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

> Menjana video baharu yang dipandu oleh video rujukan, dengan audio pengganti serta bingkai pertama dan terakhir pilihan

Menerima `prompt` dan rujukan `video_url`. `audio_url` pilihan menggantikan audio; jika diabaikan, audio daripada video input akan digunakan. `image_url` dan `end_image_url` boleh menetapkan bingkai pertama dan terakhir. Dengan `match_video_length` diaktifkan, jumlah bingkai mengikut rujukan; jika tidak, `num_frames` (9 hingga 481) digunakan.

- Model id: `ltx-2.3-22b/reference-video-to-video`
- Made by: Lightricks
- Category: Video to Video
- Output: video
- Price per megapixel of your output video: $0.00161 / megapixel of output video (cheapest run $0.002 (2 API credits))
- Run: `POST https://api.doitong.ru/v1/run/ltx-2.3-22b/reference-video-to-video`
- Quote: `POST https://api.doitong.ru/v1/quote/ltx-2.3-22b/reference-video-to-video`
- Docs page: https://doitong.com/ms/developers/models/ltx-2.3-22b/reference-video-to-video

## Pricing

Price: **$0.00161 / 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 $0.453 = 453 API credits (282 MP output video × $0.001605).

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/reference-video-to-video` 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 asas penjanaan video. |
| `video_url` | `video` | string (video URL) | yes |  |  | URL yang mengenal pasti video rujukan. |
| `audio_url` | `audio` | string (audio URL) \| null | no |  |  | URL audio pilihan yang membekalkan trek audio video. Jika ditinggalkan, audio daripada video sumber digunakan jika tersedia. |
| `image_url` | `image` | string (image URL) \| null | no |  |  | URL imej pilihan yang menentukan bingkai pembukaan video. |
| `end_image_url` | `end_image` | string (image URL) \| null | no |  |  | URL imej yang menentukan bingkai penamat video. |
| `match_video_length` |  | boolean | no | `true` |  | Mod pemilihan jumlah bingkai: dilumpuhkan menggunakan `num_frames`, manakala didayakan mengira jumlah menggunakan FPS dan tempoh video. |
| `num_frames` |  | integer | no | `121` | 9 – 481 | Bilangan bingkai untuk output yang dijana. |
| `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 dijana. |
| `generate_audio` |  | boolean | no | `true` |  | Mengawal sama ada video menyertakan audio yang dijana. |
| `use_multiscale` |  | boolean | no | `true` |  | Togol penjanaan berbilang skala untuk koheren dan perincian yang lebih baik. Dengan True, video awal yang lebih kecil membimbing penjanaan kedua yang saiznya memenuhi atau melebihi dimensi yang diminta. |
| `match_input_fps` |  | boolean | no | `true` |  | Penggantian kadar bingkai output yang menggantikan FPS sasaran lalai dengan FPS video sumber apabila didayakan. |
| `fps` |  | number | no | `24` | 1 – 60 | Kadar bingkai video output, diukur dalam bingkai sesaat. |
| `num_inference_steps` |  | integer | no | `40` | 8 – 50 | Bilangan langkah inferens yang dilakukan. |
| `video_cfg_scale` |  | number | no | `3` | 1 – 20 | Tetapan panduan video: tingkatkannya untuk mendapatkan konsistensi dan fokus yang lebih tinggi dalam kandungan yang dijana. Menggunakan panduan tanpa pengelas (CFG). |
| `video_stg_scale` |  | number | no | `0` | 0 – 20 | Kawalan konsistensi dan fokus video melalui skala Spatiotemporal Guidance (STG); tingkatkan tetapan untuk menguatkan kedua-dua ciri. |
| `video_rescaling_scale` |  | number | no | `0.7` | 0 – 1 | Pelarasan penskalaan semula video untuk mengimbangi panduan tanpa pengelas dengan panduan ruang masa sebagai nisbah. |
| `video_modality_scale` |  | number | no | `3` | 0 – 10 | Pelarasan modaliti video untuk mengimbangi sumbangan video dan audio sebagai nisbah. |
| `audio_cfg_scale` |  | number | no | `7` | 1 – 20 | Tetapan panduan audio: tingkatkannya untuk mendapatkan konsistensi dan fokus yang lebih tinggi dalam kandungan yang dijana. Menggunakan panduan tanpa pengelas (CFG). |
| `audio_stg_scale` |  | number | no | `0` | 0 – 20 | Kawalan konsistensi dan fokus audio melalui skala Spatiotemporal Guidance (STG); tingkatkan tetapan untuk menguatkan kedua-dua ciri. |
| `audio_rescaling_scale` |  | number | no | `0.7` | 0 – 1 | Pelarasan penskalaan semula audio untuk mengimbangi panduan tanpa pengelas dengan panduan ruang masa sebagai nisbah. |
| `audio_modality_scale` |  | number | no | `3` | 0 – 10 | Pelarasan modaliti audio untuk mengimbangi sumbangan video dan audio sebagai nisbah. |
| `gradient_estimation_gamma` |  | number | no | `2` | 0 – 10 | Tetapan anggaran kecerunan nyahhingar: 0 mematikan anggaran; jika tidak, nilai tersebut menentukan gamma. |
| `use_restart_sampling` |  | boolean | no | `false` |  | Togol pensampelan mula semula untuk kualiti video yang berpotensi lebih baik: pendayaan menambah sedikit hingar pada setiap langkah nyahhingar. |
| `scheduler` |  | enum (string) | no | `ltx2` | `ltx2`, `linear_quadratic`, `beta` | Pemilihan penjadual. |
| `acceleration` |  | enum (string) | no | `regular` | `none`, `regular`, `high`, `full` | Tahap pecutan yang digunakan pada pemprosesan. |
| `camera_lora` |  | enum (string) | no | `none` | `dolly_in`, `dolly_out`, `dolly_left`, `dolly_right`, `jib_up`, `jib_down`, `static`, `none` | Pemilihan Camera LoRA untuk mengawal pergerakan dalam video yang dijana dengan lebih tepat berbanding prompt gerakan kamera sahaja. |
| `camera_lora_scale` |  | number | no | `1` | 0 – 1 | Kekuatan Camera LoRA untuk mengawal pergerakan dalam video yang dijana dengan lebih tepat berbanding prompt gerakan kamera sahaja. |
| `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 semasa penjanaan video. |
| `seed` |  | integer \| null | no |  |  | Nilai seed yang memulakan penjanaan nombor rawak. |
| `enable_prompt_expansion` |  | boolean | no | `true` |  | Mengawal sama ada pengembangan prompt didayakan. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Mengawal sama ada pemeriksaan keselamatan didayakan. |
| `video_output_type` |  | enum (string) | no | `X264 (.mp4)` | `X264 (.mp4)`, `VP9 (.webm)`, `PRORES4444 (.mov)`, `GIF (.gif)` | Jenis output untuk video yang terhasil. |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | Tahap kualiti untuk video yang terhasil. |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | Mod penulisan untuk video yang terhasil. |
| `distill_lora_first_pass_scale` |  | number | no | `0.2` | 0 – 1 | Kawal penskalaan LoRA distil pas pertama, menggunakan 0 untuk mematikannya. |
| `distill_lora_second_pass_scale` |  | number | no | `0.5` | 0 – 1 | Kawal penskalaan LoRA distil bagi setiap pas selepas pas pertama. |
| `video_strength` |  | number | no | `1` | 0 – 1 | Kebebasan untuk mengubah kandungan video dikawal oleh kekuatan pengkondisian ini: tetapan yang lebih kecil memberikan model lebih banyak kelonggaran. |
| `audio_strength` |  | number | no | `1` | 0 – 1 | Kebebasan untuk mengubah kandungan audio dikawal oleh kekuatan pengkondisian ini: tetapan yang lebih kecil memberikan model lebih banyak kelonggaran. |
| `preprocessor` |  | enum (string) | no | `none` | `depth`, `canny`, `pose`, `none` | Prapemproses yang digunakan semasa penjanaan. |
| `ic_lora_type` |  | enum (string) | no | `union` | `match_preprocessor`, `union`, `detailer`, `none` | Varian IC LoRA yang digunakan semasa penjanaan. |

