# Wan v2.2 5B · Text to Video API

> 5B ᠵᠠᠯᠠᠨ ᡳ ᠥᠯᡝᠨ ᡥᡝᠯᡝᠨ ᠸᡳᡩᡝᠣ: 580p ᠣᠴᡳ 720p, 16:9, 9:16 ᠣᠴᡳ 1:1, ᠵᠠᠯᠠᠨ ᠩᡝᠰᡝᠮᡝ ᠠᠮᠠᠰᡳ

ᡳᠯᡤᠠᠨ `prompt`-ᡳ ᡩᡝᠯᡤᡳ ᠪᡳᡩᡝᠣ ᠨᡳᠶᠠᠯᠮᠠ ᠪᡳᡥᡝᠨ ᡩᡝᠯᡤᡳ ᡥᡡᠯᠠᠮᠪᡳ。 ᡠᠯᠠᠩᡤᠠ ᠵᡝᡵᡤᡳ `num_frames`-ᡳ ᠵᠠᠯᠠᠨ 17 ᡩᠣᠯᠣ 161 ᠪᡳᠴᡳᠪᡝᡳ ᠵᠠᠯᠠᠨ ᠪᡳᠴᡳᠮᡝ᠂ ᡝᡵᡝ ᠵᠠᠯᠠᠨ `frames_per_second`-ᡳ 4 ᡩᠣᠯᠣ 60 ᠪᡳᠴᡳᠮᡝ᠂ ᡳᠨᡠ `resolution` 580p ᡠᠯᡳ 720p ᠪᡳᠮᡝ᠂ ᠠᠰᡠ 16:9᠂ 9:16 ᡠᠯᡳ 1:1 ᠪᡳᠴᡳᠮᡝᠨᡳ ᠪᡳᠮᡝᠨᡳ。 film ᡠᠯᡳ rife ᠪᡝ ᡳᠯᡥᠠᠨ ᠪᡳᠴᡳᠮᡝ ᠵᡠᠰᡳᠯᡝᡵᡝ ᠵᠠᠯᠠᠨ ᡥᡝᠯᡳ ᠠᠰᡠ ᠵᡠᠰᡳᠯᡝᠮᡝ᠂ ᡠᠨᡩᡝᠯᡝᠨ ᠵᡠᠰᡳᠯᡝᡵᡝ ᡠᠯᡳ ᠪᡳᠴᡳᠪᡝᠨᡳ ᠮᠣᡩᡝ ᠵᠠᠯᠠᠨ ᠪᡳᠮᡝᠨᡳ。 ᡝᠨᡝ ᡩᡝᠯᡤᡳ ᠵᡠᠯᡤᡝᠨ ᡳᠯᠠᠨ ᡥᡝᠯᡳ ᠵᠠᠯᠠᠨ ᠪᡳᠮᡝ᠂ ᠵᡝᠯᡤᡳ 50 ᠵᠠᠯᠠᠨ ᡳᠯᡤᡠᠯᡤᠠᠨ ᠪᡳᠮᡝᠨᡳ。

