# Lynx API

> Image-to-Video, dat d'Identitéit vum Sujet konsequent behält, mat 480p bis 720p an 9 bis 81 Frames

Animéiert e Sujetbild (`image_url`) op Basis vun engem Text-`prompt`. D'Identitéitsbeibehale kann mat `ip_scale` a `strength` (béid 0 bis 2) agestallt ginn. D'Opléisung kann 480p, 580p oder 720p sinn, d'Bildformat 16:9, 9:16 oder 1:1, an `num_frames` geet vun 9 bis 81 bei 5 bis 30 Frames pro Sekonn. Et gëtt och en Negativ-Prompt, zwou Guidance-Skalen, 1 bis 75 Inferenz-Schrëtt an e Seed.

- 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.ru/v1/run/bytedance/lynx`
- Quote: `POST https://api.doitong.ru/v1/quote/bytedance/lynx`
- Docs page: https://doitong.com/lb/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.ru/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 |  |  | URL op d'Bild vum Sujet, dat benotzt gëtt, fir de Video ze generéieren. |
| `prompt` |  | string | yes |  |  | Textuweisungen, déi d'Videogeneratioun steieren. |
| `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` |  | Beschreift ongewollte Videoinhalter an dësem negativen Prompt, fir d'Generatioun dovun ewechzesteieren. |
| `num_inference_steps` |  | integer | no | `50` | 1 – 75 | Unzuel vun de Sampling-Schrëtt; méi Schrëtt bedeite méi laang Veraarbechtung, awer besser Qualitéit. |
| `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 | `720p` | `480p`, `580p`, `720p` | Opléisung vum Output-Video, ausgewielt aus 480p, 580p oder 720p. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `16:9`, `9:16`, `1:1` | Aspektverhältnis vum Output-Video, ausgewielt aus 16:9, 9:16 oder 1:1. |
| `ip_scale` |  | number | no | `1` | 0 – 2 | Setzt fest, wéi trei de Video d'Identitéit vun der Persoun oder dem Sujet aus dem Referenzbild behale soll. |
| `strength` |  | number | no | `1` | 0 – 2 | Passt un, wéi staark de generéierte Video op d'Referenzbild zeréckgräift, andeems seng Skala festgeluecht gëtt. |
| `frames_per_second` |  | integer | no | `16` | 5 – 30 | Frame-Taux vum Output-Video a Frames per Sekonn, limitéiert op 5 bis 30. |
| `guidance_scale` |  | number | no | `5` | 1 – 20 | Classifier-free Guidance-Stäerkt; mat steigender Skala gëtt méigleche Qualitéitsverloscht géint eng méi genee Prompt-Entspriechung ofgewiicht. |
| `guidance_scale_2` |  | number | no | `2` | 0 – 10 | Bild-Guidance-Skala fir d'Videogeneratioun, déi d'Treiheet zum Referenzbild géint d'Qualitéit ofwiicht: eng méi héich Skala favoriséiert eng méi genee Iwwereestëmmung, riskéiert awer méi niddreg Qualitéit. |
| `num_frames` |  | integer | no | `81` | 9 – 81 | Frame-Zuel vum Output-Video, limitéiert op 9 bis 100. |
| `enable_safety_checker` |  | boolean | no | `true` |  | D'Kontroll kann duerch false gelackert ginn, wann den Uruffer autoriséiert ass. |

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.ru/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.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/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.ru/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.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": "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.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} | Resultéierend Video-Datei. |
| `seed` | integer | Seed-Wäert, dee während der Generatioun benotzt gëtt. |

## 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.ru/v1/models/bytedance/lynx