# Ltx 2.3 Quality · Reference Video to Video API

> 由提示词驱动、以参考视频为引导的生成，支持可选首帧、中间帧和末帧关键帧图像

根据必需的 `prompt` 和提供运动与结构的参考 `video_url` 创建新视频。可选的 `image_url`、`mid_image_url` 和 `end_image_url` 用于固定开头、中间和结尾的外观。`video_strength` 和 `strength`（均为 0 至 1）控制对源视频的跟随或保留程度，`control_video_url` 可提供预计算的控制信号。`resolution` 提供 auto 或固定预设，例如方形以及 16:9 竖屏或横屏。

- Model id: `ltx-2.3-quality/reference-video-to-video`
- Made by: Lightricks
- Category: Video to Video
- Output: video
- Price per megapixel of your output video: $0.00241 / megapixel of output video (cheapest run $0.003 (3 API credits))
- Run: `POST https://api.doitong.ru/v1/run/ltx-2.3-quality/reference-video-to-video`
- Quote: `POST https://api.doitong.ru/v1/quote/ltx-2.3-quality/reference-video-to-video`
- Docs page: https://doitong.com/zh/developers/models/ltx-2.3-quality/reference-video-to-video

## Pricing

Price: **$0.00241 / 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 $0.27 = 270 API credits (112 MP output video × $0.002408).

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-quality/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 |  |  | 用于引导生成的提示词。 |
| `video_url` | `video` | string (video URL) | yes |  |  | 指向用于引导运动和结构的参考视频的 URL。 |
| `control_video_url` |  | string (video URL) \| null | no |  |  | 可选的预计算控制视频；与 `skip_control_preprocess` 一起提供时，会替代内置控制估计。重新采样以匹配输出尺寸和帧数后，它会成为直接控制信号。例如，该视频可以包含已渲染的深度、边缘或姿态合成结果。 |
| `skip_control_preprocess` |  | boolean | no | `false` |  | 使用 `control_video_url` 的直接控制模式，而不是在内部估计深度、边缘或姿态；未提供该 URL 时，此设置会被忽略。此模式下的输出尺寸遵循显式尺寸，并按 64 对齐，以保持 RGB 视频与控制视频匹配；`auto` 则在 LTX 限制内采用源视频尺寸和宽高比。 |
| `preserve_original_video` |  | boolean | no | `false` |  | 原始视频保留模式，仅在同时使用 `skip_control_preprocess`、`video_url` 和 `control_video_url` 时可用。默认禁用，不会改变标准控制处理；启用后会从 `video_url` 开始生成，同时保留 `control_video_url` 的结构引导。通过 `strength` 设置去噪程度，即保留量；较低的值会保留更多原始像素。 |
| `image_url` | `image` | string (image URL) \| null | no |  |  | 可选的图像锚定样式或角色身份，作为第一帧关键帧。 |
| `mid_image_url` |  | string (image URL) \| null | no |  |  | 可选的图像锚定外观，位于片段中点附近，用于补充初始 `image_url` 关键帧。它有助于使外观跟随摄像机运动而不是漂移；需要 `image_url`。 |
| `end_image_url` | `end_image` | string (image URL) \| null | no |  |  | 可选的图像锚定外观，位于片段最后一帧。当摄像机运动结束位置不同于起始图像时很有用；需要 `image_url`。 |
| `video_strength` |  | number | no | `0.6` | 0 – 1 | 此条件强度控制参考视频中运动和结构的可修改程度：较小的值允许更大的变化。 |
| `strength` |  | number | no | `1` | 0 – 1 | 参考视频转视频采样的去噪控制，其效果取决于 `preserve_original_video`。该模式关闭时，它只会缩短去噪调度；开启时，它控制源像素的变换，1.0 会全部重新生成，较低的值会保留更多内容（例如，0.5 大约保留 50%）。 |
| `num_frames` |  | integer | no | `121` | 9 – 481 | 输出帧数，受基于分辨率乘以帧数的 IC-LoRA 稳定性预算限制。422 响应表示超出该预算：请降低分辨率或 `num_frames`。该预算允许 720p 级尺寸约 150 帧，较小尺寸允许更多帧。 |
| `resolution` |  | object {width, height} \| enum (string) | no | `auto` | `auto`, `square_hd`, `square`, `portrait_4_3`, `portrait_16_9`, `landscape_4_3`, `landscape_16_9` | 输出视频尺寸，也会影响稳定时长：较小尺寸允许更多帧，较大尺寸会降低最大帧数。内置控制估计会使尺寸接近官方控制流程；通过 `skip_control_preprocess` 和 `control_video_url` 进行直接控制时，则遵循显式尺寸并按 64px 对齐。直接控制模式下，`auto` 在 LTX 限制内继承源视频尺寸和宽高比。 |
| `frames_per_second` |  | number | no | `24` | 1 – 60 | 输出视频帧率，以每秒帧数为单位。 |
| `num_inference_steps` |  | integer | no | `15` | 8 – 30 | 设置运行的推理步骤数，最多 30；保持不变时使用 15。 |
| `guidance_scale` |  | number | no | `1` | 1 – 20 | 使用此比例调整 classifier-free guidance；其默认调校兼顾高质量和快速生成。 |
| `generate_audio` |  | boolean | no | `true` |  | 返回 MP4 的音轨开关：关闭时生成仅包含视频的文件，开启时包含音频。 |
| `negative_prompt` |  | string | no | `color distortion, overexposure, static, blurry details, subtitles, style, artwork, painting, frame, still, dim overall tone, worst quality, low quality, JPEG compression artifacts, ugly, mutilated, extra fingers, poorly drawn hands, poorly drawn face, deformed, disfigured, malformed limbs, fused fingers, motionless frame, cluttered background, three legs, crowded background, walking backwards` |  | 指定生成应避免内容的负面提示词。 |
| `seed` |  | integer \| null | no |  |  | 使生成结果可复现的种子。设置为 None 时会随机选择种子。 |
| `enable_prompt_expansion` |  | boolean | no | `true` |  | 控制是否启用提示词扩展。 |
| `enable_safety_checker` |  | boolean | no | `true` |  | 控制是否启用安全检查。 |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | 应用于输出视频的质量预设。 |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | 结果视频的写入模式。 |

