# LTX 2.5 Reframe

> LTX 2.5 Reframe adapts existing video to a new aspect ratio by generating missing frame content. It supports five aspect ratios, 720p and 1080p output, and source placement controls for fitting and positioning the original video.


## Overview

- **Endpoint**: `https://fal.run/lightricks/ltx-2.5/reframe`
- **Model ID**: `lightricks/ltx-2.5/reframe`
- **Category**: video-to-video
- **Kind**: inference
**Tags**: reframe, outpainting, aspect-ratio, vfx



## Pricing

Billing is calculated per second of input video, based on the output resolution: **$0.10** at **720p** and **$0.20** at **1080p**. A **5-second** input costs **$0.50** at **720p** or **$1.00** at **1080p**.

For more details, see [fal.ai pricing](https://fal.ai/pricing).

## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.


### Input Schema

The API accepts the following input parameters:


- **`video_url`** (`string`, _required_):
  URL of the source video.

- **`enable_safety_checker`** (`boolean`, _optional_):
   Default value: `true`
  - Default: `true`

- **`aspect_ratio`** (`AspectRatioEnum`, _optional_):
   Default value: `"16:9"`
  - Default: `"16:9"`
  - Options: `"1:1"`, `"4:5"`, `"5:4"`, `"9:16"`, `"16:9"`

- **`resolution`** (`ResolutionEnum`, _optional_):
  Output tier or explicit frame dimensions. Explicit WxH dimensions must agree with aspect_ratio when both are explicitly provided. Default value: `"1080p"`
  - Default: `"1080p"`
  - Options: `"720p"`, `"1080p"`, `"720x720"`, `"1080x1080"`, `"720x900"`, `"1080x1350"`, `"900x720"`, `"1350x1080"`, `"720x1280"`, `"1080x1920"`, `"1280x720"`, `"1920x1080"`

- **`placement`** (`LTX25ReframeAnchor | LTX25ReframeRectangle`, _optional_):
  Source placement. Omit to center at the largest size that fits. Rectangles preserve source aspect ratio, must fit in the frame, and cannot enlarge the source more than 2x.
  - One of: LTX25ReframeAnchor | LTX25ReframeRectangle



**Required Parameters Example**:

```json
{
  "video_url": ""
}
```

**Full Example**:

```json
{
  "video_url": "",
  "enable_safety_checker": true,
  "aspect_ratio": "16:9",
  "resolution": "1080p"
}
```


### Output Schema

The API returns the following output format:

- **`video`** (`VideoFile`, _required_):
  The reframed video file
  - Examples: {"content_type":"video/mp4","file_name":"ltxv-2-3-reframe-output.mp4","url":"https://v3b.fal.media/files/b/0a90e00f/xvl9SlF6b7a8327wKJDvm_JW6crfr3.mp4"}



**Example Response**:

```json
{
  "video": {
    "content_type": "video/mp4",
    "file_name": "ltxv-2-3-reframe-output.mp4",
    "url": "https://v3b.fal.media/files/b/0a90e00f/xvl9SlF6b7a8327wKJDvm_JW6crfr3.mp4"
  }
}
```


## Usage Examples

### cURL

```bash
curl --request POST \
  --url https://fal.run/lightricks/ltx-2.5/reframe \
  --header "Authorization: Key $FAL_KEY" \
  --header "Content-Type: application/json" \
  --data '{
     "video_url": ""
   }'
```

### Python

Ensure you have the Python client installed:

```bash
pip install fal-client
```

Then use the API client to make requests:

```python
import fal_client

def on_queue_update(update):
    if isinstance(update, fal_client.InProgress):
        for log in update.logs:
           print(log["message"])

result = fal_client.subscribe(
    "lightricks/ltx-2.5/reframe",
    arguments={
        "video_url": ""
    },
    with_logs=True,
    on_queue_update=on_queue_update,
)
print(result)
```

### JavaScript

Ensure you have the JavaScript client installed:

```bash
npm install --save @fal-ai/client
```

Then use the API client to make requests:

```javascript
import { fal } from "@fal-ai/client";

const result = await fal.subscribe("lightricks/ltx-2.5/reframe", {
  input: {
    video_url: ""
  },
  logs: true,
  onQueueUpdate: (update) => {
    if (update.status === "IN_PROGRESS") {
      update.logs.map((log) => log.message).forEach(console.log);
    }
  },
});
console.log(result.data);
console.log(result.requestId);
```


## Deploy your own model

To run your own weights, a fine-tune or a custom pipeline on the GPUs that serve this API, deploy it on fal Serverless. GPUs from H100 (80GB) to B300 (288GB), billed per second; an H100 is $4.50/h list, as low as $2.49/h. Prices, GPU specs and deploy steps: [fal Serverless](https://fal.ai/serverless.md).

## Additional Resources

### Documentation

- [Model Playground](https://fal.ai/models/lightricks/ltx-2.5/reframe)
- [API Documentation](https://fal.ai/models/lightricks/ltx-2.5/reframe/api)
- [OpenAPI Schema](https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=lightricks/ltx-2.5/reframe)

### fal.ai Platform

- [Platform Documentation](https://fal.ai/docs/documentation)
- [Python Client](https://fal.ai/docs/api-reference/client-libraries/python)
- [JavaScript Client](https://fal.ai/docs/api-reference/client-libraries/javascript)

### Other agent-readable surfaces

This file covers one model. To find anything else:

- [Platform overview](https://fal.ai/llms.txt): Entry points and representative endpoint IDs
- [Documentation index](https://fal.ai/docs/llms.txt): Every documentation page
- [Full documentation text](https://fal.ai/docs/llms-full.txt): The whole documentation inlined
- [Pricing](https://fal.ai/pricing.md): Model API and Serverless GPU prices
- [fal Serverless](https://fal.ai/serverless.md): Deploy your own models: GPU prices, specs and steps
- Any other model: `https://fal.ai/models/<endpoint-id>/llms.txt`