# Ltx 2.3 Quality · Render to Real API

> 将 3D、CG 或游戏渲染素材转换为逼真视频，并可选择转换强度

将通过 `video_url` 提供的 3D 渲染转换为更逼真的画面。`intensity` 可设为 light、strong 或 strong-v2，强度从柔和到激进。可选的 `image_url` 设置逼真的首帧，`enable_detail_refine` 会使用 `detail_refine_strength`（0.3 到 0.95）增加第二次锐化处理。提示词保留 `3DREAL` 触发词，输出为 480p 或 720p。

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

## Pricing

Price: **from $0.00241 / megapixel of output video** (the lowest tier; the quote prices your exact input). 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.

Price by tier:

- base rate: $0.00241 / megapixel of output video
- detail refine: $0.00963 / megapixel of output video

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.com/v1/quote/ltx-2.3-quality/render-to-real` 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 |
|---|---|---|---|---|---|---|
| `video_url` | `video` | string (video URL) | yes |  |  | 指向 3D、CG 或游戏渲染视频的 URL，用于转换为照片级真实效果。 |
| `image_url` | `image` | string (image URL) \| null | no |  |  | 可选的第 0 帧图像锚点，用于确定照片级真实感外观。未提供时，只有渲染结果会引导输出；提供后，该图像会成为第一帧，符合适配器的图像转视频训练方式。 |
| `intensity` |  | enum (string) | no | `light` | `light`, `strong`, `strong-v2` | 照片级真实感转换级别，其中 `strong-v2` 会选择最新改进的适配器，以提升场景、音频、说话角色和整体质量的一致性。其他选项中，选择 `light` 可保留更多源渲染外观和运动，选择 `strong` 则会更激进地转向照片级真实感。 |
| `enable_detail_refine` |  | boolean | no | `false` |  | 启用额外的细化阶段以提高清晰度和分辨率；默认禁用。基础生成完成后，空间放大器会将视频潜变量放大 2x，然后使用蒸馏模型通过短暂的细节增强阶段进行细化。 |
| `detail_refine_strength` |  | number | no | `0.75` | 0.3 – 0.95 | 细节增强去噪强度，默认值为 0.75，仅在启用 `enable_detail_refine` 时适用。要进行更温和且保留基础结果的编辑，请使用较低值；提高该值会更大程度地重新生成细节，但也可能产生更大偏差。 |
| `prompt` |  | string | no | `3DREAL.` |  | 所需照片级真实感结果的文本提示词，写在预填充的 `3DREAL` 适配器激活触发词之后。清空提示词或启用提示词扩展都不会移除该触发词；它始终会保留。 |
| `resolution` |  | enum (string) | no | `720p` | `480p`, `720p` | 在保留源宽高比的同时选择输出短边分辨率：480p 对最长约 15 秒的片段生成较柔和的结果，720p 对最长约 6 秒的片段生成更清晰的结果。较长片段请选择 480p，因为 IC-LoRA 控制路径限制分辨率与帧数的乘积；超过该预算的请求会返回明确错误。使用 `num_frames` / `frames_per_second` 计算输出时长。 |
| `num_frames` |  | integer | no | `121` | 9 – 481 | 输出帧数，受 IC-LoRA 的分辨率与帧数乘积预算限制：720p 约 6 秒，480p 约 15 秒。超过预算时返回 422；请减少 `num_frames` 或选择 480p。片段时长（秒）等于 `num_frames` / `frames_per_second`。 |
| `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。 |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | 基于 AI 的生成提示词增强，默认禁用，因此你的措辞会原样传递。输出会报告实际使用的提示词，并始终保留 `3DREAL`；启用扩展后，AI 模型会在生成前扩展描述。 |
| `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_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`, `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
{
  "video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
}
```

A fuller example:

```json
{
  "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.com/v1/run/ltx-2.3-quality/render-to-real?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "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.com/v1/requests/REQUEST_ID?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY"
```

### JavaScript

```javascript
const API = "https://api.doitong.com/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/render-to-real?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "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.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}

payload = {
    "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/render-to-real", 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.com/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/render-to-real",
      "input": {
        "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/render-to-real",
  "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": {
    "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.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.com/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/render-to-real
- 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/render-to-real
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/ltx-2.3-quality/render-to-real