# Nano Banana 2 API

> Modèle d’image Gemini rapide de Google, des brouillons 0.5K rapides à la 4K, avec des formats extrêmes et un ancrage web.

Une version sœur plus rapide et moins coûteuse de Nano Banana Pro, qui gère toujours bien le texte dans les images et les scènes à plusieurs objets. La sortie va des aperçus 0.5K à la 4K, avec des formats de 1:8 à 8:1 pour les bannières et les stories verticales. La recherche web facultative ancre l’image dans des faits actuels, et un niveau de réflexion élevé facultatif planifie les mises en page complexes avant le dessin. Jusqu’à quatre images par requête.

- 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/fr/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 | 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 | `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` | Choisissez explicitement le format d'image de l'image générée, y compris les options extrêmes 4:1, 1:4, 8:1 et 1:8, ou sélectionnez "auto" pour un choix fondé sur le prompt par le modèle. |
| `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` | `0.5K`, `1K`, `2K`, `4K` | Résolution de l'image de sortie. |
| `limit_generations` |  | boolean | no | `true` |  | Limite expérimentale de génération pouvant affecter la qualité lorsqu'elle est activée. Avec `True`, chaque cycle de prompting est limité à 1 génération, les instructions de nombre d'images dans le prompt sont remplacées et les images intermédiaires générées par le modèle sont ignorées. |
| `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. |
| `thinking_level` |  | enum (string) \| null | no |  | `minimal`, `high` | Sélectionnez 'minimal' ou 'high' pour activer la réflexion du modèle à ce niveau et inclure ses réflexions dans la génération ; laisser le niveau non défini désactive la réflexion. |

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

## 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