File parameters (`video`, `control_video_url`, `image`, `mid_image_url`, `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-quality/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-quality/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-quality/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-quality/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-quality/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": 270,
    "usd": "0.27",
    "charged": 270,
    "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
    },
    "seed": 42,
    "prompt": "string"
  },
  "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} | 模型生成的视频。 |
| `seed` | integer | 生成期间实际使用的种子。 |
| `prompt` | string | 生成提示词，包括使用前应用的任何扩展内容。 |

## Related models

- [Ltx 2.3 Quality · Text to Video](https://doitong.com/developers/models/ltx-2.3-quality/text-to-video.md) (`ltx-2.3-quality/text-to-video`): $0.00241 / megapixel of output video
- [Ltx 2.3 Quality · Text to Video · LoRA](https://doitong.com/developers/models/ltx-2.3-quality/text-to-video/lora.md) (`ltx-2.3-quality/text-to-video/lora`): $0.00271 / megapixel of output video
- [Ltx 2.3 Quality · Image to Video](https://doitong.com/developers/models/ltx-2.3-quality/image-to-video.md) (`ltx-2.3-quality/image-to-video`): $0.00241 / megapixel of output video
- [Ltx 2.3 Quality · Image to Video · LoRA](https://doitong.com/developers/models/ltx-2.3-quality/image-to-video/lora.md) (`ltx-2.3-quality/image-to-video/lora`): $0.00271 / megapixel of output video
- [Ltx 2.3 Quality · Ingredient](https://doitong.com/developers/models/ltx-2.3-quality/ingredient.md) (`ltx-2.3-quality/ingredient`): $0.00241 / megapixel of output video
- [Ltx 2.3 Quality · Clean Plate](https://doitong.com/developers/models/ltx-2.3-quality/clean-plate.md) (`ltx-2.3-quality/clean-plate`): $0.00241 / megapixel of output video
- [Ltx 2.3 Quality · Colorization](https://doitong.com/developers/models/ltx-2.3-quality/colorization.md) (`ltx-2.3-quality/colorization`): $0.00241 / megapixel of output video
- [Ltx 2.3 Quality · Cross Eyed](https://doitong.com/developers/models/ltx-2.3-quality/cross-eyed.md) (`ltx-2.3-quality/cross-eyed`): $0.00241 / megapixel of output video

## Links

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