# Nano Banana Pro API

> Google's strongest image model, with reliable lettering, complex layouts and output up to 4K.

A Gemini-based image model that reasons about the prompt before drawing, so posters, infographics, menus and product shots with readable text come out right far more often than with diffusion-only models. Pick 1K, 2K or 4K output and any common aspect ratio, and optionally let it look things up on the web to ground the picture in current facts. Up to four images per request.

- Model id: `nano-banana-pro`
- Made by: Google
- Category: Text to Image
- Output: image
- Price: from $0.15 / image (cheapest run $0.15 (150 API credits))
- Run: `POST https://api.doitong.com/v1/run/nano-banana-pro`
- Quote: `POST https://api.doitong.com/v1/quote/nano-banana-pro`
- Docs page: https://doitong.com/developers/models/nano-banana-pro

## Pricing

Price: **from $0.15 / image** (the lowest tier; the quote prices your exact input). Billed per generated image (`num_images`, default 1).

Price rules (the first rule that matches the input wins; a parameter you leave out counts as its default):

- When `resolution` = 4K and `enable_web_search` = true: $0.315 (315 API credits) / image
- When `resolution` = 4K: $0.30 (300 API credits) / image
- When `enable_web_search` = true: $0.165 (165 API credits) / image

The full example input below costs $0.15 = 150 API credits (1 image × 150 API credits).

Prices are the upstream price in USD, paid from the API balance in API credits (1000 API credits = 1 USD). `POST https://api.doitong.com/v1/quote/nano-banana-pro` with the same JSON body returns the exact price for that input; the quote is exactly what a run charges. Invalid input is never charged and failed or canceled requests are refunded automatically.

## Input parameters

Send either the canonical name or the native field name (not both). Canonical names are the same across models.

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `prompt` |  | string | yes |  | 3 – 50000 characters | Text instructions used to generate an image. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 4 | Image count requested for generation. |
| `seed` |  | integer \| null | no |  |  | Seed value that initializes random-number generation. |
| `aspect_ratio` |  | enum (string) \| null | no | `1:1` | `auto`, `21:9`, `16:9`, `3:2`, `4:3`, `5:4`, `1:1`, `4:5`, `3:4`, `2:3`, `9:16` | Aspect ratio for the resulting image. |
| `output_format` |  | enum (string) | no | `png` | `jpeg`, `png`, `webp` | File format for the resulting image. |
| `safety_tolerance` |  | enum (string) | no | `4` | `1`, `2`, `3`, `4`, `5`, `6` | Set content-moderation tolerance between the least restrictive level, 6, and the strictest level, 1, which blocks most content. |
| `system_prompt` |  | string | no | `` | ≤ 50000 characters | Optional request-wide persona and output-style guidance, delivered to Gemini as a system instruction or to OpenAI-compatible providers as a system message. Nothing is sent for this instruction when the value is blank. |
| `resolution` |  | enum (string) | no | `1K` | `1K`, `2K`, `4K` | Resolution for the output image. |
| `limit_generations` |  | boolean | no | `true` |  | Experimental generation cap: enabling `True` overrides any image-count directions in the prompt and restricts each prompting round to 1 generation. |
| `enable_web_search` |  | boolean | no | `false` |  | Web search toggle for image generation, allowing the model to incorporate up-to-date information found online into the image. |

## Example input

Required parameters only:

```json
{
  "prompt": "A minimalist poster for a jazz night called \"Blue Hour\", a saxophone silhouette against a deep blue sky, bold sans-serif title"
}
```

A fuller example:

```json
{
  "prompt": "A minimalist poster for a jazz night called \"Blue Hour\", a saxophone silhouette against a deep blue sky, bold sans-serif title",
  "aspect_ratio": "3:4",
  "resolution": "2K"
}
```

## Run it

Set `DOITONG_API_KEY` to a key from https://doitong.com/developers/dashboard#keys. `?wait=20` returns the finished request in the same call when it is ready within 20 seconds; otherwise poll `GET /requests/{id}` (it also accepts `?wait=`), or pass `webhook_url`.

