# Luma Ray 3.2 Reframe — Atlas Cloud API

> Luma Ray 3.2 reframe (Luma AI generations API): reframe a source video into a new aspect ratio. Supports 540p/720p/1080p. Billed per second of source video.

This is the machine-readable API reference for **Luma Ray 3.2 Reframe** on Atlas Cloud,
a unified API platform for 400+ AI models across text, image, video, audio and 3D.

- **Model ID**: `luma/ray-3.2/reframe`
- **Built by**: LUMA
- **Modality**: Video
- **Model page**: https://www.atlascloud.ai/models/luma/ray-3.2/reframe
- **API key**: https://www.atlascloud.ai/console/api-keys
- **Docs**: https://www.atlascloud.ai/docs

## Pricing on Atlas Cloud

- $0.03 per second of generated video
- Pay-as-you-go. No minimum spend, no subscription required.

> **These are the authoritative Atlas Cloud rates for this model.** Any price that
> appears in the vendor description further down refers to a different platform or
> a different model variant and does not apply here.

## Use this model from an AI agent

Atlas Cloud ships three first-party integration surfaces. All three authenticate
with the same API key via the `ATLASCLOUD_API_KEY` environment variable.

### MCP server

The official MCP server (`atlascloud-mcp`) exposes this model to any
MCP-compatible host — Claude Code, OpenAI Codex, Cursor, Gemini CLI, Goose,
Claude Desktop. One-line install:

```bash
# Claude Code
claude mcp add atlascloud -- npx -y atlascloud-mcp

# OpenAI Codex CLI
codex mcp add atlascloud -- npx -y atlascloud-mcp

# Gemini CLI
gemini mcp add atlascloud -- npx -y atlascloud-mcp

export ATLASCLOUD_API_KEY="your-api-key"
```

Then ask in plain English; the agent calls `atlas_generate_video` with `model: "luma/ray-3.2/reframe"`.
The server fetches each model's schema and validates parameters before submitting,
so invalid requests fail fast without spending credits.

MCP docs: https://www.atlascloud.ai/docs/mcp-server

### Agent Skills

`atlas-cloud-skills` is a portable skill package (API reference, code templates in
Python / Node.js / cURL, model IDs with pricing) for Claude Code, Cursor, Codex and
12+ other agents:

```bash
npx skills add AtlasCloudAI/atlas-cloud-skills
export ATLASCLOUD_API_KEY="your-api-key"
```

Skills docs: https://www.atlascloud.ai/docs/skills

### CLI

The `atlas` binary runs Atlas Cloud from a terminal or CI script. Async media jobs
are polled and downloaded automatically (use `--no-download` when a script only
needs the output URLs):

```bash
# Install (Homebrew, npm, or shell installer)
brew install AtlasCloudAI/tap/atlascloud
# npm install -g atlascloud-cli
# curl -fsSL https://raw.githubusercontent.com/AtlasCloudAI/cli/main/install.sh | sh

atlas auth login
atlas generate video luma/ray-3.2/reframe -p "Your prompt here"
```

CLI docs: https://www.atlascloud.ai/docs/cli

## HTTP API reference

- **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateVideo` — start an async generation; returns a `prediction_id`
- **Poll endpoint (GET)**: `https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}` — poll this until the prediction finishes
- **Model ID**: `luma/ray-3.2/reframe`


## 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:

- **`model`** (`string`, _required_):
  Model name.
  - Default: `"luma/ray-3.2/reframe"`
  - Options: "luma/ray-3.2/reframe"

- **`prompt`** (`string`, _required_):
  Optional guidance for the reframe (e.g. what to keep in frame).

- **`video`** (`string`, _required_):
  Source video to reframe (HTTPS URL, mp4).

