# FLUX.3 Klein API

> Yerel 4K boyutları, isteğe bağlı sınırlayıcı kutu düzen kontrolü ve istek başına en fazla 4 görselle metinden görsele oluşturma

Ayrıntılı bir metin `prompt`undan görseller üretir. `image_size`ın her kenarı 256-4096 piksel arasında olabilir ve çağrı başına 1-4 görsel istenebilir. En fazla 32 `bounding_boxes`, adlandırılmış nesneleri karede belirli konumlara yerleştirmenizi sağlar. Çıktı png, jpeg veya webp olabilir; istem genişletme açılıp kapatılabilir.

- 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/tr/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 |  |  | Konuyu, kadrajı, aydınlatmayı ve arka planı ayrıntılı olarak açıklayan, modeli eğitmek için kullanılan ayrıntılı açıklamalarla eşleşen görsel üretim talimatları. |
| `enable_prompt_expansion` |  | boolean | no | `true` |  | Üretim öncesinde istemin ayrıntılı açıklamaya genişletilmesi; true olduğunda etkinleştirilir. Düzenlemede açıklama, referans görsellerine dayandırılır. |
| `seed` |  | integer \| null | no |  |  | Tekrarlanabilir görseller için seed: model sürümü değişmediğinde aynı istem ve seed, aynı görseli üretir. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 4 | Üretim için istenen görsel sayısı. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Güvenlik denetleyicisi etkinleştirme; true denetimi etkinleştirir. |
| `output_format` |  | enum (string) | no | `png` | `jpeg`, `png`, `webp` | Ortaya çıkan görselin dosya biçimi. |
| `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` | 256–4096 piksel aralığında çıktı genişliğini ve yüksekliğini bağımsız olarak ayarlayın; yerel 4K üretimini destekler. |
| `bounding_boxes` |  | array of object {label, description, box} \| null | no |  | ≤ 32 items | Açıklanan her nesneyi kendisine atanmış kutuyla sınırlayan isteğe bağlı kutulu yerleşim; kutuları istem etiketleriyle tanımlayın, ör. `A red fox <fox> sits under a red umbrella <umbrella>`. Koordinatlar, (0, 0) sol üst başlangıç noktasından ölçülen görsel boyutlarının kesirleri olarak kutu kenarlarını ifade eder. |
| `bounding_boxes[].label` |  | string \| null | no |  | ≤ 64 characters | Kutu için kısa nesne etiketi; örneğin `fox`; varsayılan `obj_<n>` değeridir. Sözcüklerini kutuyla ilişkilendirmek için isteme `<fox>` ekleyin; istemde belirtilmeyen kutular sahneye eklenir. |
| `bounding_boxes[].description` |  | string | yes |  | ≤ 500 characters | Görünümü de dahil olmak üzere kutu içinde oluşturulacak nesne. |
| `bounding_boxes[].box` |  | object {x_min, y_min, x_max, y_max} | yes |  |  | Çıktı görseli içindeki nesne yerleşimi. |
| `bounding_boxes[].box.x_min` |  | number | yes |  | 0 – 1 | Görsel genişliğine göre 0 ile 1 arasında ifade edilen sol sınır. |
| `bounding_boxes[].box.y_min` |  | number | yes |  | 0 – 1 | Görsel yüksekliğine göre 0 ile 1 arasında ifade edilen üst sınır. |
| `bounding_boxes[].box.x_max` |  | number | yes |  | 0 – 1 | Görsel genişliğine göre 0 ile 1 arasında ifade edilen sağ sınır. |
| `bounding_boxes[].box.y_max` |  | number | yes |  | 0 – 1 | Görsel yüksekliğine göre 0 ile 1 arasında ifade edilen alt sınır. |

## 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} | Model tarafından oluşturulan görseller. |
| `timings` | object | Üretim sürecinin zamanlama bilgileri. |
| `seed` | integer | İlk görsel için üretim seed'i. |
| `has_nsfw_concepts` | array of boolean | Üretilen görsellerde NSFW kavramlarının bulunup bulunmadığını belirtir. |
| `prompt` | string | Görsel üretimi sırasında kullanılan istem. |

## 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