# LTX-2.3 22B Distilled · Reference Video to Video · LoRA API

> Pembuatan reference-video terdistilasi dengan LoRA khusus serta opsi preprocessor dan tipe IC LoRA

Menerima `video_url` referensi, `prompt`, dan daftar `loras` yang wajib diisi. `preprocessor` mendukung peta kedalaman, canny, pose, atau none, dan `ic_lora_type` memilih mode IC LoRA. `video_strength` dan `audio_strength` berkisar dari 0 hingga 1, dengan input `audio_url`, `image_url`, dan `end_image_url` opsional.

- Model id: `ltx-2.3-22b/distilled/reference-video-to-video/lora`
- Made by: Lightricks
- Category: Video to Video
- Output: video
- Price per megapixel of your output video: $0.00141 / megapixel of output video (cheapest run $0.002 (2 API credits))
- Run: `POST https://api.doitong.ru/v1/run/ltx-2.3-22b/distilled/reference-video-to-video/lora`
- Quote: `POST https://api.doitong.ru/v1/quote/ltx-2.3-22b/distilled/reference-video-to-video/lora`
- Docs page: https://doitong.com/id/developers/models/ltx-2.3-22b/distilled/reference-video-to-video/lora

## Pricing

Price: **$0.00141 / megapixel of output video**. Price per megapixel 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 $0.397 = 397 API credits (282 MP output video × $0.001405).

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/ltx-2.3-22b/distilled/reference-video-to-video/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 |  |  | Prompt yang digunakan sebagai dasar pembuatan video. |
| `video_url` | `video` | string (video URL) | yes |  |  | URL yang mengidentifikasi video referensi. |
| `audio_url` | `audio` | string (audio URL) \| null | no |  |  | URL audio opsional yang menyediakan trek audio video. Jika dihilangkan, audio dari video sumber digunakan jika tersedia. |
| `image_url` | `image` | string (image URL) \| null | no |  |  | URL gambar opsional yang menentukan bingkai pembuka video. |
| `end_image_url` | `end_image` | string (image URL) \| null | no |  |  | URL gambar yang menentukan bingkai penutup video. |
| `match_video_length` |  | boolean | no | `true` |  | Mode pemilihan jumlah bingkai: dinonaktifkan menggunakan `num_frames`, sedangkan diaktifkan menghitung jumlahnya menggunakan FPS dan durasi video. |
| `num_frames` |  | integer | no | `121` | 9 – 481 | Jumlah bingkai untuk output yang dibuat. |
| `video_size` |  | object {width, height} \| enum (string) | no | `auto` | `auto`, `square_hd`, `square`, `portrait_4_3`, `portrait_16_9`, `landscape_4_3`, `landscape_16_9` | Dimensi video yang dihasilkan. |
| `generate_audio` |  | boolean | no | `true` |  | Mengontrol apakah video menyertakan audio yang dihasilkan. |
| `use_multiscale` |  | boolean | no | `true` |  | Sakelar pembuatan multiskala untuk meningkatkan koherensi dan detail. Dengan True, video awal yang lebih kecil memandu pembuatan kedua yang ukurannya memenuhi atau melebihi dimensi yang diminta. |
| `match_input_fps` |  | boolean | no | `true` |  | Penggantian laju bingkai output yang mengganti FPS target bawaan dengan FPS video sumber saat diaktifkan. |
| `fps` |  | number | no | `24` | 1 – 60 | Bingkai rate video output, diukur dalam bingkai per detik. |
| `scheduler` |  | enum (string) | no | `ltx2` | `ltx2`, `linear_quadratic`, `beta` | Pemilihan scheduler. |
| `acceleration` |  | enum (string) | no | `none` | `none`, `regular`, `high`, `full` | Tingkat akselerasi yang diterapkan pada pemrosesan. |
| `camera_lora` |  | enum (string) | no | `none` | `dolly_in`, `dolly_out`, `dolly_left`, `dolly_right`, `jib_up`, `jib_down`, `static`, `none` | Pemilihan Camera LoRA untuk mengontrol gerakan pada video yang dibuat dengan lebih presisi daripada prompt gerakan kamera saja. |
| `camera_lora_scale` |  | number | no | `1` | 0 – 1 | Kekuatan Camera LoRA untuk mengontrol gerakan pada video yang dibuat dengan lebih presisi daripada prompt gerakan kamera saja. |
| `negative_prompt` |  | string | no | `news broadcast, 3d animation, computer graphics, pc game, console game, video game, cartoon, childish, watermark, logo, text, on screen text, subtitles, titles, signature, slowmo, static` |  | Prompt negatif yang digunakan selama pembuatan video. |
| `seed` |  | integer \| null | no |  |  | Nilai seed yang menginisialisasi pembuatan angka acak. |
| `enable_prompt_expansion` |  | boolean | no | `true` |  | Mengontrol apakah perluasan prompt diaktifkan. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Mengontrol apakah pemeriksaan keamanan diaktifkan. |
| `video_output_type` |  | enum (string) | no | `X264 (.mp4)` | `X264 (.mp4)`, `VP9 (.webm)`, `PRORES4444 (.mov)`, `GIF (.gif)` | Jenis output untuk video yang dihasilkan. |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | Tingkat kualitas untuk video yang dihasilkan. |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | Mode penulisan untuk video yang dihasilkan. |
| `loras` |  | array of object {path, weight_name, scale} | yes |  |  | Pemilihan LoRA untuk pembuatan. |
| `loras[].path` |  | string | yes |  |  | Lokasi bobot LoRA, yang diberikan sebagai URL atau ID repositori HuggingFace dalam format owner/repo. |
| `loras[].weight_name` |  | string \| null | no |  |  | Nama bobot LoRA untuk memilih di antara beberapa bobot dalam repositori HuggingFace; hanya repositori yang berisi beberapa bobot yang memerlukannya. Pengaturan ini tidak berpengaruh kecuali `path` mengidentifikasi repositori HuggingFace. |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | Faktor penskalaan yang diterapkan pada LoRA, dengan rentang 0.0 hingga 4.0. |
| `distill_lora_second_pass_scale` |  | number | no | `0.5` | 0 – 1 | Mengontrol penskalaan distill LoRA untuk setiap pass setelah yang pertama. |
| `video_strength` |  | number | no | `1` | 0 – 1 | Kebebasan mengubah konten video dikontrol oleh kekuatan conditioning ini: pengaturan yang lebih kecil memberi model keleluasaan lebih besar. |
| `audio_strength` |  | number | no | `1` | 0 – 1 | Kebebasan mengubah konten audio dikontrol oleh kekuatan conditioning ini: pengaturan yang lebih kecil memberi model keleluasaan lebih besar. |
| `preprocessor` |  | enum (string) | no | `none` | `depth`, `canny`, `pose`, `none` | Praprosesor yang diterapkan selama pembuatan. |
| `ic_lora_type` |  | enum (string) | no | `union` | `match_preprocessor`, `union`, `detailer`, `none` | Varian IC LoRA yang diterapkan selama pembuatan. |