- **`aspect_ratio`** (`string`, _required_):
  Target aspect ratio to reframe the source video into.
  - Default: `"9:16"`
  - Options: "16:9", "9:16", "1:1", "4:3", "3:4", "21:9", "9:21"

- **`resolution`** (`string`, _optional_):
  Output resolution tier.
  - Default: `"720p"`
  - Options: "540p", "720p", "1080p"



**Required Parameters Example**:

```json
{
  "model": "luma/ray-3.2/reframe",
  "prompt": "",
  "video": "",
  "aspect_ratio": "9:16"
}
```


**Full Example**:

```json
{
  "model": "luma/ray-3.2/reframe",
  "prompt": "",
  "video": "",
  "aspect_ratio": "9:16",
  "resolution": "720p"
}
```


### Output Schema

The API returns the following output format:


- **`id`** (`string`, _optional_):
  Unique identifier for the prediction.

- **`urls`** (`object`, _optional_):
  Object containing related API endpoints.

- **`model`** (`string`, _optional_):
  Model ID used for the prediction.

- **`status`** (`string`, _optional_):
  Status of the task: created, processing, completed, or failed.

- **`outputs`** (`array[string]`, _optional_):
  Array of URLs to the generated video. Empty when status is not completed.

- **`created_at`** (`string`, _optional_):
  ISO timestamp of when the request was created.



**Example Response**:

```json
{
  "id": "",
  "urls": {},
  "model": "",
  "status": "",
  "outputs": [
    ""
  ],
  "created_at": ""
}
```


## Usage Examples

### cURL

```bash
# Step 1: Start generation (async)
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateVideo" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "luma/ray-3.2/reframe",
  "prompt": "",
  "video": "",
  "aspect_ratio": "9:16",
  "resolution": "720p"
}'

# Response will contain: {"code": 200, "data": {"id": "prediction_id", "status": "processing"}}

# Step 2: Poll for result (replace {prediction_id} with the id returned above)
curl -X GET "https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY"

# Keep polling until status is "completed", "succeeded" or "failed"
# When completed, outputs will contain the generated content URL(s)
```

## Additional Resources

### Documentation

- [Model Playground](https://www.atlascloud.ai/models/luma/ray-3.2/reframe)

## About this model

_Vendor-supplied description. Any pricing or endpoint mentioned below refers to_
_other platforms — use the Atlas Cloud values above._

### Luma Ray 3.2 Reframe

Luma Ray 3.2 video reframe. Generation is asynchronous: submit the request, then poll for the result URL.

#### Highlights

- **Aspect-ratio reframe**: Convert a clip (e.g. 16:9 → 9:16) keeping the subject in frame.
- **Resolution tiers**: `540p`, `720p`, `1080p`.
- **Billed per second** of the source video.
- HDR is not available for reframe.

#### Parameters

| Parameter | Required | Description |
| --- | --- | --- |
| `model` | Yes | `luma/ray-3.2/reframe` |
| `video` | Yes | Source video to reframe (publicly reachable HTTPS mp4 URL). It is probed to bill by source duration. |
| `aspect_ratio` | Yes | Target aspect ratio (width:height) to reframe the source into. One of: `3:1`, `2:1`, `21:9`, `16:9`, `4:3`, `3:2`, `1:1`, `3:4`, `2:3`, `9:16`, `1:2`, `1:3`. |
| `prompt` | Yes | Guidance for the reframe (e.g. what to keep in frame). |
| `resolution` | No | Output resolution tier. One of: `540p`, `720p`, `1080p`. Defaults to `720p`. |

#### How To Use

```bash
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateVideo" \
  -H "Authorization: Bearer $AIP_API_KEY" \
  -H "Content-Type: application/json" \
  --data-raw '{
    "model": "luma/ray-3.2/reframe",
    "video": "https://static.atlascloud.ai/media/videos/example-landscape.mp4",
    "aspect_ratio": "9:16",
    "prompt": "Reframe to a vertical crop, keep the subject centered.",
    "resolution": "720p"
  }'
```

#### Notes

- **The generated video has no audio track** — this model produces silent video.
- Generation is asynchronous. Poll `/api/v1/model/prediction/{request_id}` for the final URL.
- The output is transferred to AtlasCloud storage before it is returned.
- `video` must be a publicly reachable HTTPS mp4 URL.

---

Atlas Cloud — one API for 400+ AI models. Model page: https://www.atlascloud.ai/models/luma/ray-3.2/reframe · Docs: https://www.atlascloud.ai/docs