# Ltx 2.3 Quality · Render to Real API

> 將 3D、CG 或遊戲渲染畫面轉換為寫實影片，並可選擇強度

將 `video_url` 提供的 3D 渲染轉換為更寫實的外觀。`intensity` 可設為 light、strong 或 strong-v2，強度從輕微到激進。可選的 `image_url` 會設定寫實的第一個影格，而 `enable_detail_refine` 會使用 `detail_refine_strength`（0.3 至 0.95）新增第二次銳化處理。提示詞保留 `3DREAL` 觸發詞，輸出為 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.ru/v1/run/ltx-2.3-quality/render-to-real`
- Quote: `POST https://api.doitong.ru/v1/quote/ltx-2.3-quality/render-to-real`
- Docs page: https://doitong.com/zh-TW/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.ru/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 或遊戲渲染影片的 URL，用於轉換成寫實效果。 |
| `image_url` | `image` | string (image URL) \| null | no |  |  | 影格 0 的選用圖像錨點，用於建立其寫實外觀。未提供時，只有渲染結果會引導輸出；提供後，圖像會成為第一個影格，符合轉接器的圖像轉影片訓練方式。 |
| `intensity` |  | enum (string) | no | `light` | `light`, `strong`, `strong-v2` | 寫實轉換程度；`strong-v2` 會選用最新改良轉接器，以提升場景、音訊、說話角色及整體品質的一致性。其他選項中，選擇 `light` 可保留更多來源渲染外觀與動態，選擇 `strong` 則會更積極地轉向寫實效果。 |
| `enable_detail_refine` |  | boolean | no | `false` |  | 啟用額外精修階段以提升銳利度與解析度；預設停用。基礎生成後，空間放大器會將影片潛表示放大 2x，接著由精細化器使用蒸餾模型進行短暫精修。 |
| `detail_refine_strength` |  | number | no | `0.75` | 0.3 – 0.95 | 精細化器去噪強度，預設為 0.75，僅在啟用 `enable_detail_refine` 時適用。若要進行較輕微且保留基礎結果的編輯，請使用較低的值；提高此值會更大幅度地重新生成細節，但也可能造成更大偏差。 |
| `prompt` |  | string | no | `3DREAL.` |  | 所需寫實結果的文字提示詞，寫在預先填入的 `3DREAL` 轉接器啟用觸發詞之後。清除提示詞或啟用提示詞擴展都不會移除該觸發詞；它一定會保留。 |
| `resolution` |  | enum (string) | no | `720p` | `480p`, `720p` | 在保留來源長寬比的情況下選擇短邊解析度：480p 會為最長約 15 秒的片段提供較柔和的結果，720p 則會為最長約 6 秒的片段提供更清晰的結果。較長片段請選擇 480p，因為 IC-LoRA 控制路徑限制解析度乘以影格數；超出該預算的請求會因明確錯誤而遭拒。輸出時長計算方式為 `num_frames` / `frames_per_second`。 |
| `num_frames` |  | integer | no | `121` | 9 – 481 | 輸出影格數，受 IC-LoRA 的解析度乘以影格數預算限制：約為 720p 下 6 秒或 480p 下 15 秒。超出預算會返回 422；請降低 `num_frames` 或選擇 480p。片段時長（秒）等於 `num_frames` / `frames_per_second`。 |
| `frames_per_second` |  | number | no | `24` | 1 – 60 | 輸出影片影格率，以每秒影格數表示。 |
| `num_inference_steps` |  | integer | no | `15` | 8 – 30 | 設定要執行的推論步驟數，最多 30；維持不變時使用 15。 |
| `guidance_scale` |  | number | no | `1` | 1 – 20 | 使用此尺度調整無分類器引導；預設調校同時以高品質和快速生成為目標。 |
| `generate_audio` |  | boolean | no | `true` |  | 返回 MP4 的音訊軌切換：關閉會產生僅含影片的檔案，開啟則包含音訊。 |
| `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` |  | 指定生成應避免內容的負面提示詞。 |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | 以 AI 增強生成提示詞；預設停用，因此你的文字會原樣傳遞。輸出會回報實際使用的提示詞，且一定保留 `3DREAL`；啟用擴展後，AI 模型會在生成前擴寫描述。 |
| `seed` |  | integer \| null | no |  |  | 使生成結果可重現的種子。設為 None 會隨機選擇種子。 |
| `enable_safety_checker` |  | boolean | no | `true` |  | 控制是否啟用安全性檢查。 |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | 套用至輸出影片的品質預設。 |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | 結果影片的寫入模式。 |

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.ru/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.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/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.ru/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.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/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.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} | 模型產生的影片。 |
| `seed` | integer | 生成期間實際套用的種子。 |
| `prompt` | string | 生成提示詞，包括使用前套用的任何擴寫內容。 |

## 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.ru/v1/models/ltx-2.3-quality/render-to-real