# Nano Banana 2 API

> Googles schnelles Gemini-Bildmodell von schnellen 0.5K-Entwürfen bis 4K, mit extremen Seitenverhältnissen und Web-Grounding.

Eine schnellere, günstigere Variante von Nano Banana Pro, die weiterhin Text in Bildern und Szenen mit mehreren Objekten gut verarbeitet. Die Ausgabe reicht von 0.5K-Vorschauen bis 4K, mit Seitenverhältnissen von 1:8 bis 8:1 für Banner und vertikale Stories. Die optionale Websuche verankert das Bild in aktuellen Fakten, und eine optionale hohe Denkstufe plant komplexe Layouts vor dem Zeichnen. Bis zu vier Bilder pro Anfrage.

- Model id: `nano-banana-2`
- Made by: Google
- Category: Text to Image
- Output: image
- Price: from $0.06 / image (cheapest run $0.06 (60 API credits))
- Run: `POST https://api.doitong.com/v1/run/nano-banana-2`
- Quote: `POST https://api.doitong.com/v1/quote/nano-banana-2`
- Docs page: https://doitong.com/de/developers/models/nano-banana-2

## Pricing

Price: **from $0.06 / 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 `enable_web_search` = true and `thinking_level` = high: by `resolution`, 0.5K: $0.077, 1K: $0.097, 2K: $0.137, 4K: $0.177 / image
- When `enable_web_search` = true: by `resolution`, 0.5K: $0.075, 1K: $0.095, 2K: $0.135, 4K: $0.175 / image
- When `thinking_level` = high: by `resolution`, 0.5K: $0.062, 1K: $0.082, 2K: $0.122, 4K: $0.162 / image

The full example input below costs $0.08 = 80 API credits (1 image × 80 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-2` 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 | Textanweisungen zur Generierung eines Bildes. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 4 | Für die Generierung angeforderte Bildanzahl. |
| `seed` |  | integer \| null | no |  |  | Seed-Wert zur Initialisierung der Zufallszahlengenerierung. |
| `aspect_ratio` |  | enum (string) \| null | no | `auto` | `auto`, `21:9`, `16:9`, `3:2`, `4:3`, `5:4`, `1:1`, `4:5`, `3:4`, `2:3`, `9:16`, `4:1`, `1:4`, `8:1`, `1:8` | Lege das Seitenverhältnis des generierten Bildes explizit fest, einschließlich der extremen Optionen 4:1, 1:4, 8:1 und 1:8, oder wähle "auto" für eine promptbasierte Auswahl durch das Modell. |
| `output_format` |  | enum (string) | no | `png` | `jpeg`, `png`, `webp` | Dateiformat des resultierenden Bilds. |
| `safety_tolerance` |  | enum (string) | no | `4` | `1`, `2`, `3`, `4`, `5`, `6` | Stelle die Toleranz der Inhaltsmoderation zwischen der am wenigsten restriktiven Stufe 6 und der strengsten Stufe 1 ein, die den Großteil der Inhalte blockiert. |
| `system_prompt` |  | string | no | `` | ≤ 50000 characters | Optionale, anfrageweite Vorgaben für Persona und Ausgabestil, die Gemini als Systemanweisung oder OpenAI-kompatiblen Anbietern als Systemnachricht übermittelt werden. Bei leerem Wert wird für diese Anweisung nichts gesendet. |
| `resolution` |  | enum (string) | no | `1K` | `0.5K`, `1K`, `2K`, `4K` | Auflösung des Ausgabebilds. |
| `limit_generations` |  | boolean | no | `true` |  | Experimentelle Generierungsgrenze, die bei Aktivierung die Qualität beeinflussen kann. Mit `True` wird jede Prompt-Runde auf 1 Generierung beschränkt, Bildanzahlanweisungen im Prompt überschrieben und vom Modell erzeugte Zwischenbilder ignoriert. |
| `enable_web_search` |  | boolean | no | `false` |  | Umschalter für die Websuche bei der Bildgenerierung, sodass das Modell aktuelle Online-Informationen in das Bild einbeziehen kann. |
| `thinking_level` |  | enum (string) \| null | no |  | `minimal`, `high` | Wähle 'minimal' oder 'high', um das Denken des Modells auf dieser Stufe zu aktivieren und seine Gedanken in die Generierung einzubeziehen; bleibt die Stufe nicht gesetzt, ist das Denken deaktiviert. |

## Example input

Required parameters only:

```json
{
  "prompt": "A cozy bookshop window at night with a hand-painted sign reading \"Open Late\", warm light, rain on the glass"
}
```

A fuller example:

```json
{
  "prompt": "A cozy bookshop window at night with a hand-painted sign reading \"Open Late\", warm light, rain on the glass",
  "aspect_ratio": "4:5",
  "resolution": "1K"
}
```

## 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-2?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "A cozy bookshop window at night with a hand-painted sign reading \"Open Late\", warm light, rain on the glass",
    "aspect_ratio": "4:5",
    "resolution": "1K"
  }'

# 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-2?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "prompt": "A cozy bookshop window at night with a hand-painted sign reading \"Open Late\", warm light, rain on the glass",
    "aspect_ratio": "4:5",
    "resolution": "1K"
  }),
});
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 cozy bookshop window at night with a hand-painted sign reading \"Open Late\", warm light, rain on the glass",
    "aspect_ratio": "4:5",
    "resolution": "1K",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/nano-banana-2", 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-2",
      "input": {
        "prompt": "A cozy bookshop window at night with a hand-painted sign reading \"Open Late\", warm light, rain on the glass",
        "aspect_ratio": "4:5",
        "resolution": "1K"
      },
      "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-2",
  "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": 80,
    "usd": "0.08",
    "charged": 80,
    "refunded": 0
  },
  "input": {
    "prompt": "A cozy bookshop window at night with a hand-painted sign reading \"Open Late\", warm light, rain on the glass",
    "aspect_ratio": "4:5",
    "resolution": "1K"
  },
  "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} | Vom Modell erzeugte Bilder. |
| `description` | string | Beschreibung zu den generierten Bildern. |

## Related models

- [Nano Banana 2 Edit](https://doitong.com/developers/models/nano-banana-2/edit.md) (`nano-banana-2/edit`): from $0.06 / image
- [Nano Banana Pro](https://doitong.com/developers/models/nano-banana-pro.md) (`nano-banana-pro`): from $0.15 / 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-2
- 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-2
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/nano-banana-2