# Lynx API

> Image-to-video zachowujące spójność tożsamości obiektu, z rozdzielczością od 480p do 720p i 9–81 klatkami

Animuje obraz obiektu (`image_url`) zgodnie z tekstowym `prompt`. Zachowanie tożsamości można regulować za pomocą `ip_scale` i `strength` (oba od 0 do 2). Rozdzielczość może wynosić 480p, 580p lub 720p, proporcje 16:9, 9:16 lub 1:1, a `num_frames` mieści się w zakresie od 9 do 81 przy 5–30 klatkach na sekundę. Udostępnia także negatywny prompt, dwa ustawienia sterowania, od 1 do 75 kroków wnioskowania oraz ziarno.

- 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/pl/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 wskazujący obraz obiektu używany do wygenerowania wideo. |
| `prompt` |  | string | yes |  |  | Instrukcje tekstowe sterujące generowaniem wideo. |
| `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` |  | Opisz niepożądaną zawartość wideo w tym negatywnym prompcie, aby odsunąć od niej generowanie. |
| `num_inference_steps` |  | integer | no | `50` | 1 – 75 | Liczba kroków próbkowania; większa liczba oznacza dłuższe przetwarzanie, ale lepszą jakość. |
| `seed` |  | integer \| null | no |  |  | Ziarno zapewniające powtarzalność generowania. Ustawienie None wybiera ziarno losowo. |
| `resolution` |  | enum (string) | no | `720p` | `480p`, `580p`, `720p` | Rozdzielczość wynikowego wideo, wybierana spośród 480p, 580p lub 720p. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `16:9`, `9:16`, `1:1` | Proporcje wynikowego wideo, wybierane spośród 16:9, 9:16 lub 1:1. |
| `ip_scale` |  | number | no | `1` | 0 – 2 | Określ, jak wiernie wideo ma zachować tożsamość osoby lub obiektu przedstawionego na obrazie referencyjnym. |
| `strength` |  | number | no | `1` | 0 – 2 | Dostosuj, w jakim stopniu wygenerowane wideo korzysta z obrazu referencyjnego, ustawiając jego skalę. |
| `frames_per_second` |  | integer | no | `16` | 5 – 30 | Liczba klatek wynikowego wideo na sekundę, ograniczona do zakresu od 5 do 30. |
| `guidance_scale` |  | number | no | `5` | 1 – 20 | Siła sterowania bez klasyfikatora, poświęcająca potencjalną jakość na rzecz dokładniejszego dopasowania do promptu wraz ze wzrostem skali. |
| `guidance_scale_2` |  | number | no | `2` | 0 – 10 | Skala sterowania obrazem przy generowaniu wideo, równoważąca zgodność z obrazem referencyjnym i jakość: zwiększenie skali sprzyja dokładniejszemu dopasowaniu, ale może obniżyć jakość. |
| `num_frames` |  | integer | no | `81` | 9 – 81 | Liczba klatek wynikowego wideo, ograniczona do zakresu od 9 do 100. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Filtrowanie można złagodzić, ustawiając false, jeśli wywołujący ma odpowiednie uprawnienia. |

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} | Wynikowy plik wideo. |
| `seed` | integer | Wartość ziarna używana podczas generowania. |

## 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