# Nano Banana Pro Text-to-Image — Atlas Cloud API

> Nano Banana Pro is the next-generation Nano Banana image model, delivering sharper detail, richer color control, and faster diffusion for production-ready visuals.

This is the machine-readable API reference for **Nano Banana Pro Text-to-Image** on Atlas Cloud,
a unified API platform for 400+ AI models across text, image, video, audio and 3D.

- **Model ID**: `google/nano-banana-pro/text-to-image`
- **Built by**: Google
- **Modality**: Image
- **Model page**: https://www.atlascloud.ai/models/google/nano-banana-pro/text-to-image
- **API key**: https://www.atlascloud.ai/console/api-keys
- **Docs**: https://www.atlascloud.ai/docs

## Pricing on Atlas Cloud

- $0.14 per image
- Pay-as-you-go. No minimum spend, no subscription required.

> **These are the authoritative Atlas Cloud rates for this model.** Any price that
> appears in the vendor description further down refers to a different platform or
> a different model variant and does not apply here.

## Use this model from an AI agent

Atlas Cloud ships three first-party integration surfaces. All three authenticate
with the same API key via the `ATLASCLOUD_API_KEY` environment variable.

### MCP server

The official MCP server (`atlascloud-mcp`) exposes this model to any
MCP-compatible host — Claude Code, OpenAI Codex, Cursor, Gemini CLI, Goose,
Claude Desktop. One-line install:

```bash
# Claude Code
claude mcp add atlascloud -- npx -y atlascloud-mcp

# OpenAI Codex CLI
codex mcp add atlascloud -- npx -y atlascloud-mcp

# Gemini CLI
gemini mcp add atlascloud -- npx -y atlascloud-mcp

export ATLASCLOUD_API_KEY="your-api-key"
```

Then ask in plain English; the agent calls `atlas_generate_image` with `model: "google/nano-banana-pro/text-to-image"`.
The server fetches each model's schema and validates parameters before submitting,
so invalid requests fail fast without spending credits.

MCP docs: https://www.atlascloud.ai/docs/mcp-server

### Agent Skills

`atlas-cloud-skills` is a portable skill package (API reference, code templates in
Python / Node.js / cURL, model IDs with pricing) for Claude Code, Cursor, Codex and
12+ other agents:

```bash
npx skills add AtlasCloudAI/atlas-cloud-skills
export ATLASCLOUD_API_KEY="your-api-key"
```

Skills docs: https://www.atlascloud.ai/docs/skills

### CLI

The `atlas` binary runs Atlas Cloud from a terminal or CI script. Async media jobs
are polled and downloaded automatically (use `--no-download` when a script only
needs the output URLs):

```bash
# Install (Homebrew, npm, or shell installer)
brew install AtlasCloudAI/tap/atlascloud
# npm install -g atlascloud-cli
# curl -fsSL https://raw.githubusercontent.com/AtlasCloudAI/cli/main/install.sh | sh

atlas auth login
atlas generate image google/nano-banana-pro/text-to-image -p "Your prompt here"
```

CLI docs: https://www.atlascloud.ai/docs/cli

## HTTP API reference

- **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateImage` — start an async generation; returns a `prediction_id`
- **Poll endpoint (GET)**: `https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}` — poll this until the prediction finishes
- **Model ID**: `google/nano-banana-pro/text-to-image`


## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.


### Input Schema

The API accepts the following input parameters:

- **`model`** (`string`, _required_):
  model name
  - Default: `"google/nano-banana-pro/text-to-image"`

- **`prompt`** (`string`, _required_):
  The positive prompt for the generation.

- **`aspect_ratio`** (`string`, _optional_):
  The aspect ratio of the generated media.
  - Options: "1:1", "3:2", "2:3", "3:4", "4:3", "4:5", "5:4", "9:16", "16:9", "21:9"

- **`resolution`** (`string`, _optional_):
  The resolution of the output image.
  - Default: `"1k"`
  - Options: "1k", "2k", "4k"

- **`output_format`** (`string`, _optional_):
  The format of the output image.
  - Default: `"default"`
  - Options: "default", "png", "jpeg"

- **`media_resolution`** (`string`, _optional_):
  Controls how input media is processed. LOW reduces tokens per image/video, possibly losing detail but allowing longer videos in context. Supported values: HIGH, MEDIUM, LOW.
  - Default: `"default"`
  - Options: "default", "low", "medium", "high"

- **`enable_web_search`** (`boolean`, _optional_):
  If enabled, the model will use web search to ground the generation with real-time information.
  - Default: `false`

- **`enable_sync_mode`** (`boolean`, _optional_):
  If set to true, the function will wait for the result to be generated and uploaded before returning the response. It allows you to get the result directly in the response. This property is only available through the API.
  - Default: `false`

