# Wan-2.1 Text-to-Video with LoRAs API

> Wan 2.1 text-to-video mat Ënnerstëtzung fir personaliséiert LoRA-Gewiichter, Turbo-Modus an optionaler Ëmdréiung

Generéiert e Video aus engem Text-`prompt` a benotzt personaliséiert LoRAen, déi an `loras` opgezielt sinn. D'Opléisung ass 480p, 580p oder 720p, mat engem Bildverhältnis vun 16:9 oder 9:16. `num_frames` geet vun 81 bis 100 an `frames_per_second` vun 5 bis 24. `turbo_mode` ass standardméisseg aktiv, an `reverse_video` spillt d'Resultat réckleefeg of.

- Model id: `wan-t2v-lora`
- Made by: Alibaba
- Category: Text to Video
- Output: video
- Price: $0.75 / video (cheapest run $0.75 (750 API credits))
- Run: `POST https://api.doitong.com/v1/run/wan-t2v-lora`
- Quote: `POST https://api.doitong.com/v1/quote/wan-t2v-lora`
- Docs page: https://doitong.com/lb/developers/models/wan-t2v-lora

## Pricing

Price: **$0.75 / video**. Billed once per generated video.

The full example input below costs $0.75 = 750 API credits (1 video × 750 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.com/v1/quote/wan-t2v-lora` 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 |  |  | Textinstruktiounen, déi d'Video-Generatioun steieren. |
| `negative_prompt` |  | string | no | `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` |  | Negative Prompt bei der Generatioun vun engem Video. |
| `num_frames` |  | integer \| null | no | `81` | 81 – 100 | Framezuel fir d'Generatioun, vun 81 bis inklusiv 100. |
| `frames_per_second` |  | integer \| null | no | `16` | 5 – 24 | Frame-Rate vum generéierte Video a Frames pro Sekonn, vun 5 bis 24. |
| `seed` |  | integer \| null | no |  |  | Seed, deen d'Generatioun reproduzéierbar mécht. Wann et op None gesat gëtt, gëtt e Seed zoufälleg gewielt. |
| `resolution` |  | enum (string) | no | `480p` | `480p`, `580p`, `720p` | Opléisung vum Output-Video: 480p, 580p oder 720p. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `9:16`, `16:9` | Aspektverhältnis vum Output-Video, entweder 16:9 oder 9:16. |
| `num_inference_steps` |  | integer | no | `30` | 2 – 40 | Unzuel vun de Sampling-Schrëtt; méi Schrëtt bedeite méi laang Veraarbechtung, awer besser Qualitéit. |
| `enable_safety_checker` |  | boolean | no | `false` |  | Sécherheetskontrollschalter, deem seng ausgeschalt Astellung d'Autorisatioun vum Kont erfuerdert. Ouni dës Autorisatioun gëtt all Ufro onofhängeg vun der Astellung kontrolléiert; true aktivéiert d'Kontroll. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | Steiert, ob d'Prompt-Erweiderung aktivéiert ass. |
| `turbo_mode` |  | boolean | no | `true` |  | Schalter fir méi séier Video-Generatioun. D'Aktivéierung verkierzt d'Generatiounszäit ouni bemierkbare Verloscht u visueller Qualitéit. |
| `loras` |  | array of object {path, weight_name, scale} | no | `[]` |  | LoRA-Gewiichter, déi während der Inferenz applizéiert ginn. |
| `loras[].path` |  | string | yes |  |  | Plaz vun de LoRA-Gewiichter, uginn als URL oder Pad. |
| `loras[].weight_name` |  | string \| null | no |  |  | LoRA-Gewiichtsnumm, nëmmen erfuerderlech, wann e Hugging Face Repository méi wéi 1 safetensors-Datei enthält. Dësen Numm gëtt nëmme benotzt, wann `path` esou e Repository identifizéiert. |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | Multiplikator, deen op d'LoRA-Gewiicht applizéiert gëtt, ier et an de Basismodell zesummegefouert gëtt. |
| `reverse_video` |  | boolean | no | `false` |  | Video-Reverséierungs-Schalter; true dréint d'Ofspillung ëm. |

## 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-t2v-lora?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-t2v-lora?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-t2v-lora", 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-t2v-lora",
      "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-t2v-lora",
  "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": 750,
    "usd": "0.75",
    "charged": 750,
    "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
    },
    "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.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} | Video-Datei, déi duerch d'Generatioun erstallt gouf. |
| `seed` | integer | Seed-Wäert, deen während der Generatioun applizéiert gouf. |

## Related models

- [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
- [MiniMax H3 Text to Video](https://doitong.com/developers/models/minimax/h3/text-to-video.md) (`minimax/h3/text-to-video`): from $0.05 / second
- [Seedance 2.0 Fast Text to Video](https://doitong.com/developers/models/bytedance/seedance-2.0/fast/text-to-video.md) (`bytedance/seedance-2.0/fast/text-to-video`): from $0.113 / second
- [Seedance 2.0 Text to Video](https://doitong.com/developers/models/bytedance/seedance-2.0/text-to-video.md) (`bytedance/seedance-2.0/text-to-video`): from $0.141 / second

## Links

- HTML page: https://doitong.com/developers/models/wan-t2v-lora
- 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-t2v-lora
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/wan-t2v-lora