# Wan v2.2 5B · Text to Video API

> Text-to-video con el modelo 5B: 580p o 720p, 16:9, 9:16 o 1:1 e interpolación de fotogramas opcional

Crea un clip de vídeo a partir de un `prompt` de texto. La duración se establece mediante `num_frames` (17 a 161) y `frames_per_second` (4 a 60), con `resolution` de 580p o 720p y relaciones de aspecto 16:9, 9:16 o 1:1. Se puede activar la interpolación de fotogramas con film o rife, y se pueden ajustar la calidad de salida y el modo de escritura del archivo. Esta es la variante con guía estándar y hasta 50 pasos de inferencia.

- Model id: `wan/v2.2-5b/text-to-video`
- Made by: Alibaba
- Category: Text to Video
- Output: video
- Price: $0.15 / video (cheapest run $0.15 (150 API credits))
- Run: `POST https://api.doitong.ru/v1/run/wan/v2.2-5b/text-to-video`
- Quote: `POST https://api.doitong.ru/v1/quote/wan/v2.2-5b/text-to-video`
- Docs page: https://doitong.com/es-ES/developers/models/wan/v2.2-5b/text-to-video

## Pricing

Price: **$0.15 / video**. Billed once per generated video.

The full example input below costs $0.15 = 150 API credits (1 video × 150 API credits).

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/v2.2-5b/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 | `24` | 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` | `580p`, `720p` | Resolución del vídeo de salida, 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 | `40` | 2 – 50 | 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. |
| `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. |
| `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 | `0` | 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/v2.2-5b/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/v2.2-5b/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/v2.2-5b/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/v2.2-5b/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/v2.2-5b/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": 150,
    "usd": "0.15",
    "charged": 150,
    "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 medium shot establishes a modern, minimalist office setting: clean lines, muted grey walls, and polished wood surfaces. The focus shifts to a close-up on a woman in sharp, navy blue business attire. Her crisp white blouse contrasts with the deep blue of her tailored suit jacket. The subtle texture of the fabric is visible—a fine weave with a slight sheen. Her expression is serious, yet engaging, as she speaks to someone unseen just beyond the frame. Close-up on her eyes, showing the intensity of her gaze and the fine lines around them that hint at experience and focus. Her lips are slightly parted, as if mid-sentence. The light catches the subtle highlights in her auburn hair, meticulously styled. Note the slight catch of light on the silver band of her watch. High resolution 4k",
    "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 5b · Text to Image](https://doitong.com/developers/models/wan/v2.2-5b/text-to-image.md) (`wan/v2.2-5b/text-to-image`): $0.016 / image
- [Wan · v2.2 5b · Text to Video · Distill](https://doitong.com/developers/models/wan/v2.2-5b/text-to-video/distill.md) (`wan/v2.2-5b/text-to-video/distill`): $0.08 / video
- [Wan v2.2 5B · Image to Video](https://doitong.com/developers/models/wan/v2.2-5b/image-to-video.md) (`wan/v2.2-5b/image-to-video`): $0.15 / 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
- [LTX 2.5 Pro Text to Video](https://doitong.com/developers/models/lightricks/ltx-2.5/text-to-video/pro.md) (`lightricks/ltx-2.5/text-to-video/pro`): from $0.12 / second

## Links

- HTML page: https://doitong.com/developers/models/wan/v2.2-5b/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/v2.2-5b/text-to-video
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/wan/v2.2-5b/text-to-video