- 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/mnc/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 |  |  | ᠰᡠᠨᡤᠠ ᠪᡠᠶᡝᠮᡝ ᡳ ᠵᠠᠯᠠᠨ ᡳ ᡥᡡᠯᠠᠨ᠉ |
| `negative_prompt` |  | string | no | `` |  | ᠰᡠᠨᡤᠠ ᠪᡠᠶᡝᠮᡝ ᡩᡝ ᠵᠠᠯᠠᠮᡝ ᠮᡠᠰᡝ ᡥᡡᠯᠠᠨ᠉ |
| `num_frames` |  | integer | no | `81` | 17 – 161 | ᠪᡠᠶᡝᠮᡝ ᡳ ᡶᡳᠯᡝᠮᡝ ᡳᠨᡠᠮᠪᡳ᠂ 17–161 ᡩᡝ ᠪᠠᡳᠴᡳᠨᠠᠮᠪᡳ᠉ |
| `frames_per_second` |  | integer \| null | no | `24` | 4 – 60 | ᠪᡠᠶᡝᠮᡝ ᠰᡠᠨᡤᠠ ᡳ ᡶᡳᠯᡝᠮᡝ ᡳ ᠵᠠᠰᡳᠨ 4 ᡩᡝᠴᡳ 60 ᡩᡝ᠂ `adjust_fps_for_interpolation` ᠪᡝ false ᠪᡠᠮᡝᠨ ᠰᡠᠮᡝᠮᠪᡳ᠉ ᠵᠠᠨ ᡳ ᠵᠠᠰᡳᠨ true ᠪᠠ 1 ᡳ ᠵᠠᠰᡳᠮᡝᠨ ᡩᡝ ᠰᡝᠨᡩᡝᠮᡝᠨ 16 FPS ᡩᡝ 32 FPS ᠪᠠᠶᠠᠨ᠉ |
| `seed` |  | integer \| null | no |  |  | ᠪᡠᠶᡝᠮᡝ ᡩᡝ ᠰᠠᡳᠨ ᠪᡳᠰᡳᠮᡝ ᠪᠠᠨᠵᡳᠨᠠᠮᡝ᠉ None ᡩᡝ ᠪᡳᠮᡝ ᠪᠠᠨᠵᡳᠨ ᡤᠣᠯᠣᠮᡝ᠉ |
| `resolution` |  | enum (string) | no | `720p` | `580p`, `720p` | ᠪᡠᠶᡝᠮᡝ ᠰᡠᠨᡤᠠ ᡳ ᠵᠠᠯᠠᠨ᠄ 580p ᠠᡴᡳ 720p᠉ |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `16:9`, `9:16`, `1:1` | ᠪᡠᠶᡝᠮᡝ ᡳ ᠰᡠᠨᡤᠠ ᡳ ᡳᠯᡤᠠᠨ ᡳ ᡵᠠᠰᡠ, 16:9 ᠠᠮᠠ 9:16. |
| `num_inference_steps` |  | integer | no | `40` | 2 – 50 | ᠰᠠᠮᡝᠨᡳ ᠵᠠᡴᡠᠨᠨᡳ ᠵᠠᠯᠠᠨ, ᠮᡠᠯᡥᡝ ᠵᠠᠯᠠᠨᡩᠣᠮᡝᠨᡳ ᠵᡝᠪᡝᠯᡝ ᠵᡠᠯᡝᠮᡝ. |
| `enable_safety_checker` |  | boolean | no | `false` |  | ᠵᠠᠰᡳᠮᡝ ᡳ ᠵᠠᠨ ᠠᠮᠠᠯᠠ ᡩᠠᠪᠠᠨ᠂ true ᠪᡝ ᠵᠠᠰᡳᠮᠪᡳ᠉ |
| `enable_output_safety_checker` |  | boolean | no | `false` |  | ᠪᡠᠶᡝᠮᡝ ᠰᡠᠨᡤᠠ ᡳ ᠠᠮᠠᠯᠠ ᡩᠠᠪᠠᠨ᠂ true ᠪᡝ ᠵᠠᠰᡳᠮᠪᡳ᠉ |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | ᠠᠮᠪᠠ ᠪᡠᠮᡝ ᡳ ᡥᡡᠯᠠᠨ ᠪᡝ ᠵᡠᠯᡝ ᠵᡠᠯᡝᠮᡝ᠉ |
| `guidance_scale` |  | number | no | `3.5` | 1 – 10 | Classifier-free guidance ᡩᡝ ᠵᠠᠯᠠᠨ ᠵᡠᠯᡝᠮᡝ; ᠵᠠᠯᠠᠨ ᠣᠯᡥᠠ ᠣᠴᡳ ᡥᡡᠯᠠᠨ ᡩᡝ ᠵᡝᠯᡳᠨ ᠵᡠᠯᡝᠮᡝ. |
| `shift` |  | number | no | `5` | 1 – 10 | ᠰᡠᠨᡤᠠ ᠰᡳᠯᡤᠠᠨ ᡳ ᠵᠠᠰᡳᠨ᠂ 1.0–10.0 ᠪᡝ ᠵᡝᠮᡝᠮᠪᡳ᠉ |
| `interpolator_model` |  | enum (string) | no | `film` | `none`, `film`, `rife` | ᡶᡳᠯᡝᠮᡝ ᡳ ᠵᠠᠯᠠᠮᡝ ᠵᠠᠰᡳᠨ᠄ None ᠪᡝ ᠰᠠᠮᡝᠮᠪᡳ᠂ ᠠᡴᡳ ᠵᠠᠰᡳᠮᡝ ᠮᠣᡩᡝᠯ ᠪᡝ ᠵᡝᠮᡝᠮᠪᡳ᠉ |
| `num_interpolated_frames` |  | integer | no | `0` | 0 – 4 | ᠵᡝᠨᡠ ᠪᡠᠶᡝᠮᡝ ᠵᡠᠶᡝᠨ ᡳ ᡳᠯᡳ ᡩᡝ 0–4 ᡶᡳᠯᡝᠮᡝ ᠣᠨᡩᠣᠮᠪᡳ᠉ |
| `adjust_fps_for_interpolation` |  | boolean | no | `true` |  | ᡶᡳᠯᡝᠮᡝ ᡳ ᠵᠠᠰᡳᠨ ᡳ ᠪᡠᠮᡝᠯᡝᠨ᠄ false ᠪᡝ ᠵᡝᠮᡝ ᠵᠠᠰᡳᠨ ᡩᡝ ᠰᡠᠮᡝᠮᠪᡳ᠂ true ᡩᡝ 1 ᡳ ᠵᠠᠰᡳᠮᡝᠨ ᡩᡝ ᠨᠠᠮᡠᠨ ᠵᠠᠰᡳᠮᠪᡳ᠉ |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | ᠪᡠᠶᡝᠮᡝ ᠰᡠᠨᡤᠠ ᡳ ᠰᡠᠮᠪᡝ ᡳ ᠵᠠᠰᡳᠨ᠂ ᠵᠠᠰᡳᠨ ᠵᠠᠯᠠᠮᡝ ᡶᡳᠯᡝ ᠨᠠᠮᠪᡳ᠉ |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | ᠰᡠᠨᡤᠠ ᠪᡳᡥᡝ ᡳ ᠵᠠᠰᡳᠨ᠂ balanced ᠵᠠᠰᡳᠨ ᠪᠠ ᠵᡝᠯᡤᡳ ᡳ ᠵᡝᠯᡤᡳ ᡳ ᠰᠠᠮᡝᠮᠪᡳ᠉ small ᠪᡝ ᠰᡠᠮᠪᡝ ᠪᠠ ᠵᠠᠯᠠᠨ ᡳ ᠪᡳᡥᡝ ᡩᡝ ᠰᠣᠩᡤᠣᠮᠪᡳ᠉ |

## 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} | ᠪᡠᠶᡝᠮᡝ ᠵᡠᠴᡝᠨ ᡳ ᡶᡳᠯᡝ᠉ |
| `prompt` | string | ᠰᡠᠨᡤᠠ ᠪᡠᠶᡝᠮᡝ ᡳ ᡥᡡᠯᠠᠨ᠉ |
| `seed` | integer | ᠪᡠᠶᡝᠮᡝ ᡩᡝ ᠶᠠᠪᡠᡥᠠᠨ ᠪᠠᠨᠵᡳᠨᠠᠮᡝ᠉ |

## 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