Nano Banana Pro
by Google DeepMind
Studio-grade images with text that actually reads, up to 4K.
What it is
Nano Banana Pro is Google DeepMind's image model built on Gemini 3, described by its makers as a way to "create and edit images with studio-quality levels of precision and control". In practice that means two things you cannot get from most image models: text you can put in front of a client, and a scene you can keep editing without it drifting into something else.
It renders at 1K, 2K and 4K, and it draws on Gemini's knowledge of the real world, so a prompt that names a real technique, a real material or a real place lands closer than it would elsewhere. Where it earns its keep is the second pass: adjusting the angle, the depth of field, the colour grade, the lighting or the aspect ratio of something you already have.
In this studio it sits on both the image and the edit side, so the same model that makes the shot is the one that revises it. Open it in the Studio, describe what you want, and change one thing at a time.
What it is good at
Google states it can "generate clear text for posters and intricate diagrams". That is the difference between an image you use and an image you regenerate eleven times.
Consistency of up to five characters and fidelity of up to fourteen objects in a single workflow, per Google. Enough for a product line-up or a small ensemble across a set of images.
Angle, depth of field, colour grading, lighting and aspect ratio are things you adjust rather than re-prompt. Pair it with the camera and lens presets in the Studio and you are describing a shot, not a wish.
Gemini's real-world knowledge means naming a real lens, a real fabric or a real location does actual work in the prompt instead of just adding words.
Where it struggles
- Google names the limits itself: small faces, accurate spelling and fine detail are where visual and text fidelity slip.
- Its real-world knowledge is "extensive but not infallible", particularly for anything data-driven , do not treat a generated chart as a source.
- Advanced edits such as masked editing or a major lighting change can come out looking unnatural.
- Character consistency is strong but not guaranteed. For a series that has to hold, anchor it with a reference image.
How to prompt it
Google's own guidance is to be detailed: think about the characters, the setting and the overall feel, and write them down. This is not a model that rewards three words. Name the subject, then the environment, then the light, then the finish , and if something has to be legible, spell it out in quotes.
An example that shows what that means
A folded matte-black business card standing upright on a raw concrete surface, the words "NORTH & FIELD" set in a thin uppercase serif across the top third, shot on an 85mm lens at f/2.8, single soft window light from the left, a long soft shadow to the right, neutral photographic colour, fine paper grain visible.
What we offer here
Straight from the catalogue, so this list never goes stale. The price is the provider’s published rate with our markup on top, and it is on the button before you run anything.
Questions
What makes this different from the standard Nano Banana?
Resolution and control. Pro renders up to 4K and is built for the second pass , changing the angle, the light or the grade on something you already made. The standard model is built for speed and volume.
Can it put real text in an image?
Yes, and that is one of the reasons to reach for it. Google states it generates clear text for posters and diagrams. Put the exact wording in quotes in your prompt. Small type is still where it slips.
Will the same person turn up in every image?
Up to five characters stay consistent within a workflow, per Google, but it is not a guarantee. For a series that has to hold, lock the face with a reference image , that is what the Keep the same character tool does.
What does it cost here?
The rate comes straight from the provider's published price with our markup on top, and it is shown on the button before you run anything. Nothing on this page is a number we invented.