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
{
  "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
{
  "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/reference-video-to-video?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",
    "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/reference-video-to-video?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",
    "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 = {
    "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/reference-video-to-video", 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/reference-video-to-video",
      "input": {
        "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/reference-video-to-video",
  "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": 453,
    "usd": "0.453",
    "charged": 453,
    "refunded": 0
  },
  "input": {
    "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 oleh model. |
| `seed` | integer | Nilai seed yang digunakan untuk memulakan penjanaan nombor rawak. |
| `prompt` | string | Prompt yang digunakan untuk membimbing penjanaan. |

## Related models

- [LTX-2.3 22B · Text to Video](https://doitong.com/developers/models/ltx-2.3-22b/text-to-video.md) (`ltx-2.3-22b/text-to-video`): $0.00161 / megapixel of output video
- [LTX-2.3 22B · Text to Video · LoRA](https://doitong.com/developers/models/ltx-2.3-22b/text-to-video/lora.md) (`ltx-2.3-22b/text-to-video/lora`): $0.00181 / megapixel of output video
- [LTX-2.3 22B · Image to Video](https://doitong.com/developers/models/ltx-2.3-22b/image-to-video.md) (`ltx-2.3-22b/image-to-video`): $0.00161 / megapixel of output video
- [LTX-2.3 22B · Image to Video · LoRA](https://doitong.com/developers/models/ltx-2.3-22b/image-to-video/lora.md) (`ltx-2.3-22b/image-to-video/lora`): $0.00181 / megapixel of output video
- [LTX 2.3 22B](https://doitong.com/developers/models/ltx-2.3-22b/reference-video-to-video/lora.md) (`ltx-2.3-22b/reference-video-to-video/lora`): $0.00181 / megapixel of output video
- [LTX-2.3 22B · Extend Video](https://doitong.com/developers/models/ltx-2.3-22b/extend-video.md) (`ltx-2.3-22b/extend-video`): $0.00161 / megapixel of output video
- [LTX-2.3 22B · Extend Video · LoRA](https://doitong.com/developers/models/ltx-2.3-22b/extend-video/lora.md) (`ltx-2.3-22b/extend-video/lora`): $0.00181 / megapixel of output video
- [LTX-2.3 22B · Video to Video](https://doitong.com/developers/models/ltx-2.3-22b/video-to-video.md) (`ltx-2.3-22b/video-to-video`): $0.00161 / megapixel of output video

## Links

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