# Wan v2.2 5B · Image to Video API

> Wan 2.2 5Bによるimage-to-video。柔軟なフレーム数、580pまたは720p、フレーム補間に対応

テキスト`prompt`から画像（`image_url`）をアニメーション化します。`num_frames`は17～161、`frames_per_second`は4～60で、解像度は580pまたは720pです。アスペクト比はauto、16:9、9:16、1:1から選択できます。フレーム補間はfilmまたはrifeを使用し、各フレーム間に0～4フレームを追加します。`video_quality`と`video_write_mode`でエンコードを制御します。

- Model id: `wan/v2.2-5b/image-to-video`
- Made by: Alibaba
- Category: Image 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/image-to-video`
- Quote: `POST https://api.doitong.ru/v1/quote/wan/v2.2-5b/image-to-video`
- Docs page: https://doitong.com/ja/developers/models/wan/v2.2-5b/image-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/image-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

Send either the canonical name or the native field name (not both). Canonical names are the same across models.

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `image_url` | `image` | string (image URL) | yes |  |  | ソース画像 URL。選択したアスペクト比によって前処理の要否が決まり、不一致の場合はリサイズ後に中央クロップされます。 |
| `prompt` |  | string | yes |  |  | 動画生成を導くテキスト指示。 |
| `num_frames` |  | integer | no | `81` | 17 – 161 | 生成するフレーム数。17～161（両端を含む）。 |
| `frames_per_second` |  | integer \| null | no | `24` | 4 – 60 | 生成動画のフレームレート。4～60を受け付けます。`adjust_fps_for_interpolation`をfalseにすると、このレートをそのまま保持します。補間を使用し、`adjust_fps_for_interpolation`がtrue（デフォルト）の場合、最終FPSはこのレートに補間フレーム数に1を加えた値を掛けて求めます。たとえば、16 FPSで補間フレームが1つの場合は32 FPSになります。 |
| `negative_prompt` |  | string | no | `` |  | 動画生成時に適用するネガティブプロンプト。 |
| `seed` |  | integer \| null | no |  |  | 生成を再現可能にするシード。None に設定するとシードをランダムに選択します。 |
| `resolution` |  | enum (string) | no | `720p` | `580p`, `720p` | 出力動画の解像度。580pまたは720p。 |
| `aspect_ratio` |  | enum (string) | no | `auto` | `auto`, `16:9`, `9:16`, `1:1` | 生成動画の縦横比。'auto'に設定すると入力画像から自動選択されます。 |
| `num_inference_steps` |  | integer | no | `40` | 2 – 50 | サンプリングステップ数。増やすほど処理時間が長くなる代わりに品質が向上します。 |
| `enable_safety_checker` |  | boolean | no | `false` |  | 処理前の入力安全性チェック。無効化できるのは認証済みアカウントのみです。認証のないリクエストは常にチェックされ、それ以外ではtrueでチェックが有効になります。 |
| `enable_output_safety_checker` |  | boolean | no | `false` |  | 生成動画の安全性チェックを制御します。trueにすると生成後にチェックします。 |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | 大規模言語モデルにプロンプトを詳細化させます。この拡張を有効にしても、プロンプトの意味は変わりません。 |
| `guidance_scale` |  | number | no | `3.5` | 1 – 10 | Classifier-free guidanceの強度。スケールを上げるほどプロンプトへの一致度が高まる一方、品質低下の可能性があります。 |
| `shift` |  | number | no | `5` | 1 – 10 | 動画のシフト設定。許容範囲は1.0～10.0です。 |
| `interpolator_model` |  | enum (string) | no | `film` | `none`, `film`, `rife` | フレーム補間設定。補間をスキップするにはNoneを、実行するモデルを指定するにはモデル名を選択します。 |
| `num_interpolated_frames` |  | integer | no | `0` | 0 – 4 | 生成された2つのフレーム間の各間隔に、0～4個の補間フレームを挿入します。 |
| `adjust_fps_for_interpolation` |  | boolean | no | `true` |  | フレームレート調整の切り替え。falseでは指定したFPSを保持し、trueでは補間フレーム数に1を加えた値を掛けます。したがって、補間フレームが1つで調整が有効な場合、16 FPSは32 FPSになります。 |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | 出力動画の品質設定。値を上げるほどファイルサイズが大きくなる代わりに映像が改善されます。 |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | 動画書き出しモード。balancedは速度と品質の妥協点です。最小ファイルかつ最も遅い書き出しにはsmallを選択します。高速な書き出しでは結果が早く返りますが、ファイルサイズは大きくなります。 |

File parameters (`image`) take a public `https://` URL, a `data:` URI up to 10 MB, or the `file_url` of an upload from `POST /files`.

## Example input

Required parameters only:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
  "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

A fuller example:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
  "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

## 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/image-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",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  }'

# 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/image-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",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  }),
});
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",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
}

# 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/image-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/image-to-video",
      "input": {
        "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
        "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
      },
      "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/image-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",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  },
  "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": "The white dragon warrior stands still, eyes full of determination and strength. The camera slowly moves closer or circles around the warrior, highlighting the powerful presence and heroic spirit of the character.",
    "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} | 生成された動画ファイル。 |
| `prompt` | string | 動画生成に使用するテキストプロンプト。 |
| `seed` | integer | 生成時に適用したシード値。 |

## 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](https://doitong.com/developers/models/wan/v2.2-5b/text-to-video.md) (`wan/v2.2-5b/text-to-video`): $0.15 / video
- [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 3.0 Image to Video](https://doitong.com/developers/models/alibaba/wan-3.0/image-to-video.md) (`alibaba/wan-3.0/image-to-video`): from $0.05 / second
- [FLUX 3 Max Image to Video](https://doitong.com/developers/models/blackforestlabs/flux-3-max/image-to-video.md) (`blackforestlabs/flux-3-max/image-to-video`): from $0.0425 / second of output video
- [Grok Imagine Video 1.5 Image to Video](https://doitong.com/developers/models/xai/grok-imagine-video/v1.5/image-to-video.md) (`xai/grok-imagine-video/v1.5/image-to-video`): from $0.082 / second
- [Kling 3.0 Pro Image to Video](https://doitong.com/developers/models/kling-video/v3/pro/image-to-video.md) (`kling-video/v3/pro/image-to-video`): from $0.112 / second
- [LTX 2.5 Pro Image to Video](https://doitong.com/developers/models/lightricks/ltx-2.5/image-to-video/pro.md) (`lightricks/ltx-2.5/image-to-video/pro`): from $0.12 / second

## Links

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