# Nano Banana 2 API

> Spartus Google Gemini vaizdų modelis – nuo greitų 0.5K juodraščių iki 4K, su itin įvairiais kraštinių santykiais ir žiniatinklio kontekstu.

Spartesnis ir pigesnis Nano Banana Pro variantas, taip pat gerai apdorojantis tekstą vaizduose ir scenas su keliais objektais. Išvestis gali būti nuo 0.5K peržiūrų iki 4K, o kraštinių santykiai – nuo 1:8 iki 8:1, skirti reklamjuostėms ir vertikalioms istorijoms. Pasirenkama žiniatinklio paieška susieja vaizdą su dabartiniais faktais, o pasirenkamas aukštas mąstymo lygis prieš piešdamas suplanuoja sudėtingus maketus. Vienoje užklausoje galima gauti iki keturių vaizdų.

- 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/lt/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 | Vaizdui generuoti naudojamos tekstinės instrukcijos. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 4 | Generavimui prašomas vaizdų skaičius. |
| `seed` |  | integer \| null | no |  |  | Atsitiktinių skaičių generavimą inicijuojanti pradinis reikšmė. |
| `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` | Aiškiai pasirinkite generuojamo vaizdo kraštinių santykį, įskaitant kraštutines parinktis 4:1, 1:4, 8:1, 1:8, arba pasirinkite "auto", kad modelis jį parinktų pagal raginį. |
| `output_format` |  | enum (string) | no | `png` | `jpeg`, `png`, `webp` | Galutinio vaizdo failo formatas. |
| `safety_tolerance` |  | enum (string) | no | `4` | `1`, `2`, `3`, `4`, `5`, `6` | Nustatykite turinio moderavimo toleranciją nuo mažiausiai ribojančio lygio 6 iki griežčiausio lygio 1, kuris blokuoja didžiąją dalį turinio. |
| `system_prompt` |  | string | no | `` | ≤ 50000 characters | Pasirinktinis visai užklausai taikomas personos ir išvesties stiliaus nurodymas, perduodamas Gemini kaip sistemos instrukcija arba OpenAI suderinamiems teikėjams kaip sistemos pranešimas. Jei reikšmė tuščia, ši instrukcija nesiunčiama. |
| `resolution` |  | enum (string) | no | `1K` | `0.5K`, `1K`, `2K`, `4K` | Išvesties vaizdo raiška. |
| `limit_generations` |  | boolean | no | `true` |  | Eksperimentinė generavimo riba, kuri įjungta gali paveikti kokybę. Naudojant `True`, kiekvienas raginimo etapas apribojamas iki 1 generavimo, nepaisomi raginio vaizdų skaičiaus nurodymai ir ignoruojami modelio sugeneruoti tarpiniai vaizdai. |
| `enable_web_search` |  | boolean | no | `false` |  | Interneto paieškos jungiklis vaizdams generuoti, leidžiantis modeliui į vaizdą įtraukti internete rastą naujausią informaciją. |
| `thinking_level` |  | enum (string) \| null | no |  | `minimal`, `high` | Pasirinkite 'minimal' arba 'high', kad suaktyvintumėte tokio lygio modelio mąstymą ir įtrauktumėte jo mintis į generavimą; nepasirinkus lygio mąstymas lieka išjungtas. |

## 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} | Modelio sukurti vaizdai. |
| `description` | string | Generuojamus vaizdus lydintis aprašas. |

## 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