# Nano Banana Pro API

> Modèle d’image le plus puissant de Google, avec un lettrage fiable, des mises en page complexes et une sortie jusqu’à 4K.

Modèle d’image basé sur Gemini qui raisonne sur le prompt avant de dessiner ; les affiches, infographies, menus et photos de produits avec texte lisible sont donc bien plus souvent réussis qu’avec les seuls modèles de diffusion. Choisissez une sortie 1K, 2K ou 4K et n’importe quel format courant, et autorisez éventuellement une recherche web pour ancrer l’image dans des faits actuels. Jusqu’à quatre images par requête.

- 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/fr/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 | Instructions textuelles utilisées pour générer une image. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 4 | Nombre d'images demandé pour la génération. |
| `seed` |  | integer \| null | no |  |  | Valeur de graine qui initialise la génération de nombres aléatoires. |
| `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` | Rapport hauteur/largeur de l’image résultante. |
| `output_format` |  | enum (string) | no | `png` | `jpeg`, `png`, `webp` | Format de fichier de l'image obtenue. |
| `safety_tolerance` |  | enum (string) | no | `4` | `1`, `2`, `3`, `4`, `5`, `6` | Définissez la tolérance de modération du contenu entre le niveau le moins restrictif, 6, et le niveau le plus strict, 1, qui bloque la plupart des contenus. |
| `system_prompt` |  | string | no | `` | ≤ 50000 characters | Indications facultatives, valables pour toute la requête, sur la persona et le style de sortie, transmises à Gemini comme instruction système ou aux fournisseurs compatibles OpenAI comme message système. Rien n'est envoyé pour cette instruction si la valeur est vide. |
| `resolution` |  | enum (string) | no | `1K` | `1K`, `2K`, `4K` | Résolution de l'image de sortie. |
| `limit_generations` |  | boolean | no | `true` |  | Limite expérimentale de génération : l'activation de `True` remplace toute indication de nombre d'images dans le prompt et limite chaque cycle de prompting à 1 génération. |
| `enable_web_search` |  | boolean | no | `false` |  | Interrupteur de recherche Web pour la génération d'image, permettant au modèle d'intégrer à l'image des informations récentes trouvées en ligne. |

## 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 produites par le modèle. |
| `description` | string | Description accompagnant les images générées. |

## 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