# Lynx API

> 피사체의 정체성을 일관되게 유지하는 이미지-동영상 변환, 480p~720p 및 9~81프레임

텍스트 `prompt`에 따라 대상 이미지(`image_url`)를 애니메이션화합니다. `ip_scale` 및 `strength`(둘 다 0에서 2 사이)로 정체성 보존을 조정할 수 있습니다. 해상도는 480p, 580p 또는 720p, 종횡비는 16:9, 9:16 또는 1:1을 지원하며, `num_frames`는 초당 5에서 30 프레임으로 9에서 81까지 설정 가능합니다. 또한 부정 프롬프트, 두 개의 가이던스 스케일, 1~75 추론 단계 및 시드를 제공합니다.

- Model id: `bytedance/lynx`
- Made by: ByteDance
- Category: Image to Video
- Output: video
- Price per second of your output video: $0.60 / second of output video (cheapest run $0.60 (600 API credits))
- Run: `POST https://api.doitong.com/v1/run/bytedance/lynx`
- Quote: `POST https://api.doitong.com/v1/quote/bytedance/lynx`
- Docs page: https://doitong.com/ko/developers/models/bytedance/lynx

## Pricing

Price: **$0.60 / second of output video**. 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.

The full example input below costs $3.038 = 3038 API credits (5.0625 s output video × $0.60).

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/bytedance/lynx` 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 |
|---|---|---|---|---|---|---|
| `image_url` | `image` | string (image URL) | yes |  |  | 동영상 생성에 사용할 피사체 이미지의 URL입니다. |
| `prompt` |  | string | yes |  |  | 동영상 생성을 지시하는 텍스트 입력입니다. |
| `negative_prompt` |  | string | no | `Bright tones, overexposed, blurred background, static, subtitles, style, works, paintings, images, overall gray, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, misshapen limbs, fused fingers, still picture, messy background, three legs, many people in the background, walking backwards` |  | 이 네거티브 프롬프트에 원하지 않는 동영상 콘텐츠를 설명해 생성을 피하도록 유도합니다. |
| `num_inference_steps` |  | integer | no | `50` | 1 – 75 | 샘플링 단계 수입니다. 수가 늘어날수록 처리 시간이 길어지는 대신 품질이 향상됩니다. |
| `seed` |  | integer \| null | no |  |  | 생성을 재현 가능하게 하는 시드입니다. None으로 설정하면 무작위로 선택됩니다. |
| `resolution` |  | enum (string) | no | `720p` | `480p`, `580p`, `720p` | 480p, 580p 또는 720p 중 선택하는 출력 동영상 해상도입니다. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `16:9`, `9:16`, `1:1` | 16:9, 9:16 또는 1:1 중 선택하는 출력 동영상 가로세로 비율입니다. |
| `ip_scale` |  | number | no | `1` | 0 – 2 | 동영상이 참조 이미지에 묘사된 인물 또는 피사체의 정체성을 얼마나 충실히 유지할지 설정합니다. |
| `strength` |  | number | no | `1` | 0 – 2 | 스케일을 설정하여 생성된 동영상이 참조 이미지를 얼마나 활용할지 조정합니다. |
| `frames_per_second` |  | integer | no | `16` | 5 – 30 | 초당 프레임 수로 나타낸 출력 동영상 프레임 레이트이며 5~30으로 제한됩니다. |
| `guidance_scale` |  | number | no | `5` | 1 – 20 | 분류기 없는 안내 강도입니다. 스케일이 커질수록 프롬프트 일치도가 높아지는 대신 품질이 저하될 수 있습니다. |
| `guidance_scale_2` |  | number | no | `2` | 0 – 10 | 동영상 생성의 이미지 안내 스케일입니다. 참조 이미지 충실도와 품질 사이의 균형을 조정하며, 스케일을 높이면 더 유사해지지만 품질이 낮아질 수 있습니다. |
| `num_frames` |  | integer | no | `81` | 9 – 81 | 출력 동영상 프레임 수이며 9~100으로 제한됩니다. |
| `enable_safety_checker` |  | boolean | no | `true` |  | 호출자에게 권한이 있으면 false로 설정해 검사를 완화할 수 있습니다. |

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
{
  "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

A fuller example:

```json
{
  "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
  "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/bytedance/lynx?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "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/bytedance/lynx?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "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 = {
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "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/bytedance/lynx", 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": "bytedance/lynx",
      "input": {
        "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
        "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": "bytedance/lynx",
  "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": 3038,
    "usd": "3.038",
    "charged": 3038,
    "refunded": 0
  },
  "input": {
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "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
    },
    "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, width, height, fps, duration, num_frames} | 결과 동영상 파일입니다. |
| `seed` | integer | 생성 중 사용하는 시드 값입니다. |

## Related models

- [OmniHuman](https://doitong.com/developers/models/bytedance/omnihuman.md) (`bytedance/omnihuman`): $0.14 / second of input audio
- [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
- [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

## Links

- HTML page: https://doitong.com/developers/models/bytedance/lynx
- 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=bytedance/lynx
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/bytedance/lynx