# Wan VACE 14B API

> Model video VACE 14B umum: pilih tugas (peta kedalaman, pose, inpainting, outpainting, reframe) dengan banyak input pilihan

Penjana dan penyunting video pelbagai guna yang dipilih melalui `task`: peta kedalaman, pose, inpainting, outpainting atau reframe. Input termasuk `video_url` sumber, video atau imej pelitup, `ref_image_urls`, serta URL bingkai pertama dan terakhir. `num_frames` berjulat daripada 17 hingga 241 dan `resolution` daripada 240p hingga 720p. Pensampel unipc, dpm++ dan euler boleh dipilih.

- 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.ru/v1/run/wan-vace-14b`
- Quote: `POST https://api.doitong.ru/v1/quote/wan-vace-14b`
- Docs page: https://doitong.com/ms/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.ru/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 |  |  | Arahan teks yang memandu penjanaan video. |
| `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` |  | Prompt negatif yang digunakan semasa menjana video. |
| `match_input_num_frames` |  | boolean | no | `false` |  | Sumber bilangan bingkai video yang dijana: false menggunakan `num_frames`, manakala true menyalin bilangan bingkai video input. |
| `num_frames` |  | integer | no | `81` | 17 – 241 | Bilangan bingkai output, dengan julat inklusif 81–241. |
| `match_input_frames_per_second` |  | boolean | no | `false` |  | Sumber kadar bingkai video yang dijana: false menggunakan `frames_per_second`, manakala true menyalin kadar bingkai video input. |
| `frames_per_second` |  | integer \| null | no | `16` | 5 – 30 | Kadar bingkai video yang dijana, digunakan hanya apabila `match_input_frames_per_second` bukan true; nilai yang diterima ialah 5–30 bingkai sesaat. |
| `task` |  | enum (string) | no | `depth` | `depth`, `pose`, `inpainting`, `outpainting`, `reframe` | Jenis tugas yang dilakukan oleh model. |
| `seed` |  | integer \| null | no |  |  | Seed yang menjadikan penjanaan boleh diulang. Menetapkannya kepada None memilih seed secara rawak. |
| `resolution` |  | enum (string) | no | `auto` | `auto`, `240p`, `360p`, `480p`, `580p`, `720p` | Resolusi untuk video output. |
| `aspect_ratio` |  | enum (string) | no | `auto` | `auto`, `16:9`, `1:1`, `9:16` | Nisbah bidang untuk video yang terhasil. |
| `num_inference_steps` |  | integer | no | `30` | 2 – 50 | Bilangan langkah pensampelan, yang menukar masa pemprosesan lebih lama dengan kualiti lebih baik apabila bilangannya meningkat. |
| `guidance_scale` |  | number | no | `5` | 1 – 10 | Kekuatan penjajaran prompt yang dikawal melalui panduan tanpa pengelas; meningkatkan skala menggalakkan imej yang dijana mengikut teks dengan lebih dekat. |
| `sampler` |  | enum (string) | no | `unipc` | `unipc`, `dpm++`, `euler` | Pensampel yang digunakan semasa menjana video. |
| `shift` |  | number | no | `5` | 1 – 15 | Tetapan anjakan yang digunakan semasa menjana video. |
| `video_url` | `video` | string (video URL) \| null | no |  |  | Rujukan video untuk model, dibekalkan sebagai URL yang menunjuk kepada fail sumber apabila diberikan. |
| `mask_video_url` |  | string (video URL) \| null | no |  |  | Rujukan topeng untuk model, dibekalkan sebagai URL yang menunjuk kepada fail sumber apabila diberikan. |
| `mask_image_url` |  | string (image URL) \| null | no |  |  | Topeng panduan yang dibekalkan melalui URL fail, mengatasi URL video topeng apabila tersedia. Model menggunakan topeng ini untuk memandu penciptaan video bertopeng. |
| `ref_image_urls` |  | array of image URL | no |  |  | URL imej sumber pilihan yang memberikan imej rujukan untuk digunakan oleh model. |
| `first_frame_url` | `image` | string \| null | no |  |  | Rujukan bingkai pertama pilihan yang dibekalkan melalui URL untuk digunakan oleh model semasa memproses video. |
