# FLUX.3 Klein API

> Tekstas į vaizdą su savąja 4K raiška, pasirenkamu išdėstymo valdymu pagal aprėpties stačiakampius ir iki 4 vaizdų vienoje užklausoje

Generuoja vaizdus iš išsamaus tekstinio `prompt`. Kiekviena `image_size` kraštinė gali būti nuo 256 iki 4096 pikselių, o per vieną iškvietimą galima užklausti 1–4 vaizdų. Iki 32 `bounding_boxes` leidžia nustatytose kadro vietose išdėstyti įvardytus objektus. Išvestis gali būti png, jpeg arba webp, o raginio išplėtimą galima įjungti arba išjungti.

- 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/lt/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 |  |  | Išsamios vaizdo generavimo instrukcijos, aprašančios objektą, kadravimą, apšvietimą ir foną, atitinkančios išsamias antraštes, naudotas modeliui mokyti. |
| `enable_prompt_expansion` |  | boolean | no | `true` |  | Raginio išplėtimas į išsamią antraštę prieš generavimą, įjungiamas, kai reikšmė true. Redaguojant antraštė grindžiama nuorodiniais vaizdais. |
| `seed` |  | integer \| null | no |  |  | Atkuriamų vaizdų pradinė reikšmė: nepakitęs raginys ir pradinė reikšmė sukuria tokį patį vaizdą, jei modelio versija nepasikeitė. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 4 | Generavimui prašomas vaizdų skaičius. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Saugos tikrintuvo aktyvinimas; true įjungia tikrinimą. |
| `output_format` |  | enum (string) | no | `png` | `jpeg`, `png`, `webp` | Galutinio vaizdo failo formatas. |
| `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` | Atskirai nustatykite išvesties plotį ir aukštį nuo 256 iki 4096 pikselių, palaikydami savąjį 4K generavimą. |
| `bounding_boxes` |  | array of object {label, description, box} \| null | no |  | ≤ 32 items | Pasirenkamas langelių išdėstymas, apribojantis kiekvieną aprašytą objektą jo langeliu; langelius nurodykite raginio etiketėmis, pavyzdžiui, `A red fox <fox> sits under a red umbrella <umbrella>`. Koordinatės išreiškia langelio kraštines kaip vaizdo matmenų dalis, matuojamas nuo viršutinio kairiojo pradžios taško (0, 0). |
| `bounding_boxes[].label` |  | string \| null | no |  | ≤ 64 characters | Trumpa langelio objekto etiketė, pavyzdžiui, `fox`; numatytoji reikšmė yra `obj_<n>`. Įtraukite `<fox>` į raginį, kad jo žodžiai būtų susieti su langeliu; raginyje nepaminėti langeliai įtraukiami į sceną. |
| `bounding_boxes[].description` |  | string | yes |  | ≤ 500 characters | Langelyje atvaizduojamas objektas, įskaitant jo išvaizdą. |
| `bounding_boxes[].box` |  | object {x_min, y_min, x_max, y_max} | yes |  |  | Objekto vieta išvesties vaizde. |
| `bounding_boxes[].box.x_min` |  | number | yes |  | 0 – 1 | Kairioji riba, išreikšta vaizdo pločio dalimi nuo 0 iki 1. |
| `bounding_boxes[].box.y_min` |  | number | yes |  | 0 – 1 | Viršutinė riba, išreikšta vaizdo aukščio dalimi nuo 0 iki 1. |
| `bounding_boxes[].box.x_max` |  | number | yes |  | 0 – 1 | Dešinioji riba, išreikšta vaizdo pločio dalimi nuo 0 iki 1. |
| `bounding_boxes[].box.y_max` |  | number | yes |  | 0 – 1 | Apatinė riba, išreikšta vaizdo aukščio dalimi nuo 0 iki 1. |

## 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} | Modelio sukurti vaizdai. |
| `timings` | object | Generavimo proceso laiko informacija. |
| `seed` | integer | Pirmo vaizdo generavimo pradinė reikšmė. |
| `has_nsfw_concepts` | array of boolean | Nurodo, ar sugeneruotuose vaizduose yra NSFW sąvokų. |
| `prompt` | string | Vaizdo generavimo metu naudojamas raginys. |

## 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