# Nano Banana

Source: https://docs.prodia.com/models/nano-banana/

Nano Banana is Google's image generation and editing model. It is the model that powers the conversational, prompt-driven image editing in the Gemini app — you describe what you want changed in natural language, and the model edits the image while preserving everything else. On Prodia, both modes are exposed as flat-rate jobs that complete in around 8 seconds.

### Architecture

Nano Banana is a multimodal model built on Google's Gemini family. It accepts text and images in the same context window, which is what makes its editing behavior different from a typical diffusion img2img: rather than running noise through a pre-conditioned latent, the model reads the input image as visual tokens and reasons about which regions the prompt describes. In practice this means edits stay tightly localized — change "the puppy's collar" and the rest of the scene, lighting, and pose stay frozen.

The text-to-image variant uses the same model with no input images, generating output from prompt and aspect ratio alone.

### When to use Nano Banana

- *Localized edits to existing images* — adding, removing, or modifying a specific element while keeping the rest of the image unchanged. Identity preservation, prop swaps, expression edits, clothing changes
- *Multi-image composition* — img2img.v2 accepts up to 3 input images, useful for combining a subject from one photo with a setting from another
- *Conversational prompt style* — the model responds well to natural-language instructions ("add a red bow tie", "make it nighttime") rather than the keyword-heavy prompts used for diffusion models
- *Flat per-job pricing* — every job is $0.039 regardless of resolution or aspect ratio, so cost is predictable

For photorealistic generation with style presets and high-resolution output up to 4096px, [FLUX.2](https://docs.prodia.com/models/flux-2/) is a stronger choice. For native text rendering inside images, see [Recraft V4](https://docs.prodia.com/models/recraft-v4/). For higher-fidelity Google models with selectable resolution up to 4K, see [Gemini 3](https://docs.prodia.com/models/gemini-3/).

### Job types

| Job type                           | Description                                                | ETA  |
| ---------------------------------- | ---------------------------------------------------------- | ---- |
| `inference.nano-banana.txt2img.v2` | Generate an image from a text prompt                       | \~8s |
| `inference.nano-banana.img2img.v2` | Edit one or more input images (up to 3) with a text prompt | \~8s |
| `inference.nano-banana.img2img.v1` | Single-image editing (deprecated — use v2)                 | \~8s |

The `nano-banana` processor on Prodia also serves Google's higher-tier Gemini image models with selectable resolution up to 4K:

| Job type                                | Description                                                      | ETA   |
| --------------------------------------- | ---------------------------------------------------------------- | ----- |
| `inference.gemini-3-pro.txt2img.v1`     | Gemini 3 Pro text-to-image                                       | \~10s |
| `inference.gemini-3-pro.img2img.v1`     | Gemini 3 Pro image-to-image (up to 3 inputs)                     | \~12s |
| `inference.gemini-3-1-flash.txt2img.v1` | Gemini 3.1 Flash text-to-image, optional Google Search grounding | \~30s |
| `inference.gemini-3-1-flash.img2img.v1` | Gemini 3.1 Flash image-to-image (up to 14 inputs)                | \~35s |

> note:
>
> The deprecated `inference.nano-banana.img2img.v1` accepts a single `image` filename and is kept for backwards compatibility. New integrations should use `img2img.v2`, which accepts an `images` array and exposes the `aspect_ratio` parameter.

### Parameters

*`inference.nano-banana.txt2img.v2`:*

- `prompt` (required) — text description of the desired output, up to 2,500 characters
- `aspect_ratio` — one of `1:1` (default), `2:3`, `3:2`, `3:4`, `4:3`, `4:5`, `5:4`, `9:16`, `16:9`, `21:9`
- `include_messages` — when `true`, the response also returns `message.txt` parts containing the model's natural-language reasoning

*`inference.nano-banana.img2img.v2`:*

- `prompt` (required) — describe the edit you want, up to 2,500 characters
- `images` — array of 1–3 input image filenames sent as multipart `input` parts
- `aspect_ratio` — one of `auto` (default — match the first input), `1:1`, `2:3`, `3:2`, `3:4`, `4:3`, `9:16`, `16:9`, `21:9`
- `include_messages` — see above

### Prompting tips

- *Describe the change, not the whole scene.* For img2img edits, write what should be different ("add a red bow tie") rather than re-describing the entire image — the model already sees the input
- *Anchor preservation explicitly.* Phrases like "keep everything else exactly the same" reduce drift in untouched regions, especially for subtle edits
- *Use natural language.* Nano Banana is a multimodal LLM, not a CLIP-conditioned diffusion model. Conversational instructions outperform comma-separated keyword prompts
- *Reference inputs by position.* When passing multiple images to `img2img.v2`, refer to them in order — "the subject from the first image, in the setting from the second image"
- *Pick `aspect_ratio` deliberately for txt2img.* The default is `1:1`. For social, web, or phone use cases, set `9:16` or `16:9` rather than upscaling/cropping after the fact

### Examples

Text-to-image at 16:9:

```json
{
  "type": "inference.nano-banana.txt2img.v2",
  "config": {
    "prompt": "a cute corgi puppy in a sunny meadow with wildflowers, soft natural light, photorealistic",
    "aspect_ratio": "16:9"
  }
}
```

![Nano Banana txt2img — corgi puppy in a wildflower meadow](https://docs.prodia.com/llms/assets/0cbcf6ef6baa-nano-banana-txt2img.jpg)

Image-to-image edit (using the previous output as input):

```json
{
  "type": "inference.nano-banana.img2img.v2",
  "config": {
    "prompt": "Add a small red bow tie to the puppy. Keep everything else exactly the same.",
    "aspect_ratio": "16:9"
  }
}
```

![Nano Banana img2img — same corgi with a red bow tie added](https://docs.prodia.com/llms/assets/2d856b1f0c39-nano-banana-img2img.jpg)

Notice how the puppy's pose, fur, the wildflowers, the lighting, and the background are all preserved — only the bow tie is added.

Multi-image composition (up to 3 inputs):

```json
{
  "type": "inference.nano-banana.img2img.v2",
  "config": {
    "prompt": "Place the product from the first image onto the wooden surface in the second image, matching the warm lighting.",
    "images": ["product.jpg", "surface.jpg"],
    "aspect_ratio": "3:2"
  }
}
```

### Guides

[Generating Images](https://docs.prodia.com/guides/generating-images/) — Step-by-step guide for generating images with Prodia.

[Transforming Images](https://docs.prodia.com/guides/transforming-images/) — Guide for image-to-image transformation.