# Wan VACE 14B API

> 通用 VACE 14B 影片模型：選擇任務（深度、姿勢、內繪、外繪、重新構圖），並提供多項選用輸入

透過 `task` 選擇的多用途影片產生與編輯模型：深度、姿勢、內繪、外繪或重新構圖。輸入包括來源 `video_url`、遮罩影片或圖像、`ref_image_urls`，以及首影格和末影格 URL。`num_frames` 範圍為 17 至 241，`resolution` 範圍為 240p 至 720p。可選擇 unipc、dpm++ 和 euler 取樣器。

- Model id: `wan-vace-14b`
- Made by: Alibaba
- Category: Video to Video
- Output: video
- Price per second of your output video: from $0.04 / second of output video (cheapest run $0.04 (40 API credits))
- Run: `POST https://api.doitong.com/v1/run/wan-vace-14b`
- Quote: `POST https://api.doitong.com/v1/quote/wan-vace-14b`
- Docs page: https://doitong.com/zh-TW/developers/models/wan-vace-14b

## Pricing

Price: **from $0.04 / second of output video** (the lowest tier; the quote prices your exact input). Price per second of your output video: the input files are measured before the run (length, resolution, frame rate). The quote measures the same files and is exactly what the run charges.

Price by tier:

- 240p: $0.04 / second of output video
- 360p: $0.04 / second of output video
- 480p: $0.04 / second of output video
- 580p: $0.06 / second of output video
- auto: $0.08 / second of output video
- 720p: $0.08 / second of output video

The full example input below costs $0.405 = 405 API credits (5.0625 s output video × $0.08 (auto)).

Prices are the upstream price in USD, paid from the API balance in API credits (1000 API credits = 1 USD). `POST https://api.doitong.com/v1/quote/wan-vace-14b` 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 |
|---|---|---|---|---|---|---|
| `prompt` |  | string | yes |  |  | 引導影片生成的文字指示。 |
| `negative_prompt` |  | string | no | `letterboxing, borders, black bars, bright colors, overexposed, static, blurred details, subtitles, style, artwork, painting, picture, still, overall gray, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, malformed limbs, fused fingers, still picture, cluttered background, three legs, many people in the background, walking backwards` |  | 生成影片時套用的負面提示詞。 |
| `match_input_num_frames` |  | boolean | no | `false` |  | 生成影片影格數的來源：false 使用 `num_frames`，true 則複製輸入影片的影格數。 |
| `num_frames` |  | integer | no | `81` | 17 – 241 | 輸出影格數，包含範圍為 81–241。 |
| `match_input_frames_per_second` |  | boolean | no | `false` |  | 生成影片影格率的來源：false 使用 `frames_per_second`，true 則複製輸入影片的影格率。 |
| `frames_per_second` |  | integer \| null | no | `16` | 5 – 30 | 生成影片的影格率，僅在 `match_input_frames_per_second` 不為 true 時套用；接受 5–30 影格/秒。 |
| `task` |  | enum (string) | no | `depth` | `depth`, `pose`, `inpainting`, `outpainting`, `reframe` | 模型執行的工作類型。 |
| `seed` |  | integer \| null | no |  |  | 使生成結果可重現的種子。設為 None 會隨機選擇種子。 |
| `resolution` |  | enum (string) | no | `auto` | `auto`, `240p`, `360p`, `480p`, `580p`, `720p` | 輸出影片的解析度。 |
| `aspect_ratio` |  | enum (string) | no | `auto` | `auto`, `16:9`, `1:1`, `9:16` | 生成影片的長寬比。 |
| `num_inference_steps` |  | integer | no | `30` | 2 – 50 | 取樣步數；步數越多，處理時間越長但品質越好。 |
| `guidance_scale` |  | number | no | `5` | 1 – 10 | 透過無分類器引導控制的提示詞對齊強度；提高此比例會促使生成圖像更貼近文字描述。 |
| `sampler` |  | enum (string) | no | `unipc` | `unipc`, `dpm++`, `euler` | 生成影片時使用的取樣器。 |
| `shift` |  | number | no | `5` | 1 – 15 | 生成影片時套用的偏移設定。 |
| `video_url` | `video` | string (video URL) \| null | no |  |  | 模型的影片參考，在提供時以指向來源檔案的 URL 傳入。 |
| `mask_video_url` |  | string (video URL) \| null | no |  |  | 模型的遮罩參考，在提供時以指向來源檔案的 URL 傳入。 |
| `mask_image_url` |  | string (image URL) \| null | no |  |  | 透過檔案 URL 提供的引導遮罩；存在時優先於遮罩影片 URL。模型會使用此遮罩引導遮罩影片的建立。 |
| `ref_image_urls` |  | array of image URL | no |  |  | 選用的來源圖像 URL，提供模型作為參考圖像使用。 |
| `first_frame_url` | `image` | string \| null | no |  |  | 透過 URL 提供的選用第一格參考，供模型處理影片時使用。 |
| `last_frame_url` | `end_image` | string \| null | no |  |  | 透過 URL 提供的選用最後一格參考，供模型處理影片時使用。 |
| `enable_safety_checker` |  | boolean | no | `false` |  | 安全檢查開關；關閉設定需要帳戶授權。沒有該授權時，每個請求都會經過檢查，不受設定影響；true 會啟用檢查器。 |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | 控制是否啟用提示詞擴展。 |
| `preprocess` |  | boolean | no | `false` |  | 控制輸入影片的前處理。 |
| `acceleration` |  | enum (string) \| null | no | `regular` | `none`, `low`, `regular` | 推論加速設定，可選 'none' 或 'regular'：加速處理可大幅提升速度，但會造成非常輕微的輸出變化。 |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | 結果影片的品質等級。 |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | 結果影片的寫入模式。 |
| `num_interpolated_frames` |  | integer | no | `0` | 0 – 5 | 插值次數：0 表示保留原始影格，不進行插值；其他值指定要在每兩個影格之間生成的中間影格數。 |
| `temporal_downsample_factor` |  | integer | no | `0` | 0 – 5 | 影片跳影格倍率，以整數表示；每個降採樣倍率會自動套用一次升採樣。使用 0 可停用時間降採樣。 |
| `enable_auto_downsample` |  | boolean | no | `false` |  | 自動調整影格數：啟用後，模型會處理長度合適且經時間降採樣的影片，之後再透過插值還原原始影格數。 |
| `auto_downsample_min_fps` |  | number | no | `15` | 1 – 60 | 降採樣後允許的最低影格速率，單位為每秒影格數。對於低動態影片，降低此值可允許更大幅度的降採樣和更長的序列；動作非常快速時可能需要更高的值，但預設值適用於大多數影片。自動降採樣會使用此門檻，尋找能保留細節的最低倍率。 |
| `interpolator_model` |  | enum (string) | no | `film` | `rife`, `film` | 影格插值模型選擇：'rife' 或 'film'。 |
| `transparency_mode` |  | enum (string) | no | `content_aware` | `content_aware`, `white`, `black` | 起始和結束影格的透明度處理方式，決定如何填補其透明區域。 |
| `return_frames_zip` |  | boolean | no | `false` |  | 控制是否同時回傳包含所有生成影格的 ZIP 封存檔；為 true 時啟用。 |

