# Wan · v2.2 5b · Text to Video · Fast Wan API

> Wan 5B text-to-video tere me te putanga 480p, 580p, 720p rānei, me te whakawhitinga kōwhiringa

Text-to-video mā te hanganga FastVideo o te tauira 5B. Ka whiwhi i tētahi `prompt` me tētahi `negative_prompt` kōwhiringa, me `num_frames` mai i te 17 ki te 161, `frames_per_second` 4 ki te 60, me te hanga 16:9, 9:16, 1:1 rānei. Ka tāpiri i te kōwhiringa 480p ki te taha o te 580p me te 720p, kāore he tāuru tatau hipanga, ā, e tautoko ana i te whakawhitinga anga film, rife rānei.

- Model id: `wan/v2.2-5b/text-to-video/fast-wan`
- Made by: Alibaba
- Category: Text to Video
- Output: video
- Price: from $0.0125 / video (cheapest run $0.013 (13 API credits))
- Run: `POST https://api.doitong.ru/v1/run/wan/v2.2-5b/text-to-video/fast-wan`
- Quote: `POST https://api.doitong.ru/v1/quote/wan/v2.2-5b/text-to-video/fast-wan`
- Docs page: https://doitong.com/mi/developers/models/wan/v2.2-5b/text-to-video/fast-wan

## Pricing

Price: **from $0.0125 / video** (the lowest tier; the quote prices your exact input). Billed once per generated video.

Price rules (the first rule that matches the input wins; a parameter you leave out counts as its default):

- When `resolution` = 580p: $0.0188 (18.75 API credits) / video
- When `resolution` = 720p: $0.025 (25 API credits) / video

The full example input below costs $0.025 = 25 API credits (1 video × 25 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/fast-wan` 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 |  |  | Ngā tohutohu kuputuhi hei ārahi i te whakaputanga ataata. |
| `negative_prompt` |  | string | no | `` |  | Te tohutohu tōraro e whakamahia ana i te whakaputa ataata. |
| `num_frames` |  | integer | no | `81` | 17 – 161 | Te maha o ngā anga mō te whakaputanga, he awhe whakauru 17–161. |
| `frames_per_second` |  | integer \| null | no | `24` | 4 – 60 | Te auau anga ataata kua whakaputaina, e whakaae ana ki ngā uara mai i te 4 ki te 60; mā te tautuhi `adjust_fps_for_interpolation` ki false ka pupuri tonu i tēnei auau. Ina whakamahia te whakanuitanga, ā, ko te taunoa o `adjust_fps_for_interpolation` he true, whakareatia tēnei auau ki te kotahi tāpirihia ki te maha o ngā anga kua whakanuitia hei whiwhi i te FPS whakamutunga. Hei tauira, ka huri te 16 FPS me te 1 anga kua whakanuitia ki te 32 FPS. |
| `seed` |  | integer \| null | no |  |  | Te kākano e taea ai te tārua o te whakaputanga. Mā te tautuhi ki None e kōwhiri matapōkeretia ai he kākano. |
| `resolution` |  | enum (string) | no | `720p` | `480p`, `580p`, `720p` | Te taumira ataata putanga, 580p, 720p rānei. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `16:9`, `9:16`, `1:1` | Te ōwehenga-āhuatanga o te ataata putanga, arā, 16:9, 9:16 rānei. |
| `enable_safety_checker` |  | boolean | no | `false` |  | Te tirotiro haumaru tāuru i mua i te tukatuka, ā, ko ngā pūkete whai mana anake ka taea te whakaweto. Ka tirotirohia tonutia ngā tono kāore he mana; ki te whai mana, mā true e whakahohe te tirotiro. |
| `enable_output_safety_checker` |  | boolean | no | `false` |  | Ka whakahaere i te tirotiro haumaru o te ataata kua whakaputaina; mā te tautuhi true e whakahohe te tirotiro i muri i te whakaputanga. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | Tukua he tauira reo nui kia whakarangatira i te tohutohu ki ngā taipitopito. Mā tēnei whakawhānuitanga e noho pūmau ai te tikanga o te tohutohu. |
| `guidance_scale` |  | number | no | `3.5` | 1 – 10 | Te kaha arataki classifier-free, ka whakawhiti i te ngaronga kounga pea mō te ū tata ake ki te tohutohu ina piki te tauine. |
| `interpolator_model` |  | enum (string) | no | `film` | `none`, `film`, `rife` | Te tautuhinga whakanui anga: kōwhiria None hei karo i te whakanui, tautuhia rānei te tauira hei mahi māna. |
| `num_interpolated_frames` |  | integer | no | `0` | 0 – 4 | Whakaurua ngā anga kua whakanuitia 0–4 ki ia āputa i waenga i ngā anga whakaputa e rua. |
| `adjust_fps_for_interpolation` |  | boolean | no | `true` |  | Pana whakatikatika auau-anga: mā false e pupuri te FPS kua tukuna, ā, mā true e whakareatia ki te kotahi tāpirihia ki te maha o ngā anga kua whakanuitia. Nō reira, ka huri te 16 FPS ki te 32 FPS ina whakanuitia te 1 anga, ā, ka whakahohea te whakatikatika. |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | Te tautuhinga kounga ataata putanga, e whakawhiti ana i te rahi ake o te kōnae mō ngā āhua pai ake ina piki te tautuhinga. |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | Te aratau tuhi ataata, ko balanced te taurite i waenga i te tere me te kounga. Kōwhiria small mō ngā kōnae iti rawa me te tuhi pōturi rawa; mā te tuhi tere ake ka hoki wawe mai ngā hua, engari ka nui ake ngā kōnae. |

## 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/fast-wan?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/fast-wan?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/fast-wan", 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/fast-wan",
      "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/fast-wan",
  "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": 25,
    "usd": "0.025",
    "charged": 25,
    "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} | Te kōnae ataata i whakaputaina. |
| `prompt` | string | Te tohutohu kuputuhi i whakamahia hei whakaputa i te ataata. |
| `seed` | integer | Te uara kākano i whakamahia i te whakaputanga. |

## Related models

- [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
- [MiniMax H3 Text to Video](https://doitong.com/developers/models/minimax/h3/text-to-video.md) (`minimax/h3/text-to-video`): from $0.05 / second
- [Seedance 2.0 Fast Text to Video](https://doitong.com/developers/models/bytedance/seedance-2.0/fast/text-to-video.md) (`bytedance/seedance-2.0/fast/text-to-video`): from $0.113 / second
- [Seedance 2.0 Text to Video](https://doitong.com/developers/models/bytedance/seedance-2.0/text-to-video.md) (`bytedance/seedance-2.0/text-to-video`): from $0.141 / second

## Links

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