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

> 사용자 지정 LoRA, 선택적 역재생 및 turbo 모드를 지원하는 Wan 2.1 이미지-투-비디오

`prompt`로 입력 이미지(`image_url`)를 애니메이션화하고 `loras`를 통해 사용자 지정 LoRA 가중치를 적용합니다. `reverse_video`로 클립을 역방향 재생하고 `turbo_mode`로 더 빠르게 생성할 수 있습니다. 해상도는 480p 또는 720p, `num_frames`는 81~100, 프레임 속도는 5~24, 화면 비율은 auto, 16:9, 9:16 또는 1:1입니다.

- Model id: `wan-i2v-lora`
- Made by: Alibaba
- Category: Image to Video
- Output: video
- Price: $0.75 / video (cheapest run $0.75 (750 API credits))
- Run: `POST https://api.doitong.ru/v1/run/wan-i2v-lora`
- Quote: `POST https://api.doitong.ru/v1/quote/wan-i2v-lora`
- Docs page: https://doitong.com/ko/developers/models/wan-i2v-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.ru/v1/quote/wan-i2v-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

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 |  |  | 동영상 생성을 안내하는 텍스트 지침입니다. |
| `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` |  | 동영상 생성에 적용되는 네거티브 프롬프트입니다. |
| `image_url` | `image` | string (image URL) | yes |  |  | 소스 이미지 URL입니다. 선택한 종횡비에 따라 전처리 필요 여부가 결정되며, 불일치하면 크기 조정 후 중앙 자르기가 수행됩니다. |
| `num_frames` |  | integer \| null | no | `81` | 81 – 100 | 생성할 프레임 수입니다. 81~100을 모두 포함하는 범위입니다. |
| `frames_per_second` |  | integer \| null | no | `16` | 5 – 24 | 생성된 동영상의 초당 프레임 수입니다. 5~24 범위입니다. |
| `seed` |  | integer \| null | no |  |  | 생성을 재현 가능하게 하는 시드입니다. None으로 설정하면 무작위로 선택됩니다. |
| `resolution` |  | enum (string) | no | `720p` | `480p`, `720p` | 출력 동영상 해상도이며 480p 또는 720p입니다. |
| `num_inference_steps` |  | integer | no | `30` | 2 – 40 | 샘플링 단계 수입니다. 수가 늘어날수록 처리 시간이 길어지는 대신 품질이 향상됩니다. |
| `guide_scale` |  | number | no | `5` | 1 – 10 | 분류기 없는 안내 강도입니다. 스케일이 커질수록 프롬프트 일치도가 높아지는 대신 품질이 저하될 수 있습니다. |
| `shift` |  | number | no | `5` | 1 – 10 | 동영상 생성에 적용되는 시프트 설정입니다. |
| `enable_safety_checker` |  | boolean | no | `false` |  | 안전 검사 스위치입니다. 끔 설정에는 계정 인증이 필요합니다. 인증이 없으면 설정과 관계없이 모든 요청을 검사하며, true는 검사기를 활성화합니다. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | 프롬프트 확장 활성화 여부를 제어합니다. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `auto`, `16:9`, `9:16`, `1:1` | 출력 동영상의 가로세로 비율입니다. |
| `loras` |  | array of object {path, weight_name, scale} | no | `[]` |  | 추론 중 적용할 LoRA 가중치입니다. |
| `loras[].path` |  | string | yes |  |  | URL 또는 경로로 지정하는 LoRA 가중치 위치입니다. |
| `loras[].weight_name` |  | string \| null | no |  |  | LoRA 가중치 이름입니다. Hugging Face 저장소에 safetensors 파일이 1개보다 많을 때만 필요합니다. `path`가 이러한 저장소를 식별할 때만 사용됩니다. |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | 기본 모델에 병합하기 전에 LoRA 가중치에 적용되는 배수입니다. |
| `reverse_video` |  | boolean | no | `false` |  | 동영상 반전 전환입니다. true이면 재생 방향을 반대로 바꿉니다. |
| `turbo_mode` |  | boolean | no | `true` |  | 더 빠른 동영상 생성 전환입니다. 활성화하면 눈에 띄는 시각적 품질 저하 없이 생성 시간이 줄어듭니다. |

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-i2v-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",
    "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-i2v-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",
    "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-i2v-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.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-i2v-lora",
      "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-i2v-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",
    "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
    },
    "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} | 생성으로 만들어진 동영상 파일입니다. |
| `seed` | integer | 생성 중 적용되는 시드 값입니다. |

## Related models

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

## Links

- HTML page: https://doitong.com/developers/models/wan-i2v-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-i2v-lora
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/wan-i2v-lora