File parameters (`video`, `mask_video_url`, `mask_image_url`, `ref_image_urls`) 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"
}
```

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.com/v1/run/wan-vace-14b?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.com/v1/requests/REQUEST_ID?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY"
```

### JavaScript

```javascript
const API = "https://api.doitong.com/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-vace-14b?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.com/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-vace-14b", 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.com/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-vace-14b",
      "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-vace-14b",
  "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": 405,
    "usd": "0.405",
    "charged": 405,
    "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,
      "width": 1024,
      "height": 768,
      "fps": 1.0,
      "duration": 5,
      "num_frames": 1
    },
    "prompt": "string",
    "seed": 42,
    "frames_zip": {
      "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
    }
  },
  "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.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `video` | object {url, content_type, file_name, file_size, width, height, fps, duration, num_frames} | 生成產生的影片檔案。 |
| `prompt` | string | 用於生成輸出的提示詞。 |
| `seed` | integer | 生成期間套用的種子值。 |
| `frames_zip` | object {url, content_type, file_name, file_size} \| null | 包含所有影片影格的 ZIP 封存檔，在提出要求時回傳。 |

## Related models

- [Wan VACE 14B · Depth](https://doitong.com/developers/models/wan-vace-14b/depth.md) (`wan-vace-14b/depth`): from $0.04 / second of output video
- [Wan VACE 14B · Inpainting](https://doitong.com/developers/models/wan-vace-14b/inpainting.md) (`wan-vace-14b/inpainting`): from $0.04 / second of output video
- [Wan VACE 14B · Outpainting](https://doitong.com/developers/models/wan-vace-14b/outpainting.md) (`wan-vace-14b/outpainting`): from $0.04 / second of output video
- [Wan VACE 14B · Pose](https://doitong.com/developers/models/wan-vace-14b/pose.md) (`wan-vace-14b/pose`): from $0.04 / second of output video
- [Wan VACE 14B · Reframe](https://doitong.com/developers/models/wan-vace-14b/reframe.md) (`wan-vace-14b/reframe`): from $0.04 / second of output video
- [Happy Horse Video Edit](https://doitong.com/developers/models/alibaba/happy-horse/video-edit.md) (`alibaba/happy-horse/video-edit`): from $0.28 / second of input video
- [Wan 2.1 VACE Long Reframe](https://doitong.com/developers/models/wan-vace-apps/long-reframe.md) (`wan-vace-apps/long-reframe`): from $0.04 / 2 seconds of input video
- [Wan 2.2 VACE Fun A14B · Depth](https://doitong.com/developers/models/wan-22-vace-fun-a14b/depth.md) (`wan-22-vace-fun-a14b/depth`): from $0.05 / second of output video

## Links

- HTML page: https://doitong.com/developers/models/wan-vace-14b
- 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-vace-14b
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/wan-vace-14b