File parameters (`video`, `audio`, `image`, `end_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
{
  "loras": [
    {
      "path": "https://example.com/your-file.safetensors"
    }
  ],
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
  "video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
}
```

A fuller example:

```json
{
  "loras": [
    {
      "path": "https://example.com/your-file.safetensors"
    }
  ],
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
  "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
}
```

## 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/ltx-2.3-22b/distilled/reference-video-to-video/lora?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "loras": [
      {
        "path": "https://example.com/your-file.safetensors"
      }
    ],
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
    "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
  }'

# 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/ltx-2.3-22b/distilled/reference-video-to-video/lora?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "loras": [
      {
        "path": "https://example.com/your-file.safetensors"
      }
    ],
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
    "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
  }),
});
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 = {
    "loras": [
        {
            "path": "https://example.com/your-file.safetensors",
        },
    ],
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
    "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/ltx-2.3-22b/distilled/reference-video-to-video/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": "ltx-2.3-22b/distilled/reference-video-to-video/lora",
      "input": {
        "loras": [
          {
            "path": "https://example.com/your-file.safetensors"
          }
        ],
        "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
        "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
      },
      "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": "ltx-2.3-22b/distilled/reference-video-to-video/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": 397,
    "usd": "0.397",
    "charged": 397,
    "refunded": 0
  },
  "input": {
    "loras": [
      {
        "path": "https://example.com/your-file.safetensors"
      }
    ],
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
    "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
  },
  "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,
    "prompt": "black-and-white video, a cowboy walks through a dusty town, film grain"
  },
  "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} | Video yang dihasilkan model. |
| `seed` | integer | Nilai seed yang digunakan untuk menginisialisasi pembuatan angka acak. |
| `prompt` | string | Prompt yang digunakan untuk memandu pembuatan. |

## Related models

- [LTX-2.3 22B Distilled · Text to Video](https://doitong.com/developers/models/ltx-2.3-22b/distilled/text-to-video.md) (`ltx-2.3-22b/distilled/text-to-video`): $0.00121 / megapixel of output video
- [LTX-2.3 22B Distilled · Text to Video · LoRA](https://doitong.com/developers/models/ltx-2.3-22b/distilled/text-to-video/lora.md) (`ltx-2.3-22b/distilled/text-to-video/lora`): $0.00141 / megapixel of output video
- [LTX-2.3 22B Distilled · Image to Video](https://doitong.com/developers/models/ltx-2.3-22b/distilled/image-to-video.md) (`ltx-2.3-22b/distilled/image-to-video`): $0.00121 / megapixel of output video
- [LTX-2.3 22B Distilled · Image to Video · LoRA](https://doitong.com/developers/models/ltx-2.3-22b/distilled/image-to-video/lora.md) (`ltx-2.3-22b/distilled/image-to-video/lora`): $0.00141 / megapixel of output video
- [LTX-2.3 22B Distilled · Reference Video to Video](https://doitong.com/developers/models/ltx-2.3-22b/distilled/reference-video-to-video.md) (`ltx-2.3-22b/distilled/reference-video-to-video`): $0.00121 / megapixel of output video
- [LTX-2.3 22B Distilled · Video to Video](https://doitong.com/developers/models/ltx-2.3-22b/distilled/video-to-video.md) (`ltx-2.3-22b/distilled/video-to-video`): $0.00121 / megapixel of output video
- [LTX-2.3 22B Distilled · Video to Video · LoRA](https://doitong.com/developers/models/ltx-2.3-22b/distilled/video-to-video/lora.md) (`ltx-2.3-22b/distilled/video-to-video/lora`): $0.00141 / megapixel of output video
- [LTX-2.3 22B Distilled · Audio to Video](https://doitong.com/developers/models/ltx-2.3-22b/distilled/audio-to-video.md) (`ltx-2.3-22b/distilled/audio-to-video`): $0.00121 / megapixel of output video

## Links

- HTML page: https://doitong.com/developers/models/ltx-2.3-22b/distilled/reference-video-to-video/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=ltx-2.3-22b/distilled/reference-video-to-video/lora
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/ltx-2.3-22b/distilled/reference-video-to-video/lora