames without a fixed seed.

Which generation to choose for the task

Task	Generation
Marketplace cards, previews, social media	Nano Banana 2 in 1K
Print, large format, poster	Nano Banana 2 or Pro in 4K
A complex scene with several people	Pro
Fast idea iteration, drafts	the first version or 2 Lite
Editing one frame over several passes	Nano Banana 2
A collage from many references	Nano Banana 2 or Pro

About the fourth generation: 2 Lite

Released on June 30, 2026: the fastest and the cheapest in the family, but with the same 1024-pixel ceiling and weak at editing finished images. Lite has one purpose: when you need a lot of pictures fast and the resolution requirements are modest.

A separate breakdown with speed measurements and where it fits is in the article about Nano Banana 2 Lite.

How to use it in Pixyn

In Pixyn all live Nano Banana generations are collected in one group: you switch the generation in the same selector, without going to another page. That is the most convenient way to compare them on one task.

Usage starts from 3 tokens per image. What tokens are and why generations cost differently is explained in a separate card, current packs are on the pricing page.

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Try it. Create an account: you get 6 tokens at sign-up and an image costs from 3, so the first generation is available right away, without a top-up.

FAQ

How is "nano banana" different from Gemini? It is not: they are the same thing. "Nano Banana" is a code name that stuck, while the official model name contains the word Gemini. Search also shows typos like "nano babana" or "neno banana", and they refer to the same lineup.

Why does one model have 4K and another does not? This is a limit of the models themselves, not of the platform. The first version and 2 Lite have output fixed at 1024 pixels, so the resolution selector simply does not appear for them.

Can I upload my own photo and ask for changes? Yes, all generations accept an image as input. For many edits in a row, Nano Banana 2 is the better pick: it is better suited for this than the younger ones.

What should I choose if I am not sure? Nano Banana 2 in 1K. It is the middle that covers most tasks, and if the result is not enough, repeat the same prompt on Pro.

A separate review of the senior generation is in the article about Nano Banana Pro.

Sources: the Nano Banana family page at Google DeepMind, Gemini API image generation documentation.