# Ltx 2.3 Quality · Render to Real API

> Turns 3D, CG or game render footage into a photorealistic video, with selectable intensity

Converts a 3D render supplied as `video_url` into a more realistic look. `intensity` can be light, strong or strong-v2, from gentle to aggressive. An optional `image_url` sets the photoreal first frame, and `enable_detail_refine` adds a second sharpening pass with `detail_refine_strength` from 0.3 to 0.95. The prompt keeps the `3DREAL` trigger, and output is 480p or 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/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 |  |  | URL pointing to a 3D, CG, or game-rendered video for photorealistic conversion. |
| `image_url` | `image` | string (image URL) \| null | no |  |  | Optional image anchor for frame 0, establishing its photorealistic appearance. Without it, only the render guides the result; when supplied, the image becomes the first frame, consistent with the adapter's image-to-video training. |
| `intensity` |  | enum (string) | no | `light` | `light`, `strong`, `strong-v2` | Photorealism transformation level, with `strong-v2` selecting the newest improved adapter for better coherence across scenes, audio, talking characters, and overall quality. For the other options, choose `light` to preserve more source-render appearance and motion, or `strong` for more aggressive changes toward photorealism. |
| `enable_detail_refine` |  | boolean | no | `false` |  | Enables an additional refinement stage to increase sharpness and resolution; disabled by default. Following base generation, a spatial upscaler enlarges the video latent by 2x, then a brief detailer pass refines it using the distilled model. |
| `detail_refine_strength` |  | number | no | `0.75` | 0.3 – 0.95 | Detailer denoising strength, defaulting to 0.75 and applicable only with `enable_detail_refine` enabled. For gentler edits that preserve the base result, use a lower setting; increasing it regenerates detail more extensively but risks greater divergence. |
| `prompt` |  | string | no | `3DREAL.` |  | Text prompt for the desired photorealistic result, written after the prefilled `3DREAL` adapter-activation trigger. Neither clearing the prompt nor enabling prompt expansion removes that trigger; it is always retained. |
| `resolution` |  | enum (string) | no | `720p` | `480p`, `720p` | Choose the output's short-side resolution while retaining the source aspect ratio: 480p gives softer results for clips up to approximately 15 seconds, whereas 720p gives sharper results for up to approximately 6 seconds. Choose 480p for longer clips because the IC-LoRA control path limits resolution multiplied by frame count; requests exceeding that budget are rejected with a clear error. Calculate the output duration as `num_frames` / `frames_per_second`. |
| `num_frames` |  | integer | no | `121` | 9 – 481 | Output frame count, subject to an IC-LoRA budget on resolution multiplied by frames: approximately 6 seconds at 720p or 15 seconds at 480p. Exceeding that budget returns 422; reduce `num_frames` or select 480p. Clip duration in seconds equals `num_frames` / `frames_per_second`. |
| `frames_per_second` |  | number | no | `24` | 1 – 60 | Output video frame rate, measured in frames per second. |
| `num_inference_steps` |  | integer | no | `15` | 8 – 30 | Set how many inference steps to run, up to 30; leaving this unchanged uses 15. |
| `guidance_scale` |  | number | no | `1` | 1 – 20 | Adjust classifier-free guidance using this scale; its default tuning targets both high quality and fast generation. |
| `generate_audio` |  | boolean | no | `true` |  | Audio-track toggle for the returned MP4: off produces a video-only file, and on includes audio. |
| `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` |  | Negative prompt specifying what generation should avoid. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | AI-based enrichment of the generation prompt, disabled by default so your wording passes through unchanged. The output reports the prompt actually used, always retaining `3DREAL`; enabling expansion lets an AI model elaborate the description before generation. |
| `seed` |  | integer \| null | no |  |  | Seed that makes generation reproducible. Setting it to None selects a seed randomly. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Controls whether safety checking is enabled. |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | Quality preset applied to the output video. |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | Write mode for the resulting video. |

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} | Video produced by the model. |
| `seed` | integer | Actual seed applied during generation. |
| `prompt` | string | Generation prompt, including any expansion applied before use. |

## 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