# FLUX.2 [pro] API

> 세밀한 조정 기능 없이 완성도 높은 사실적 결과에 맞춰 조정된 Black Forest Labs의 상용 FLUX.2 모델

FLUX.2의 관리형 프로 등급입니다. 조정할 스텝 수나 가이던스 없이 프롬프트와 크기만 사용하며, 상업 사진, 제품 촬영 및 캠페인 비주얼에 맞춘 출력을 제공합니다. 프리셋 또는 사용자 지정 크기로 요청당 이미지 1개를 생성하고 JPEG 또는 PNG를 출력합니다. 시드를 사용하면 결과를 반복할 수 있습니다.

- Model id: `flux-2-pro`
- Made by: Black Forest Labs
- Category: Text to Image
- Output: image
- Price per megapixel of your output image: $0.015 / megapixel of output image (cheapest run $0.015 (15 API credits))
- Run: `POST https://api.doitong.com/v1/run/flux-2-pro`
- Quote: `POST https://api.doitong.com/v1/quote/flux-2-pro`
- Docs page: https://doitong.com/ko/developers/models/flux-2-pro

## Pricing

Price: **$0.015 / megapixel of output image**. Price per megapixel of your output image: the input files are measured before the run (length, resolution, frame rate). The quote measures the same files and is exactly what the run charges.

The full example input below costs $0.03 = 30 API credits (1 MP output image × $0.015 + $0.015).

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/flux-2-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

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `prompt` |  | string | yes |  |  | 이미지 생성을 안내하는 프롬프트입니다. |
| `image_size` |  | object {width, height} \| enum (string) | no | `landscape_4_3` | `square_hd`, `square`, `portrait_4_3`, `portrait_16_9`, `landscape_4_3`, `landscape_16_9` | 생성된 이미지의 치수입니다. |
| `seed` |  | integer \| null | no |  |  | 생성용 시드 값입니다. |
| `safety_tolerance` |  | enum (string) | no | `2` | `1`, `2`, `3`, `4`, `5` | 생성 이미지 안전 설정입니다. 허용 수준은 5에서 가장 관대하고 1에서 가장 엄격합니다. |
| `output_format` |  | enum (string) | no | `jpeg` | `jpeg`, `png` | 결과 이미지의 파일 형식입니다. |

## Example input

Required parameters only:

```json
{
  "prompt": "Studio product photo of a ceramic coffee cup on a linen napkin, morning window light, soft shadows"
}
```

A fuller example:

```json
{
  "prompt": "Studio product photo of a ceramic coffee cup on a linen napkin, morning window light, soft shadows",
  "image_size": "square_hd"
}
```

## 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/flux-2-pro?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "Studio product photo of a ceramic coffee cup on a linen napkin, morning window light, soft shadows",
    "image_size": "square_hd"
  }'

# 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/flux-2-pro?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "prompt": "Studio product photo of a ceramic coffee cup on a linen napkin, morning window light, soft shadows",
    "image_size": "square_hd"
  }),
});
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": "Studio product photo of a ceramic coffee cup on a linen napkin, morning window light, soft shadows",
    "image_size": "square_hd",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/flux-2-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": "flux-2-pro",
      "input": {
        "prompt": "Studio product photo of a ceramic coffee cup on a linen napkin, morning window light, soft shadows",
        "image_size": "square_hd"
      },
      "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": "flux-2-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": 30,
    "usd": "0.03",
    "charged": 30,
    "refunded": 0
  },
  "input": {
    "prompt": "Studio product photo of a ceramic coffee cup on a linen napkin, morning window light, soft shadows",
    "image_size": "square_hd"
  },
  "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
      }
    ],
    "seed": 42
  },
  "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} | 모델이 생성한 이미지입니다. |
| `seed` | integer | 생성 중 사용된 시드 값입니다. |

## Related models

- [FLUX 2 Flash](https://doitong.com/developers/models/flux-2/flash.md) (`flux-2/flash`): $0.005 / megapixel
- [FLUX 2 Lora](https://doitong.com/developers/models/flux-2/lora.md) (`flux-2/lora`): $0.021 / megapixel
- [FLUX 2 Turbo](https://doitong.com/developers/models/flux-2/turbo.md) (`flux-2/turbo`): $0.008 / megapixel
- [FLUX.2 \[dev\]](https://doitong.com/developers/models/flux-2.md) (`flux-2`): $0.012 / megapixel
- [FLUX 2 Edit](https://doitong.com/developers/models/flux-2/edit.md) (`flux-2/edit`): $0.012 / megapixel
- [FLUX 2 Flash Edit](https://doitong.com/developers/models/flux-2/flash/edit.md) (`flux-2/flash/edit`): $0.005 / megapixel
- [FLUX 2 Lora Edit](https://doitong.com/developers/models/flux-2/lora/edit.md) (`flux-2/lora/edit`): $0.021 / megapixel
- [FLUX 2 Pro Edit](https://doitong.com/developers/models/flux-2-pro/edit.md) (`flux-2-pro/edit`): $0.105 / run

## Links

- HTML page: https://doitong.com/developers/models/flux-2-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=flux-2-pro
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/flux-2-pro