# Wan v2.2 5B · Text to Video API

> 5B modelle text-to-video: 580p veya 720p, 16:9, 9:16 veya 1:1 ve isteğe bağlı kare enterpolasyonu

Metin `prompt`undan video klibi oluşturur. Uzunluk `num_frames` (17 ile 161) ve `frames_per_second` (4 ile 60) ile belirlenir; `resolution` 580p veya 720p, en-boy oranı 16:9, 9:16 veya 1:1'dir. film veya rife ile kare enterpolasyonu etkinleştirilebilir; çıktı kalitesi ve dosya yazma modu ayarlanabilir. Bu, en fazla 50 çıkarım adımına sahip standart yönlendirme çeşididir.

- 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/tr/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 |  |  | Video üretimine yön veren metin yönergeleri. |
| `negative_prompt` |  | string | no | `` |  | Video üretilirken uygulanan negatif istem. |
| `num_frames` |  | integer | no | `81` | 17 – 161 | 17–161 dahil aralığında üretim kare sayısı. |
| `frames_per_second` |  | integer \| null | no | `24` | 4 – 60 | 4 ile 60 arasındaki değerleri kabul eden üretilen video kare hızı; `adjust_fps_for_interpolation` false olarak ayarlanırsa bu hızı değiştirmeden korur. Enterpolasyon kullanılırken `adjust_fps_for_interpolation` true olduğunda (varsayılanı budur), son FPS değerini elde etmek için bu hızı enterpole edilen kare sayısının bir fazlasıyla çarpın. Örneğin, 1 enterpolasyonlu kare ile 16 FPS, 32 FPS olur. |
| `seed` |  | integer \| null | no |  |  | Üretimi tekrarlanabilir kılan seed. None olarak ayarlanması seed'in rastgele seçilmesini sağlar. |
| `resolution` |  | enum (string) | no | `720p` | `580p`, `720p` | 580p veya 720p olan çıktı video çözünürlüğü. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `16:9`, `9:16`, `1:1` | Çıktı videosunun 16:9 veya 9:16 olan en-boy oranı. |
| `num_inference_steps` |  | integer | no | `40` | 2 – 50 | Sayı arttıkça daha uzun işlem süresi karşılığında daha iyi kalite sunan örnekleme adımı sayısı. |
| `enable_safety_checker` |  | boolean | no | `false` |  | İşleme öncesi girdi güvenlik taraması; yalnızca yetkili hesaplar bunu kapatabilir. Yetkisi olmayan istekler her zaman taranır; aksi halde true taramayı etkinleştirir. |
| `enable_output_safety_checker` |  | boolean | no | `false` |  | Üretilen videonun güvenlik taramasını denetler; true ayarı üretim sonrası kontrolü etkinleştirir. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | Büyük dil modelinin istemi ayrıntılarla zenginleştirmesine izin verir. Bu genişletmenin etkinleştirilmesi istemin anlamını değiştirmez. |
| `guidance_scale` |  | number | no | `3.5` | 1 – 10 | Ölçek arttıkça olası kalite kaybı karşılığında istemle daha yakın eşleşme sağlayan sınıflandırıcısız yönlendirme gücü. |
| `shift` |  | number | no | `5` | 1 – 10 | 1.0–10.0 aralığında izin verilen video kaydırma ayarı. |
| `interpolator_model` |  | enum (string) | no | `film` | `none`, `film`, `rife` | Kare enterpolasyonu ayarı: enterpolasyonu atlamak için None seçin veya gerçekleştirecek modeli belirtin. |
| `num_interpolated_frames` |  | integer | no | `0` | 0 – 4 | Üretilen her iki kare arasındaki her boşluğa 0–4 enterpolasyonlu kare ekleyin. |
| `adjust_fps_for_interpolation` |  | boolean | no | `true` |  | Kare hızı ayarlama anahtarı: false sağlanan FPS'yi korur; true bunu enterpolasyonlu kare sayısının bir fazlasıyla ölçekler. Böylece 1 kare enterpole edilip ayarlama etkinleştirildiğinde 16 FPS, 32 FPS olur. |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | Ayar arttıkça daha büyük dosyalar karşılığında daha iyi görseller sağlayan çıktı video kalitesi ayarı. |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | balanced hız ve kalite arasında denge sunan video yazma modu. En küçük dosyalar ve en yavaş yazma için small seçin; daha hızlı yazma sonuçları erken döndürür ancak daha büyük dosyalar oluşturur. |

## 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} | Üretimle oluşturulan video dosyası. |
| `prompt` | string | Videoyu üretmek için kullanılan metin istemi. |
| `seed` | integer | Üretim sırasında uygulanan seed değeri. |

## 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