# Nano Banana 2 Lite Text-to-Image Developer — Atlas Cloud API

> Google's fastest and most cost-efficient Nano Banana image model, turning natural-language text prompts into high-quality 1k images in as little as 4 seconds for rapid, high-volume generation.

This is the machine-readable API reference for **Nano Banana 2 Lite Text-to-Image Developer** on Atlas Cloud,
a unified API platform for 400+ AI models across text, image, video, audio and 3D.

- **Model ID**: `google/nano-banana-2-lite/text-to-image-developer`
- **Built by**: Google
- **Modality**: Image
- **Model page**: https://www.atlascloud.ai/models/google/nano-banana-2-lite/text-to-image-developer
- **API key**: https://www.atlascloud.ai/console/api-keys
- **Docs**: https://www.atlascloud.ai/docs

## Pricing on Atlas Cloud

- $0.028 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-2-lite/text-to-image-developer"`.
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-2-lite/text-to-image-developer -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-2-lite/text-to-image-developer`


## 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-2-lite/text-to-image-developer"`

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

- **`aspect_ratio`** (`string`, _optional_):
  The aspect ratio of the generated media.
  - Default: `"auto"`
  - Options: "auto", "1:1", "3:2", "2:3", "3:4", "4:3", "4:5", "5:4", "9:16", "16:9", "21:9", "4:1", "1:4", "8:1", "1:8"

- **`thinking_level`** (`string`, _optional_):
  Controls the amount of internal reasoning the model performs before generating a response. Higher levels may improve quality on complex tasks but increase latency.
  - Default: `"default"`
  - Options: "default", "high", "minimal"

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

- **`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-2-lite/text-to-image-developer",
  "prompt": ""
}
```


**Full Example**:

```json
{
  "model": "google/nano-banana-2-lite/text-to-image-developer",
  "prompt": "",
  "aspect_ratio": "auto",
  "thinking_level": "default",
  "resolution": "1k",
  "enable_sync_mode": false,
  "enable_base64_output": false
}
```


### Output Schema

The API returns the following output format:


- **`code`** (`integer`, _optional_):
  HTTP status code of the response.

- **`message`** (`string`, _optional_):
  Human-readable message; non-empty on failure.

- **`data`** (`object`, _optional_):
  - Properties:
    - **`id`** (`string`, _optional_):
      Unique identifier for the prediction.

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

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

    - **`urls`** (`object`, _optional_):
      Object containing related API endpoints.
      - Properties:
        - **`get`** (`string`, _optional_):
          URL to poll for the prediction result.


    - **`has_nsfw_contents`** (`array[boolean]`, _optional_):
      Array of boolean values indicating NSFW detection for each output. Null if not applicable.

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

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

    - **`error`** (`string`, _optional_):
      Error message if the task failed, empty string otherwise.

    - **`error_code`** (`integer`, _optional_):
      Error code if the task failed.

    - **`executionTime`** (`number`, _optional_):
      Total execution time in milliseconds.

    - **`timings`** (`object`, _optional_):
      Detailed timing breakdown.
      - Properties:
        - **`inference`** (`number`, _optional_):
          Inference time in milliseconds.


    - **`stt_result`** (`object`, _optional_):
      The speech-to-text transcription result.




**Example Response**:

```json
{
  "code": 0,
  "message": "",
  "data": {
    "id": "",
    "model": "",
    "outputs": [
      ""
    ],
    "urls": {
      "get": ""
    },
    "has_nsfw_contents": [],
    "status": "",
    "created_at": "",
    "error": "",
    "error_code": 0,
    "executionTime": 0,
    "timings": {
      "inference": 0
    },
    "stt_result": {}
  }
}
```


## 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-2-lite/text-to-image-developer",
  "prompt": "",
  "aspect_ratio": "auto",
  "thinking_level": "default",
  "resolution": "1k",
  "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-2-lite/text-to-image-developer)

## About this model

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

#### Google Nano Banana 2 Lite — Text-to-Image Developer

**Nano Banana 2 Lite** (Gemini 3.1 Flash-Lite Image, `gemini-3.1-flash-lite-image`) is Google's **fastest and most cost-efficient** image model in the Nano Banana family. This variant turns a natural-language text prompt into a high-quality image in **as little as 4 seconds**, making it purpose-built for rapid iteration, high-throughput pipelines, and cost-sensitive workflows — from blank page to finished layout in a single, near-instant step.

It replaces the original Nano Banana (Gemini 2.5 Flash Image) with improved visual quality, better world knowledge, stronger character consistency, and more legible in-image text — all while being faster and cheaper.

#### 🌟 Why it stands out

- **Lightning-fast generation** — Produces images in roughly 4 seconds, delivering the lowest latency in its class so you can iterate faster than you can rethink the prompt.
- **Reliable prompt adherence** — Faithfully interprets subjects, backgrounds, and spatial relationships to build contextually correct compositions.
- **Strong character consistency** — Keeps character identities and object fidelity stable across multiple generations, ideal for storyboards and series content.
- **Legible in-image text** — Renders readable text and quick localizations directly into generated images for posters, mockups, and social assets.
- **World knowledge** — Drafts accurate contextual scenes, rough data visualizations, and location-specific mockups grounded in real-world understanding.
- **Most cost-efficient tier** — The budget-friendly member of the Nano Banana family, engineered for high-volume generation at scale.

#### ⚙️ Capabilities

_(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-2-lite/text-to-image-developer · Docs: https://www.atlascloud.ai/docs