# FLUX.3 Klein API

> ネイティブ4Kサイズのテキスト画像生成。オプションのバウンディングボックスによるレイアウト制御と、リクエストあたり最大4枚に対応します

詳細なテキスト`prompt`から画像を生成します。`image_size`の各辺は256～4096ピクセルで、1回の呼び出しで1～4枚を指定できます。最大32個の`bounding_boxes`で、名前付きオブジェクトをフレーム内の指定位置に配置できます。出力はpng、jpeg、webpに対応し、プロンプト拡張はオンまたはオフにできます。

- Model id: `blackforestlabs/flux-3/klein/text-to-image`
- Made by: Black Forest Labs
- Category: Text to Image
- Output: image
- Price per run: from $0.008 / run of output image (cheapest run $0.008 (8 API credits))
- Run: `POST https://api.doitong.ru/v1/run/blackforestlabs/flux-3/klein/text-to-image`
- Quote: `POST https://api.doitong.ru/v1/quote/blackforestlabs/flux-3/klein/text-to-image`
- Docs page: https://doitong.com/ja/developers/models/blackforestlabs/flux-3/klein/text-to-image

## Pricing

Price: **from $0.008 / run of output image** (the lowest tier; the quote prices your exact input). Price per run: 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 $0.009 = 9 API credits (1 run × $0.009).

Prices are the upstream price in USD, paid from the API balance in API credits (1000 API credits = 1 USD). `POST https://api.doitong.ru/v1/quote/blackforestlabs/flux-3/klein/text-to-image` 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 |  |  | 被写体、構図、照明、背景を詳細に説明する画像生成指示。モデルの学習に使用された詳細なキャプションに合わせます。 |
| `enable_prompt_expansion` |  | boolean | no | `true` |  | 生成前にプロンプトを詳細なキャプションへ拡張します。trueの場合に有効です。編集ではキャプションの内容を参照画像に基づけます。 |
| `seed` |  | integer \| null | no |  |  | 再現可能な画像のシード。モデルのバージョンが同じであれば、同一のプロンプトとシードで同一の画像が生成されます。 |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 4 | 生成する画像の枚数。 |
| `enable_safety_checker` |  | boolean | no | `true` |  | 安全性チェッカーの有効化。true でチェックを有効にします。 |
| `output_format` |  | enum (string) | no | `png` | `jpeg`, `png`, `webp` | 結果の画像のファイル形式。 |
| `image_size` |  | object {width, height} \| enum (string) | no | `square_hd` | `square_hd`, `square`, `portrait_4_3`, `portrait_16_9`, `landscape_4_3`, `landscape_16_9` | 出力の幅と高さを256～4096ピクセルの範囲で個別に設定します。ネイティブ4K生成に対応します。 |
| `bounding_boxes` |  | array of object {label, description, box} \| null | no |  | ≤ 32 items | 説明した各オブジェクトを割り当てたボックス内に収めるオプションのボックスレイアウト。プロンプトラベルでボックスを識別します（例：`A red fox <fox> sits under a red umbrella <umbrella>`）。座標は左上の原点(0, 0)から測定した、画像寸法に対するボックス辺の割合です。 |
| `bounding_boxes[].label` |  | string \| null | no |  | ≤ 64 characters | ボックスの簡潔なオブジェクトラベル（例：`fox`）。デフォルトは`obj_<n>`です。ボックスに関連付ける語をプロンプトに`<fox>`として含めます。プロンプトに記載されていないボックスはシーンに追加されます。 |
| `bounding_boxes[].description` |  | string | yes |  | ≤ 500 characters | ボックス内に描画するオブジェクトと、その外観。 |
| `bounding_boxes[].box` |  | object {x_min, y_min, x_max, y_max} | yes |  |  | 出力画像内のオブジェクト配置。 |
| `bounding_boxes[].box.x_min` |  | number | yes |  | 0 – 1 | 画像幅を基準にした左端の位置。0～1です。 |
| `bounding_boxes[].box.y_min` |  | number | yes |  | 0 – 1 | 画像高さを基準にした上端の位置。0～1です。 |
| `bounding_boxes[].box.x_max` |  | number | yes |  | 0 – 1 | 画像幅を基準にした右端の位置。0～1です。 |
| `bounding_boxes[].box.y_max` |  | number | yes |  | 0 – 1 | 画像高さを基準にした下端の位置。0～1です。 |

## Example input

Required parameters only:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

A fuller example:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

## 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.ru/v1/run/blackforestlabs/flux-3/klein/text-to-image?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  }'

# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY"
```

### JavaScript

```javascript
const API = "https://api.doitong.ru/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/blackforestlabs/flux-3/klein/text-to-image?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  }),
});
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.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}

payload = {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/blackforestlabs/flux-3/klein/text-to-image", 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.ru/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": "blackforestlabs/flux-3/klein/text-to-image",
      "input": {
        "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
      },
      "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": "blackforestlabs/flux-3/klein/text-to-image",
  "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": 9,
    "usd": "0.009",
    "charged": 9,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  },
  "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
      }
    ],
    "timings": {},
    "seed": 42,
    "has_nsfw_concepts": [
      false
    ],
    "prompt": "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.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `images` | array of object {url, content_type, file_name, file_size, width, height} | モデルが生成した画像。 |
| `timings` | object | 生成処理のタイミング情報。 |
| `seed` | integer | 最初の画像の生成シード。 |
| `has_nsfw_concepts` | array of boolean | 生成画像に NSFW 概念が含まれるかどうかを示します。 |
| `prompt` | string | 画像生成時に使用するプロンプト。 |

## Related models

- [FLUX.3 Klein Image Editing](https://doitong.com/developers/models/blackforestlabs/flux-3/klein/edit-image.md) (`blackforestlabs/flux-3/klein/edit-image`): from $0.008 / run of output 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
- [Nano Banana 2](https://doitong.com/developers/models/nano-banana-2.md) (`nano-banana-2`): from $0.06 / image

## Links

- HTML page: https://doitong.com/developers/models/blackforestlabs/flux-3/klein/text-to-image
- 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=blackforestlabs/flux-3/klein/text-to-image
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/blackforestlabs/flux-3/klein/text-to-image