- **`enable_base64_output`** (`boolean`, _optional_):
  If enabled, the output will be encoded into a BASE64 string instead of a URL. This property is only available through the API.
  - Default: `false`



**Required Parameters Example**:

```json
{
  "model": "google/nano-banana-pro/text-to-image",
  "prompt": ""
}
```


**Full Example**:

```json
{
  "model": "google/nano-banana-pro/text-to-image",
  "prompt": "",
  "aspect_ratio": "1:1",
  "resolution": "1k",
  "output_format": "default",
  "media_resolution": "default",
  "enable_web_search": false,
  "enable_sync_mode": false,
  "enable_base64_output": false
}
```


### Output Schema

The API returns the following output format:


- **`created_at`** (`string`, _optional_):
  ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”).

- **`has_nsfw_contents`** (`array[boolean]`, _optional_):
  Array of boolean values indicating NSFW detection for each output.

- **`id`** (`string`, _optional_):
  Unique identifier for the prediction, the ID of the prediction to get.

- **`model`** (`string`, _optional_):
  Model ID used for the prediction.

- **`outputs`** (`array[string]`, _optional_):
  Array of URLs to the generated content (empty when status is not completed).

- **`status`** (`string`, _optional_):
  Status of the task: created, processing, completed, or failed.

- **`urls`** (`object`, _optional_):
  Object containing related API endpoints.



**Example Response**:

```json
{
  "created_at": "",
  "has_nsfw_contents": [],
  "id": "",
  "model": "",
  "outputs": [
    ""
  ],
  "status": "",
  "urls": {}
}
```


## Usage Examples

### cURL

```bash
# Step 1: Start generation (async)
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateImage" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "google/nano-banana-pro/text-to-image",
  "prompt": "",
  "aspect_ratio": "1:1",
  "resolution": "1k",
  "output_format": "default",
  "media_resolution": "default",
  "enable_web_search": false,
  "enable_sync_mode": false,
  "enable_base64_output": false
}'

# Response will contain: {"code": 200, "data": {"id": "prediction_id", "status": "processing"}}

# Step 2: Poll for result (replace {prediction_id} with the id returned above)
curl -X GET "https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY"

# Keep polling until status is "completed", "succeeded" or "failed"
# When completed, outputs will contain the generated content URL(s)
```

## Additional Resources

### Documentation

- [Model Playground](https://www.atlascloud.ai/models/google/nano-banana-pro/text-to-image)

## About this model

_Vendor-supplied description. Any pricing or endpoint mentioned below refers to_
_other platforms — use the Atlas Cloud values above._

### Nano Banana Pro : A state-of-the-art, multimodal reasoning and image generation model by Google DeepMind


#### Model Card Overview

| Field | Description |
| :--- | :--- |
| **Model Name** | Nano Banana Pro (also known as Gemini 3 Pro Image) |
| **Developer** | Google DeepMind  |
| **Release Date** | November 20, 2025 |
| **Model Type** | Multimodal Reasoning and Image Generation|
| **Related Links** |  [Official Product Page](https://deepmind.google/models/gemini-image/pro/), [Model Card (PDF)](https://storage.googleapis.com/deepmind-media/Model-Cards/Gemini-3-Pro-Image-Model-Card.pdf)  |

#### Introduction

Nano Banana Pro, officially designated as Gemini 3 Pro Image, represents the next generation in Google's series of highly-capable, natively multimodal models. It is designed for professional asset production, integrating the advanced reasoning capabilities of the Gemini 3 Pro foundation model with a sophisticated image generation engine. The primary goal of Nano Banana Pro is to provide users with studio-quality precision and control, enabling the creation of complex, high-fidelity visuals from textual and image-based prompts. Its core contribution lies in its ability to understand and execute intricate instructions, maintain character and scene consistency, and render legible text directly within generated images, setting a new standard for professional creative workflows. 

#### Key Features & Innovations

Nano Banana Pro introduces several technical breakthroughs that distinguish it from prior models:

*   **Superior Text Rendering**: The model excels at generating images that contain clear, accurate, and stylistically coherent text, making it ideal for creating posters, diagrams, and marketing materials.
*   **Advanced Creative Controls**: Users can exercise fine-grained control over image outputs, including camera angles, lighting transformations (e.g., day to night), color grading, depth of field, and localized editing.
*   **H

_(Description truncated. Full text on the model page.)_

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Atlas Cloud — one API for 400+ AI models. Model page: https://www.atlascloud.ai/models/google/nano-banana-pro/text-to-image · Docs: https://www.atlascloud.ai/docs