If you want one creator across portraits, outfits and campaign images, a generic ‘make the same person’ instruction is a weak starting point. Nano Banana can be part of a reference-led workflow, but you still need an approved identity, a clear scene brief and a review process.
This guide separates the model names from the production decisions. The prompts are original editorial examples, not benchmark results or a promise that every generation will preserve every detail.
Check which Nano Banana model you are using
Google's current image-generation guide lists Nano Banana, Nano Banana Pro, Nano Banana 2 and Nano Banana 2 Lite as distinct models. It identifies Pro with Gemini 3 Pro Image and Nano Banana 2 with Gemini 3.1 Flash Image. The legacy model is Gemini 2.5 Flash Image.
Google describes different reference and editing strengths across the family. A third-party interface can expose a narrower operation set than the underlying model. Check the specific model, supported inputs and output controls before following an example designed for another interface.
| Decision | What to record |
|---|---|
| Model | The exact visible model name, not just the Nano Banana family label |
| Input | Text-only, identity reference, product reference or an existing image edit |
| Output | Aspect ratio, requested resolution and downloadable file |
| Revision | Which details are allowed to change and which stay fixed |
How to write prompts for Nano Banana
Write a scene the model can depict: who is visible, what they are doing, where they are, how the picture is framed and where the light comes from. Put fixed identity details in a separate instruction when using a reference. Replace vague requests such as “make it professional” with concrete decisions such as a waist-up portrait, a plain background and soft window light.
The Google Nano Banana prompting guide discusses subject, composition, action, location and style. Use it alongside the API documentation: a clear brief describes the image, while the interface controls determine which inputs and output settings the model receives.
Turn a vague request into a reviewable brief
| Vague instruction | Specific replacement | What you can inspect |
|---|---|---|
| Make a good creator photo | An original adult creator seated at a cafe table, with the head and both hands visible | The crop and visible anatomy |
| Make it realistic | Soft window light, cotton texture and natural skin detail | Lighting direction and material consistency |
| Keep everything the same | Change the notebook cover only; preserve the face, pose, mug and background | The requested change and unintended revisions |
Use the builder above to generate a prompt from those decisions. It assembles your fields in your browser, requires a subject and scene, and provides a selectable result. It does not call an image model or charge generation credits. Copy the output into your chosen image workflow and attach any required reference there.
Nano Banana JSON prompt versus an API request
A Nano Banana JSON prompt can mean two different things: a creative brief saved as JSON, or the actual request body a developer sends to a provider. The JSON download in this guide is a creative brief. Its subject, scene and preservation fields organize your instructions; they are not special model controls.
{
"format": "Clout editable image brief",
"subject": "An original adult creator in a mustard overshirt",
"scene": "Seated at a cafe table with a closed green notebook",
"framing": "Medium-wide photograph with both hands visible",
"lighting": "Soft window light and natural cotton texture",
"preserve": "Approved face and hairstyle when using a reference",
"avoid": "No lettering or additional people"
}Use the plain-language output in a prompt box. For an API integration, put that prompt text inside the documented request field, supply image references in the documented format and set only supported model options. Do not send the custom brief object as if its keys were Google's request schema. Downloading JSON does not attach a reference image, set an aspect ratio or select a model.
Structured briefs help a team keep decisions consistent and revise one field at a time. They do not establish that JSON produces better images than ordinary language. Evaluate the exported result, not the appearance of the prompt format.
A small revision prompt with an actual output
Change only the forest-green notebook cover to cobalt blue. Keep the creator's face, hairstyle, hands, mustard overshirt, cream shirt, mug, table, lighting and composition unchanged. Do not add any writing to the notebook.
Open the source-and-edit example in our picture guide to download both images and review this instruction against an actual result. That pair was generated with the built-in image tool and is not a Nano Banana test. It shows the review process you should apply to your own Nano Banana exports.
Keep prompts and references aligned
If the prompt says to preserve a face but no identity image was attached, the model lacks that specific baseline. If the prompt asks for a waist-up scene while the reference crops tightly around the face, check whether the selected operation can create the new framing. If your revision changes too many details, return to the accepted image and request one change at a time.
Build an identity reference you can review
Use a clear approved portrait of an original adult character or a person whose likeness you have permission to use. Avoid beginning with a blurry screenshot or a reference where the face is obscured. Save that baseline separately from later scene outputs.
Create a short identity note: facial landmarks, hair shape, apparent age and proportions. The note helps reviewers agree on what makes the character recognizable. It complements the reference image; it does not replace it.
Start with one scene transformation
Use the creator reference for the same adult character. Make a waist-up editorial photograph in a bright pottery studio. The creator wears a mustard linen blouse and holds a plain coral ceramic mug with relaxed natural hands. Keep the face, hairstyle and proportions consistent. Soft window light, a simple pale wall and realistic fabric texture.
Approve the face before approving the background. Then check the hands, mug and clothing. If the identity is wrong, return to the original reference instead of using the failed scene as the next reference.
Do not supply a collection of contradictory portraits and expect the model to know which one defines the person. Label the role of each permitted input in your brief: identity, product, scene or style. Interface syntax for reference labels varies, so use its documented controls.
Use a precise edit for a small change
Change only the blouse color from mustard to deep blue. Preserve the creator's face, hairstyle, hand position, mug, studio background and lighting. Keep the fabric weave and natural folds.
Compare the revised image with the accepted baseline. Check the mouth, eyes, fingers and object edges even when you asked only for a color change. If those areas changed, the result needs another review or a more controlled local edit.
For an outfit campaign, use a consistent framing brief and approved garment references. Exact seams, labels and fabric patterns remain approval requirements. A generated image should not be treated as proof of physical fit or product performance.
Test continuity with a small sequence
- Neutral portrait: establish a clear identity baseline.
- Lifestyle scene: move the creator into a plausible environment.
- Wardrobe variation: change one outfit while keeping the identity.
- Product scene: add a simple interaction with a reference object.
- Local revision: change one accepted detail without restarting the whole scene.
Review the five images together. Record where the identity changed, where the prompt was ignored and how much repair was necessary. This is a practical trial design, not a success-rate claim.
Diagnose the failure instead of lengthening every prompt
| Problem | Next test |
|---|---|
| The face changes | Return to one clear identity reference and simplify the new scene |
| The edit changes unrelated details | Use a more specific revision and supported local editing controls |
| Hands or props look wrong | Choose a simpler interaction with visible contact points |
| The image is too small | Check the selected model and export settings; download the master |
| Text on a product is inaccurate | Compare the reference and use controlled finishing or a real detail image |
Keep the accepted full-resolution source, prompt and model name together. This makes it easier to reproduce the campaign direction even if a later interface update changes a control or default.
Understand image output and video handoff
A static image generator and an animation workflow are separate steps. Do not assume an image export is a GIF or that an interface offering Nano Banana also supports the exact video operation you want. Approve the image, then use an appropriate image-to-video or editing workflow.
Google states that generated images include SynthID. Follow the selected provider's current usage conditions and the publishing channel's disclosure requirements. A clean-looking export does not remove those obligations.
Build the creator and campaign together
In Clout, create your character and produce photos and videos around that recognizable identity. Keep your approved reference and campaign brief central to the workflow. Build your AI photo creator and turn the first accepted image into a reusable campaign direction.
