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

> 从必需的 `loras` 字段应用自定义 LoRA 的蒸馏文生视频

根据 `prompt` 和必需的 `loras` 列表创建视频片段。`video_size` 提供预设形状，`num_frames` 为 9 至 481，`fps` 为 1 至 60。支持可选的音频生成、摄像机 LoRA 和第二遍 distill LoRA 缩放。

- Model id: `ltx-2.3-22b/distilled/text-to-video/lora`
- Made by: Lightricks
- Category: Text 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/text-to-video/lora`
- Quote: `POST https://api.doitong.ru/v1/quote/ltx-2.3-22b/distilled/text-to-video/lora`
- Docs page: https://doitong.com/zh/developers/models/ltx-2.3-22b/distilled/text-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 $0.158 = 158 API credits (112 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/text-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

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `prompt` |  | string | yes |  |  | 作为视频生成基础的提示词。 |
| `num_frames` |  | integer | no | `121` | 9 – 481 | 生成输出的帧数。 |
| `video_size` |  | object {width, height} \| enum (string) | no | `landscape_16_9` | `square_hd`, `square`, `portrait_4_3`, `portrait_16_9`, `landscape_4_3`, `landscape_16_9` | 生成视频的尺寸。 |
| `generate_audio` |  | boolean | no | `true` |  | 控制视频是否包含生成的音频。 |
| `use_multiscale` |  | boolean | no | `true` |  | 用于提升一致性和细节的多尺度生成开关。为 True 时，较小的初始视频会引导第二次生成，第二次生成的尺寸达到或超过请求尺寸。 |
| `fps` |  | number | no | `24` | 1 – 60 | 输出视频帧率，以每秒帧数表示。 |
| `scheduler` |  | enum (string) | no | `ltx2` | `ltx2`, `linear_quadratic`, `beta` | 调度器选择。 |
| `acceleration` |  | enum (string) | no | `none` | `none`, `regular`, `high`, `full` | 应用于处理的加速级别。 |
| `camera_lora` |  | enum (string) | no | `none` | `dolly_in`, `dolly_out`, `dolly_left`, `dolly_right`, `jib_up`, `jib_down`, `static`, `none` | 摄像机 LoRA 选择，用于比单独使用摄像机运动提示词更精确地控制生成视频中的运动。 |
| `camera_lora_scale` |  | number | no | `1` | 0 – 1 | 摄像机 LoRA 强度，用于比单独使用摄像机运动提示词更精确地控制生成视频中的运动。 |
| `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` |  | 视频生成期间使用的负面提示词。 |
| `seed` |  | integer \| null | no |  |  | 用于初始化随机数生成的种子值。 |
| `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_output_type` |  | enum (string) | no | `X264 (.mp4)` | `X264 (.mp4)`, `VP9 (.webm)`, `PRORES4444 (.mov)`, `GIF (.gif)` | 结果视频的输出类型。 |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | 结果视频的质量级别。 |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | 结果视频的写入模式。 |
| `loras` |  | array of object {path, weight_name, scale} | yes |  |  | 用于生成的 LoRA 选择。 |
| `loras[].path` |  | string | yes |  |  | LoRA 权重位置，以 URL 或 owner/repo 格式的 HuggingFace 仓库 ID 提供。 |
| `loras[].weight_name` |  | string \| null | no |  |  | 用于在 HuggingFace 仓库的多个权重中进行选择的 LoRA 权重名称；仅包含多个权重的仓库需要此项。除非 `path` 标识 HuggingFace 仓库，否则此设置无效。 |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | 应用于 LoRA 的缩放因子，范围为 0.0 到 4.0。 |
| `distill_lora_second_pass_scale` |  | number | no | `0.5` | 0 – 1 | 控制第一轮之后每一轮的 distill LoRA 缩放值。 |

## 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"
}
```

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"
}
```

## 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/text-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"
  }'

# 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/text-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"
  }),
});
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",
}

# 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/text-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/text-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"
      },
      "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/text-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": 158,
    "usd": "0.158",
    "charged": 158,
    "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"
  },
  "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": "A cowboy walking through a dusty town at high noon, camera following from behind, cinematic depth, realistic lighting, western mood, 4K 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} | 模型生成的视频。 |
| `seed` | integer | 用于初始化随机数生成的种子值。 |
| `prompt` | string | 用于引导生成的提示词。 |

## 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 · 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 · Reference Video to Video · LoRA](https://doitong.com/developers/models/ltx-2.3-22b/distilled/reference-video-to-video/lora.md) (`ltx-2.3-22b/distilled/reference-video-to-video/lora`): $0.00141 / 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/text-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/text-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/text-to-video/lora