# Wan-2.2 Text-to-Video A14B API

> Text-to-video A14B con salida de 480p a 720p, dos etapas de guía e interpolación opcional

Genera un vídeo a partir de un `prompt` de texto. `num_frames` va de 17 a 161, `frames_per_second` de 4 a 60 y `resolution` es 480p, 580p o 720p en 16:9, 9:16 o 1:1. Están disponibles dos valores de guía, un ajuste de `acceleration` e interpolación film o rife (un fotograma interpolado de forma predeterminada).

- Model id: `wan/v2.2-a14b/text-to-video`
- Made by: Alibaba
- Category: Text to Video
- Output: video
- Price per second of your output video: from $0.04 / second of output video (cheapest run $0.04 (40 API credits))
- Run: `POST https://api.doitong.ru/v1/run/wan/v2.2-a14b/text-to-video`
- Quote: `POST https://api.doitong.ru/v1/quote/wan/v2.2-a14b/text-to-video`
- Docs page: https://doitong.com/es-ES/developers/models/wan/v2.2-a14b/text-to-video

## Pricing

Price: **from $0.04 / second of output video** (the lowest tier; the quote prices your exact input). Price per second of your output video: 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.

Price by tier:

- 480p: $0.04 / second of output video
- 580p: $0.06 / second of output video
- 720p: $0.08 / second of output video

The full example input below costs $0.405 = 405 API credits (5.0625 s output video × $0.08 (720p)).

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/wan/v2.2-a14b/text-to-video` 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 |  |  | Instrucciones de texto que guían la generación de vídeo. |
| `negative_prompt` |  | string | no | `` |  | Prompt negativo aplicado al generar un vídeo. |
| `num_frames` |  | integer | no | `81` | 17 – 161 | Número de fotogramas de la generación, con un intervalo inclusivo de 17–161. |
| `frames_per_second` |  | integer \| null | no | `16` | 4 – 60 | Frecuencia de fotogramas del vídeo generado, que acepta valores de 4 a 60; establecer `adjust_fps_for_interpolation` en false conserva esta frecuencia sin cambios. Con la interpolación activa y `adjust_fps_for_interpolation` en true (su valor predeterminado), multiplica esta frecuencia por uno más el número de fotogramas interpolados para obtener los FPS finales. Por ejemplo, 16 FPS con 1 fotograma interpolado se convierten en 32 FPS. |
| `seed` |  | integer \| null | no |  |  | Semilla que hace reproducible la generación. Establecerla en None selecciona una semilla aleatoriamente. |
| `resolution` |  | enum (string) | no | `720p` | `480p`, `580p`, `720p` | Resolución del vídeo de salida: 480p, 580p o 720p. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `16:9`, `9:16`, `1:1` | Relación de aspecto del vídeo de salida, 16:9 o 9:16. |
| `num_inference_steps` |  | integer | no | `27` | 2 – 40 | Número de pasos de muestreo, que intercambia un mayor tiempo de procesamiento por una mejor calidad a medida que aumenta el número. |
| `enable_safety_checker` |  | boolean | no | `false` |  | Comprobación de seguridad de la entrada antes del procesamiento, que solo pueden desactivar las cuentas autorizadas. Las solicitudes sin autorización siempre se comprueban; de lo contrario, true habilita la comprobación. |
| `enable_output_safety_checker` |  | boolean | no | `false` |  | Controla la comprobación de seguridad del vídeo generado; establecerlo en true habilita una comprobación después de la generación. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | Permite que un modelo de lenguaje grande enriquezca el prompt con detalles. Activar esta expansión no cambia el significado del prompt. |
| `acceleration` |  | enum (string) | no | `regular` | `none`, `regular` | Configuración de aceleración, con 'regular' como opción recomendada. Aumentar la aceleración reduce la calidad para acortar el tiempo de generación. |
| `guidance_scale` |  | number | no | `3.5` | 1 – 10 | Intensidad de guía sin clasificador, que intercambia una posible pérdida de calidad por una coincidencia más precisa con el prompt a medida que aumenta la escala. |
| `guidance_scale_2` |  | number | no | `4` | 1 – 10 | Escala de orientación que controla hasta qué punto el modelo sigue el prompt durante su segunda fase. |
| `shift` |  | number | no | `5` | 1 – 10 | Configuración de desplazamiento del vídeo, con un intervalo permitido de 1.0–10.0. |
| `interpolator_model` |  | enum (string) | no | `film` | `none`, `film`, `rife` | Configuración de interpolación de fotogramas: elige None para omitir la interpolación o especifica el modelo que la realizará. |
| `num_interpolated_frames` |  | integer | no | `1` | 0 – 4 | Inserta 0–4 fotogramas interpolados en cada espacio entre dos fotogramas generados. |
| `adjust_fps_for_interpolation` |  | boolean | no | `true` |  | Interruptor de ajuste de la frecuencia de fotogramas: false conserva los FPS proporcionados, mientras que true los escala por uno más el número de fotogramas interpolados. Por tanto, 16 FPS se convierten en 32 FPS cuando se interpola 1 fotograma y el ajuste está habilitado. |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | Configuración de calidad del vídeo de salida, que intercambia archivos más grandes por una mejor calidad visual a medida que aumenta el valor. |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | Modo de escritura del vídeo, donde balanced ofrece un compromiso entre velocidad y calidad. Elige small para obtener los archivos más pequeños y la escritura más lenta; una escritura más rápida devuelve los resultados antes, pero crea archivos más grandes. |

