# Wan v2.2 5B · Text to Video API

> Text-to-video dengan model 5B: 580p atau 720p, 16:9, 9:16, atau 1:1, serta interpolasi bingkai opsional

Membuat klip video dari teks `prompt`. Durasi ditentukan oleh `num_frames` (17 hingga 161) dan `frames_per_second` (4 hingga 60), dengan `resolution` 580p atau 720p dan rasio aspek 16:9, 9:16, atau 1:1. Interpolasi bingkai dengan film atau rife dapat diaktifkan, dan kualitas output serta mode penulisan file dapat disesuaikan. Ini adalah varian dengan panduan standar dan hingga 50 langkah inferensi.

- 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/id/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 |  |  | Instruksi teks yang memandu pembuatan video. |
| `negative_prompt` |  | string | no | `` |  | Prompt negatif yang diterapkan saat membuat video. |
| `num_frames` |  | integer | no | `81` | 17 – 161 | Jumlah bingkai untuk pembuatan, dengan rentang inklusif 17–161. |
| `frames_per_second` |  | integer \| null | no | `24` | 4 – 60 | Laju bingkai video yang dihasilkan, menerima nilai dari 4 hingga 60; mengatur `adjust_fps_for_interpolation` ke false mempertahankan laju ini tanpa perubahan. Saat interpolasi digunakan dan `adjust_fps_for_interpolation` true (bawaannya), kalikan laju ini dengan satu ditambah jumlah bingkai yang diinterpolasi untuk memperoleh FPS akhir. Misalnya, 16 FPS dengan 1 bingkai yang diinterpolasi menjadi 32 FPS. |
| `seed` |  | integer \| null | no |  |  | Seed yang membuat pembuatan dapat direproduksi. Mengaturnya ke None akan memilih seed secara acak. |
| `resolution` |  | enum (string) | no | `720p` | `580p`, `720p` | Resolusi video output, 580p atau 720p. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `16:9`, `9:16`, `1:1` | Rasio aspek video output, yaitu 16:9 atau 9:16. |
| `num_inference_steps` |  | integer | no | `40` | 2 – 50 | Jumlah langkah sampling, yang menukar waktu pemrosesan lebih lama dengan kualitas lebih baik seiring bertambahnya jumlah. |
| `enable_safety_checker` |  | boolean | no | `false` |  | Penyaringan keamanan input sebelum pemrosesan, yang hanya dapat dinonaktifkan oleh akun berwenang. Permintaan tanpa otorisasi selalu disaring; jika tidak, true mengaktifkan penyaringan. |
| `enable_output_safety_checker` |  | boolean | no | `false` |  | Mengontrol penyaringan keamanan video yang dihasilkan; nilai true mengaktifkan pemeriksaan setelah pembuatan. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | Izinkan large language model memperkaya prompt dengan detail. Mengaktifkan ekspansi ini tidak mengubah makna prompt. |
| `guidance_scale` |  | number | no | `3.5` | 1 – 10 | Kekuatan panduan tanpa classifier, yang menukar kemungkinan penurunan kualitas dengan pencocokan prompt yang lebih dekat seiring meningkatnya skala. |
| `shift` |  | number | no | `5` | 1 – 10 | Pengaturan pergeseran video, dengan rentang yang diizinkan 1.0–10.0. |
| `interpolator_model` |  | enum (string) | no | `film` | `none`, `film`, `rife` | Pengaturan interpolasi bingkai: pilih None untuk melewati interpolasi, atau tentukan model untuk melakukannya. |
| `num_interpolated_frames` |  | integer | no | `0` | 0 – 4 | Sisipkan 0–4 bingkai yang diinterpolasi ke setiap celah antara dua bingkai yang dihasilkan. |
| `adjust_fps_for_interpolation` |  | boolean | no | `true` |  | Sakelar penyesuaian laju bingkai: false mempertahankan FPS yang diberikan, sedangkan true mengalikannya dengan satu ditambah jumlah bingkai yang diinterpolasi. Jadi, 16 FPS menjadi 32 FPS saat 1 bingkai diinterpolasi dan penyesuaian diaktifkan. |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | Pengaturan kualitas video output yang menukar ukuran file lebih besar dengan visual yang lebih baik saat nilainya meningkat. |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | Mode penulisan video, dengan balanced sebagai kompromi antara kecepatan dan kualitas. Pilih small untuk file terkecil dan penulisan paling lambat; penulisan yang lebih cepat mengembalikan hasil lebih awal tetapi menghasilkan file yang lebih besar. |

## 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} | File video yang dihasilkan oleh pembuatan. |
| `prompt` | string | Prompt teks yang digunakan untuk menghasilkan video. |
| `seed` | integer | Nilai seed yang diterapkan selama pembuatan. |

## 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