| `last_frame_url` | `end_image` | string \| null | no |  |  | Rujukan bingkai terakhir pilihan yang dibekalkan melalui URL untuk digunakan oleh model semasa memproses video. |
| `enable_safety_checker` |  | boolean | no | `false` |  | Suis pemeriksaan keselamatan yang tetapan matinya memerlukan kebenaran akaun. Tanpa kebenaran itu, setiap permintaan diperiksa tanpa mengira tetapan; true mendayakan pemeriksa. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | Mengawal sama ada pengembangan prompt didayakan. |
| `preprocess` |  | boolean | no | `false` |  | Mengawal prapemprosesan video input. |
| `acceleration` |  | enum (string) \| null | no | `regular` | `none`, `low`, `regular` | Tetapan pecutan inferens, dengan pilihan 'none' atau 'regular': pemprosesan dipercepatkan memberikan peningkatan kelajuan yang ketara dengan perubahan output yang sangat kecil. |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | Tahap kualiti untuk video yang terhasil. |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | Mod penulisan untuk video yang terhasil. |
| `num_interpolated_frames` |  | integer | no | `0` | 0 – 5 | Bilangan interpolasi: 0 mengekalkan bingkai asal tanpa interpolasi; nilai lain menentukan bilangan bingkai perantaraan yang dijana antara bingkai tersebut. |
| `temporal_downsample_factor` |  | integer | no | `0` | 0 – 5 | Faktor pelangkauan bingkai video, dinyatakan sebagai integer, dengan pensampelan naik automatik digunakan sekali bagi setiap faktor pensampelan turun. Gunakan 0 untuk memastikan pensampelan turun temporal dilumpuhkan. |
| `enable_auto_downsample` |  | boolean | no | `false` |  | Penyesuaian bilangan bingkai automatik: mendayakan ini membolehkan model memproses video yang disampel turun secara temporal dengan panjang yang sesuai, kemudian interpolasi memulihkan bilangan bingkai asal. |
| `auto_downsample_min_fps` |  | number | no | `15` | 1 – 60 | Kadar bingkai minimum, dalam bingkai sesaat, yang dibenarkan selepas pensampelan bawah. Untuk rakaman dengan gerakan rendah, mengurangkan nilai ini membolehkan pensampelan bawah yang lebih besar dan urutan yang lebih panjang; gerakan sangat pantas mungkin memerlukan nilai lebih tinggi, walaupun lalai sesuai untuk kebanyakan video. Pensampelan bawah automatik menggunakan ambang ini untuk mencari faktor terendah yang mengekalkan perincian. |
| `interpolator_model` |  | enum (string) | no | `film` | `rife`, `film` | Pilihan model interpolasi bingkai: sama ada 'rife' atau 'film'. |
| `transparency_mode` |  | enum (string) | no | `content_aware` | `content_aware`, `white`, `black` | Pengendalian ketelusan untuk bingkai mula dan akhir, menentukan cara kawasan lutsinar diisi. |
| `return_frames_zip` |  | boolean | no | `false` |  | Mengawal sama ada arkib ZIP yang mengandungi setiap bingkai yang dijana turut dikembalikan; didayakan apabila true. |

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.ru/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.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-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.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-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.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-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.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, width, height, fps, duration, num_frames} | Fail video yang dihasilkan oleh penjanaan. |
| `prompt` | string | Prompt yang digunakan untuk menjana output. |
| `seed` | integer | Nilai seed yang digunakan semasa penjanaan. |
| `frames_zip` | object {url, content_type, file_name, file_size} \| null | Arkib ZIP yang mengandungi setiap bingkai video, dikembalikan apabila diminta. |

## 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.ru/v1/models/wan-vace-14b