## 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/wan/v2.2-a14b/text-to-video?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/wan/v2.2-a14b/text-to-video?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/wan/v2.2-a14b/text-to-video", 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": "wan/v2.2-a14b/text-to-video",
      "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": "wan/v2.2-a14b/text-to-video",
  "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": 405,
    "usd": "0.405",
    "charged": 405,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  },
  "output": {
    "video": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
      "content_type": "video/mp4",
      "file_name": "0-output.mp4",
      "file_size": 1843200
    },
    "prompt": "A close-up of a young woman smiling gently in the rain, raindrops glistening on her face and eyelashes. The video captures the delicate details of her expression and the water droplets, with soft light reflecting off her skin in the rainy atmosphere.",
    "seed": 42
  },
  "outputs": [
    {
      "type": "video",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
      "content_type": "video/mp4",
      "file_size": 1843200,
      "width": 1280,
      "height": 720,
      "duration": 5,
      "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 |
|---|---|---|
| `video` | object {url, content_type, file_name, file_size} | Archivo de vídeo producido por la generación. |
| `prompt` | string | Prompt de texto utilizado para generar el vídeo. |
| `seed` | integer | Valor de semilla aplicado durante la generación. |

## Related models

- [Wan · v2.2 A14b · Text to Image](https://doitong.com/developers/models/wan/v2.2-a14b/text-to-image.md) (`wan/v2.2-a14b/text-to-image`): $0.025 / image
- [Wan v2.2 A14B](https://doitong.com/developers/models/wan/v2.2-a14b/image-to-video.md) (`wan/v2.2-a14b/image-to-video`): from $0.04 / second of output video
- [Wan · v2.2 A14b · Video to Video](https://doitong.com/developers/models/wan/v2.2-a14b/video-to-video.md) (`wan/v2.2-a14b/video-to-video`): from $0.04 / second of output video
- [Wan-2.2 Speech-to-Video 14B](https://doitong.com/developers/models/wan/v2.2-14b/speech-to-video.md) (`wan/v2.2-14b/speech-to-video`): from $0.10 / second of output video
- [Wan 3.0 Text to Video](https://doitong.com/developers/models/alibaba/wan-3.0/text-to-video.md) (`alibaba/wan-3.0/text-to-video`): from $0.05 / second
- [FLUX 3 Max Text to Video](https://doitong.com/developers/models/blackforestlabs/flux-3-max/text-to-video.md) (`blackforestlabs/flux-3-max/text-to-video`): from $0.0425 / second of output video
- [Grok Imagine Video 1.5 Text to Video](https://doitong.com/developers/models/xai/grok-imagine-video/v1.5/text-to-video.md) (`xai/grok-imagine-video/v1.5/text-to-video`): from $0.08 / second
- [Kling 3.0 Pro Text to Video](https://doitong.com/developers/models/kling-video/v3/pro/text-to-video.md) (`kling-video/v3/pro/text-to-video`): from $0.112 / second

## Links

- HTML page: https://doitong.com/developers/models/wan/v2.2-a14b/text-to-video
- 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=wan/v2.2-a14b/text-to-video
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/wan/v2.2-a14b/text-to-video