### curl

```bash
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/nano-banana-pro?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "A minimalist poster for a jazz night called \"Blue Hour\", a saxophone silhouette against a deep blue sky, bold sans-serif title",
    "aspect_ratio": "3:4",
    "resolution": "2K"
  }'

# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.com/v1/requests/REQUEST_ID?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY"
```

### JavaScript

```javascript
const API = "https://api.doitong.com/v1";
const headers = {
  "Authorization": "Bearer " + process.env.DOITONG_API_KEY,
  "Content-Type": "application/json",
};

// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/nano-banana-pro?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "prompt": "A minimalist poster for a jazz night called \"Blue Hour\", a saxophone silhouette against a deep blue sky, bold sans-serif title",
    "aspect_ratio": "3:4",
    "resolution": "2K"
  }),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);

// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
  res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
  request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
```

### Python

```python
import os
import requests

API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}

payload = {
    "prompt": "A minimalist poster for a jazz night called \"Blue Hour\", a saxophone silhouette against a deep blue sky, bold sans-serif title",
    "aspect_ratio": "3:4",
    "resolution": "2K",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/nano-banana-pro", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
    raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])

# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
    request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
    raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
```

### MCP

The MCP server at `https://api.doitong.com/v1/mcp` exposes the tools `search_models`, `get_model`, `quote`, `run`, `get_request`, `cancel_request`, `list_requests`, `create_upload` and `get_account`. A `run` call for this model:

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "run",
    "arguments": {
      "model_id": "nano-banana-pro",
      "input": {
        "prompt": "A minimalist poster for a jazz night called \"Blue Hour\", a saxophone silhouette against a deep blue sky, bold sans-serif title",
        "aspect_ratio": "3:4",
        "resolution": "2K"
      },
      "wait_seconds": 20
    }
  }
}
```

## Response

Every call returns a request object. `status` is one of `queued`, `running`, `succeeded`, `failed`, `canceled`. `outputs` lists the generated files with URLs on our storage (kept forever, or 7 days with `?storage=temporary`; `storage` says which); `output` is the model's own result object with the same URLs.

```json
{
  "id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
  "object": "request",
  "model": "nano-banana-pro",
  "status": "succeeded",
  "created_at": "2026-10-20T12:00:00Z",
  "started_at": "2026-10-20T12:00:02Z",
  "completed_at": "2026-10-20T12:00:09Z",
  "queue_position": null,
  "cost": {
    "credits": 150,
    "usd": "0.15",
    "charged": 150,
    "refunded": 0
  },
  "input": {
    "prompt": "A minimalist poster for a jazz night called \"Blue Hour\", a saxophone silhouette against a deep blue sky, bold sans-serif title",
    "aspect_ratio": "3:4",
    "resolution": "2K"
  },
  "output": {
    "images": [
      {
        "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
        "content_type": "image/jpeg",
        "file_name": "0-output.jpeg",
        "file_size": 1843200,
        "width": 1024,
        "height": 768
      }
    ],
    "description": "string"
  },
  "outputs": [
    {
      "type": "image",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_size": 1843200,
      "width": 1024,
      "height": 768,
      "stored": true
    }
  ],
  "error": null,
  "metrics": {
    "inference_seconds": 6.8
  },
  "urls": {
    "self": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `images` | array of object {url, content_type, file_name, file_size, width, height} | Images produced by the model. |
| `description` | string | Description accompanying the generated images. |

## Related models

- [Nano Banana Pro Edit](https://doitong.com/developers/models/nano-banana-pro/edit.md) (`nano-banana-pro/edit`): from $0.15 / image
- [Nano Banana 2](https://doitong.com/developers/models/nano-banana-2.md) (`nano-banana-2`): from $0.06 / image
- [FLUX.1 \[dev\]](https://doitong.com/developers/models/flux/dev.md) (`flux/dev`): $0.025 / megapixel
- [FLUX.1 \[schnell\]](https://doitong.com/developers/models/flux/schnell.md) (`flux/schnell`): $0.003 / megapixel
- [FLUX.2 \[dev\]](https://doitong.com/developers/models/flux-2.md) (`flux-2`): $0.012 / megapixel
- [FLUX.2 \[pro\]](https://doitong.com/developers/models/flux-2-pro.md) (`flux-2-pro`): $0.015 / megapixel of output image
- [GPT Image 2.5 Text to Image](https://doitong.com/developers/models/openai/gpt-image-2.5/flare/text-to-image.md) (`openai/gpt-image-2.5/flare/text-to-image`): from $0.008 / image
- [Ideogram V4.5](https://doitong.com/developers/models/ideogram/v4.5.md) (`ideogram/v4.5`): from $0.03 / image

## Links

- HTML page: https://doitong.com/developers/models/nano-banana-pro
- All models and guides for AI agents: https://doitong.com/developers/llms.txt
- OpenAPI 3.1 with this model's typed request body: https://doitong.com/developers/openapi.json?model=nano-banana-pro
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/nano-banana-pro