# Wan v2.2 5B · Text to Video API

> Text-to-video cun il model 5B: 580p u 720p, 16:9, 9:16 u 1:1, interpolaziun da frames opzionala

Createscha in clip video a partir d’in `prompt` textual. La lunghezza vegn definida da `num_frames` (17 a 161) e `frames_per_second` (4 a 60), cun `resolution` da 580p u 720p ed aspect ratios 16:9, 9:16 u 1:1. L’interpolaziun da frames cun film u rife po vegnir activada; la qualitad d’output ed il modus da scriver la datoteca èn adattabels. Questa è la varianta cun guidance standard e fin a 50 pass d’inferenza.

- 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/rm/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 |  |  | Instrucziuns textualas che guidan la generaziun video. |
| `negative_prompt` |  | string | no | `` |  | Prompt negativ applitgà durant la generaziun d'in video. |
| `num_frames` |  | integer | no | `81` | 17 – 161 | Dumber da frames per la generaziun, cun in interval inclusiv da 17–161. |
| `frames_per_second` |  | integer \| null | no | `24` | 4 – 60 | Frequentaziun da frames dal video generà, cun valurs da 4 fin 60; definir `adjust_fps_for_interpolation` a false mantegna questa frequentaziun senza midada. Cun interpolaziun activa e `adjust_fps_for_interpolation` true (ses standard), multiplitgar questa frequentaziun per in plus il dumber da frames interpolads per obtegnair la FPS finala. Per exempel, 16 FPS cun 1 frame interpolà daventan 32 FPS. |
| `seed` |  | integer \| null | no |  |  | Seed che renda la generaziun reproducibla. Cun definir None vegn tschernì in seed casualmain. |
| `resolution` |  | enum (string) | no | `720p` | `580p`, `720p` | Resoluziun dal video d'output, 580p u 720p. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `16:9`, `9:16`, `1:1` | Proporziun dal video d'output, u 16:9 u 9:16. |
| `num_inference_steps` |  | integer | no | `40` | 2 – 50 | Dumber da pass da sampling, barattà temp d'elavuraziun pli lung per meglra qualitad cun l'augment dal dumber. |
| `enable_safety_checker` |  | boolean | no | `false` |  | Controlla da segirezza da l'input avant l'elavuraziun, che mo contos autorisads pon deactivar. Dumondas senza autorisaziun vegnan adina controlladas; uschiglio activa true la controlla. |
| `enable_output_safety_checker` |  | boolean | no | `false` |  | Controlla la segirezza dal video generà; true activa ina controlla suenter la generaziun. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | Permetta ad in large language model d'enritgir il prompt cun detagls. Questa expansiun mantegna il senn dal prompt. |
| `guidance_scale` |  | number | no | `3.5` | 1 – 10 | Furza da la guida senza classifitgat, barattà ina pussaivla perdita da qualitad per ina concordanza pli stretga cun il prompt a mesira che la scala crescha. |
| `shift` |  | number | no | `5` | 1 – 10 | Configuraziun dal shift dal video, cun in interval permess da 1.0–10.0. |
| `interpolator_model` |  | enum (string) | no | `film` | `none`, `film`, `rife` | Configuraziun da l'interpolaziun da frames: tscherner None per sursiglir l'interpolaziun u inditgar il model che duai far ella. |
| `num_interpolated_frames` |  | integer | no | `0` | 0 – 4 | Inserir 0–4 frames interpolads en mintga largia tranter dus frames generads. |
| `adjust_fps_for_interpolation` |  | boolean | no | `true` |  | Commutader per l'adattaziun da la frequenza da frames: false mantegna la FPS furnida, entant che true la multiplitgescha per in plus il dumber da frames interpolads. Uschia daventan 16 FPS 32 FPS cura ch'in frame vegn interpolà e l'adattaziun è activa. |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | Configuraziun da la qualitad dal video d'output, che baratta datotecas pli grondas per visuals meglers cura che la valur crescha. |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | Modus da scriver video, cun balanced sco cumpromiss tranter sveltezza e qualitad. Tscherner small per las datotecas las pli pitschnas e la scrittira la pli plauna; ina scrittira pli svelta returna ils resultats pli baud, ma creescha datotecas pli grondas. |

## 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} | Datoteca video producida da la generaziun. |
| `prompt` | string | Prompt da text utilisà per generar il video. |
| `seed` | integer | Valur da seed applitgada durant la generaziun. |

## 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