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Nano Banana is Google’s name for Gemini’s native image-generation and editing capabilities, accessed through the Gemini API using model identifiers. You can provide an image and a text instruction to create or edit an image; for video generation or editing, use a separate video model such as Veo or Gemini Omni Flash.
This guide explains how to choose an image model, send an image-edit request, handle the result, and understand where video fits. Check Google’s live documentation before using model IDs or SDK request details, since these can change.
What is the Nano Banana API?
“Nano Banana API” is a convenient name for using Gemini API image capabilities. It is not a separate API product. Google’s image-generation guide describes Nano Banana as the name for Gemini’s native image-generation capabilities and shows conversational image editing by pairing an image with a natural-language instruction.
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The image guide also describes using video as context to generate a new image, such as a thumbnail or artwork inspired by a scene. That is not the same as editing or exporting a video. Google lists video-generation and editing capabilities separately in its model catalog.
Which Nano Banana model should you choose?
| Model | Model ID | Documented positioning |
|---|---|---|
| Nano Banana 2.1 | gemini-nano-banana-2.1 | High-efficiency image generation and conversational editing; the guide describes 1K, 2K, and 4K output. |
| Nano Banana 2 Lite | gemini-3.1-flash-lite-image | Speed and cost efficiency; supports 1K output and is not optimized for multiple reference inputs or sequential multi-turn editing. |
| Nano Banana 2 | gemini-3.1-flash-image | Previous-generation high-efficiency option. |
| Nano Banana Pro | gemini-3-pro-image | More complex professional visual tasks. |
| Nano Banana | gemini-2.5-flash-image | Legacy model; consult the guide’s migration recommendations before starting a new integration. |
Choose based on your needs: speed and throughput, output resolution, text and layout requirements, reference-image fidelity, multi-turn consistency, and whether video input is needed. No model is universally best. These names and IDs are volatile; verify them in Google’s image-generation guide and model catalog before implementing.
Set up an image-generation request
- Choose a supported Nano Banana model in Google’s current image-generation guide.
- Initialize the Google GenAI client using the current SDK instructions for your language.
- Provide a text prompt, or pair a source image with a text instruction for an edit.
- If needed, set the documented image response format, including MIME type, aspect ratio, and image size.
- Inspect the interaction response and decode the returned image data using the current guide’s example for your language.
- Review the result rather than assuming the model followed every instruction exactly.
The official guide provides REST, Python, and JavaScript examples using the Gemini API Interactions endpoint. SDK method names, request fields, model IDs, and availability can change. Follow the live getting-started guide and image documentation; the examples there are documentation examples, not a claim that code has been tested here.
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Edit an image with a prompt
For an edit, send the source image together with a clear instruction describing the change. State what should change and what should remain consistent. For example, ask to replace the background while retaining the subject and composition, or request a different finish while preserving the object’s shape and lighting.
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- Provide the source image and a natural-language editing instruction in the format shown in the current guide.
- Read the interaction response and handle its image output according to the documented response structure.
- Check the result for unintended changes, then refine the instruction if needed.
Generative editing does not guarantee pixel-perfect preservation or an exact number of outputs. Treat instructions such as “change only the background” as guidance, not a guarantee. Use a conventional editor when precise masking or exact preservation is essential.
How image and video models work together
Nano Banana’s documented video-input capability uses a video as context to generate a new image. It does not establish that Nano Banana edits or returns a video. For video creation and editing, Google’s model catalog lists separate video models, including Veo 3.1, Veo 3.1 Lite, and Gemini Omni Flash.
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| Need | Capability to investigate |
|---|---|
| Create or edit a still image | Nano Banana image-generation and conversational editing capabilities. |
| Create a still inspired by video content | Video input as context for image generation in supported Nano Banana models. |
| Generate or edit video | Separate video models, such as Veo or Gemini Omni Flash; verify current capabilities and request formats. |
| Use a generated still as a video starting frame | The Veo guide documents an image-to-video workflow; confirm the current method and model details there. |
A practical multi-model workflow is to create and review a still with Nano Banana, then use it as a starting frame or visual reference in a video model. Finish the resulting footage in an editor if you need precise cuts, captions, audio, or timeline control. Consult Google’s Veo guide and model catalog for current video capabilities and implementation details.
Rights and output caveats
Use uploaded images only when you have the necessary rights. Follow Google’s content policies, and review outputs for unintended or inaccurate details. Google’s image-generation guide states that generated images include a SynthID watermark and notes that the model may not follow the exact requested number of image outputs.
FAQ
Is Nano Banana a separate API?
No. Nano Banana is Google’s name for Gemini’s native image-generation and editing capabilities. API requests use model identifiers through the Gemini API.
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Can Nano Banana directly edit or export a video?
The cited image guide supports using video as context to generate a new image; it does not establish that Nano Banana returns an edited video. Google lists video-generation and editing capabilities separately under video models.
How do I edit an image with the Gemini API?
Follow the current image-generation guide: provide the source image and a natural-language instruction, then inspect and handle the image output in the interaction response.
Which Nano Banana model should I use?
It depends on your requirements for speed, resolution, reference inputs, editing consistency, and task complexity. Compare the current model descriptions in Google’s image guide and verify model availability before building against an ID.
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Does generated output always follow my instructions exactly?
No. Review image results for unintended changes, and do not assume the model will produce an exact number of outputs. Use conventional editing tools when exact control is required.
Can I upload any image for editing?
Only upload images for which you have the necessary rights, and follow Google’s applicable policies.
Quick Recap
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