# Wan VACE 14B API

> Generel VACE 14B-videomodel: vælg en opgave (dybdekort, positur, inpainting, outpainting, reframe) med mange valgfri input

En alsidig videogenerator og editor, der vælges via `task`: dybdekort, positur, inpainting, outpainting eller reframe. Input omfatter en kilde-`video_url`, maskevideo eller -billede, `ref_image_urls` samt URL'er til første og sidste frame. `num_frames` går fra 17 til 241, og `resolution` fra 240p til 720p. Samplere med unipc, dpm++ og euler kan vælges.

- 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/da/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 |  |  | Tekstinstruktioner, der styrer videogenerering. |
| `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` |  | Negativ prompt anvendt ved generering af en video. |
| `match_input_num_frames` |  | boolean | no | `false` |  | Kilde til den genererede videos frameantal: false bruger `num_frames`, mens true kopierer inputvideoens frameantal. |
| `num_frames` |  | integer | no | `81` | 17 – 241 | Output-frameantal med et inklusivt interval på 81–241. |
| `match_input_frames_per_second` |  | boolean | no | `false` |  | Kilde til den genererede videos billedhastighed: false bruger `frames_per_second`, mens true kopierer inputvideoens billedhastighed. |
| `frames_per_second` |  | integer \| null | no | `16` | 5 – 30 | Genereret videos billedhastighed, kun anvendt når `match_input_frames_per_second` ikke er true; accepterede værdier er 5–30 frames per sekund. |
| `task` |  | enum (string) | no | `depth` | `depth`, `pose`, `inpainting`, `outpainting`, `reframe` | Typen af opgave, som modellen udfører. |
| `seed` |  | integer \| null | no |  |  | Seed, der gør genereringen reproducerbar. Indstilling til None vælger en seed tilfældigt. |
| `resolution` |  | enum (string) | no | `auto` | `auto`, `240p`, `360p`, `480p`, `580p`, `720p` | Opløsning for outputvideoen. |
| `aspect_ratio` |  | enum (string) | no | `auto` | `auto`, `16:9`, `1:1`, `9:16` | Højde-bredde-forhold for den resulterende video. |
| `num_inference_steps` |  | integer | no | `30` | 2 – 50 | Antal samplingstrin, hvor længere behandlingstid byttes for bedre kvalitet, når antallet øges. |
| `guidance_scale` |  | number | no | `5` | 1 – 10 | Styrke for prompttilpasning via classifier-free guidance; en øget skala får de genererede billeder til at følge teksten tættere. |
| `sampler` |  | enum (string) | no | `unipc` | `unipc`, `dpm++`, `euler` | Sampler anvendt ved generering af video. |
| `shift` |  | number | no | `5` | 1 – 15 | Shift-indstilling anvendt ved generering af video. |
| `video_url` | `video` | string (video URL) \| null | no |  |  | Videoreference til modellen, angivet som en URL til kildefilen, når den leveres. |
| `mask_video_url` |  | string (video URL) \| null | no |  |  | Maskereference til modellen, angivet som en URL til kildefilen, når den leveres. |
| `mask_image_url` |  | string (image URL) \| null | no |  |  | Styrende maske angivet via fil-URL, som har forrang frem for video-URL'en til masken, når den er til stede. Modellen bruger denne maske til at styre oprettelsen af maskeret video. |
| `ref_image_urls` |  | array of image URL | no |  |  | Valgfrie URL'er til kildebilleder, der giver modellen referencebilleder at bruge. |
| `first_frame_url` | `image` | string \| null | no |  |  | Valgfri første-frame-reference leveret via URL, som modellen skal bruge ved behandling af videoen. |
| `last_frame_url` | `end_image` | string \| null | no |  |  | Valgfri sidste-frame-reference leveret via URL, som modellen skal bruge ved behandling af videoen. |
| `enable_safety_checker` |  | boolean | no | `false` |  | Sikkerhedskontrol, hvis deaktivering kræver kontogodkendelse. Uden denne godkendelse kontrolleres alle anmodninger uanset indstillingen; true aktiverer kontrollen. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | Styrer, om promptudvidelse er aktiveret. |
| `preprocess` |  | boolean | no | `false` |  | Styrer forbehandlingen af inputvideoen. |
| `acceleration` |  | enum (string) \| null | no | `regular` | `none`, `low`, `regular` | Indstilling for inferensacceleration med valget 'none' eller 'regular': accelereret behandling giver en betydelig hastighedsforbedring på bekostning af en meget lille ændring i outputtet. |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | Kvalitetsniveau for den resulterende video. |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | Skrivetilstand for den resulterende video. |
| `num_interpolated_frames` |  | integer | no | `0` | 0 – 5 | Antal interpolationer: 0 lader de oprindelige frames være uinterpolerede; andre værdier angiver, hvor mange mellemliggende frames der skal genereres mellem dem. |
| `temporal_downsample_factor` |  | integer | no | `0` | 0 – 5 | Videos frame-springfaktor angivet som et heltal med automatisk opsampling én gang for hver nedsamplingsfaktor. Brug 0 for at deaktivere temporal nedsampling. |
| `enable_auto_downsample` |  | boolean | no | `false` |  | Automatisk tilpasning af frameantal: aktivering lader modellen behandle en temporalt nedsamplet video af passende længde, hvorefter interpolation gendanner det oprindelige frameantal. |
| `auto_downsample_min_fps` |  | number | no | `15` | 1 – 60 | Minimum frame rate i frames per sekund, der er tilladt efter downsampling. For optagelser med lav bevægelse giver en reduktion af denne værdi større downsampling og længere sekvenser; meget hurtige bevægelser kan kræve en højere værdi, selvom standarden passer til de fleste videoer. Automatisk downsampling bruger denne tærskel til at finde den laveste faktor, der bevarer detaljerne. |
| `interpolator_model` |  | enum (string) | no | `film` | `rife`, `film` | Valg af frame-interpolationsmodel: enten 'rife' eller 'film'. |
| `transparency_mode` |  | enum (string) | no | `content_aware` | `content_aware`, `white`, `black` | Transparenshåndtering for start- og slutframes, som bestemmer, hvordan deres transparente områder udfyldes. |
| `return_frames_zip` |  | boolean | no | `false` |  | Styrer, om et ZIP-arkiv med alle genererede frames også returneres; aktiveret når 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.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} | Videofil produceret ved generering. |
| `prompt` | string | Prompten, der blev brugt til at generere outputtet. |
| `seed` | integer | Seed-værdi anvendt under generering. |
| `frames_zip` | object {url, content_type, file_name, file_size} \| null | ZIP-arkiv med alle videoframes, returneret når det anmodes om det. |

## 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