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Luma Ray 3.2 Video Reframing API

luma /

Luma Ray 3.2 Video Reframing is a fast AI video reframing model that changes an existing video’s aspect ratio and fills the newly exposed canvas from a prompt while preserving the source footage. Ready-to-use REST inference API for aspect ratio conversion, social media resizing, cinematic reframing, video outpainting, creator content, advertising creatives, and professional video editing workflows with simple integration, no coldstarts, and affordable pricing.

video-to-video
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$0.06pro Durchlauf·~16 / $1

Weiter:

BeispieleAlle anzeigen

Outpaint the image to a 3:4 portrait aspect ratio suitable for mobile viewing, naturally extending the surrounding scene while matching the original lighting, perspective, and background details.

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README

Luma Ray 3.2 Video Reframing

Luma Ray 3.2 Video Reframing changes the aspect ratio of an existing video while preserving the original footage. Upload a source clip, choose a target size, and describe what should appear in the newly exposed canvas area.

Why Choose This?

  • Aspect-ratio conversion for existing videos
    Reframe source footage into a new layout without rebuilding the video from scratch.

  • Prompt-guided canvas expansion
    Use a text prompt to describe how the newly exposed area should be filled.

  • Multiple output ratios
    Supports common landscape, portrait, square, and cinematic aspect ratios.

  • Flexible resolution options
    Choose 540p, 720p, or 1080p depending on quality and budget needs.

  • Production-ready workflow
    Useful for social repurposing, vertical edits, widescreen conversion, and creative reframing tasks.

Parameters

ParameterRequiredDescription
videoYesSource video to reframe. The source video must be 30 seconds or less.
promptYesText prompt describing the content to generate in the newly exposed canvas area.
sizeNoTarget aspect ratio: 16:9, 9:16, 1:1, 4:3, 3:4, or 21:9. Default: 16:9.
resolutionNoOutput resolution: 540p, 720p, or 1080p. Default: 540p.

How to Use

  1. Upload your source video — provide the clip you want to reframe.
  2. Write your prompt — describe what should appear in the newly exposed canvas area.
  3. Choose the target size — select the new aspect ratio for the output video.
  4. Choose resolution — use 540p for lower cost, 720p for balanced output, or 1080p for higher quality.
  5. Submit — run the model and download the reframed video.

Example Prompt

Extend the sides with a realistic rainy city street, blurred traffic lights, and soft reflections that match the original nighttime mood.

Pricing

Pricing is based on source video duration and output resolution.

ResolutionPrice per Started Second5s Example10s Example
540p$0.06$0.30$0.60
720p$0.12$0.60$1.20
1080p$0.36$1.80$3.60

Billing Rules

  • Source duration is rounded up to the next whole second
  • Minimum billed duration is 1 second
  • Maximum billed duration is 30 seconds
  • size does not affect pricing
  • Source position is handled automatically and is not exposed in the form

Best Use Cases

  • Vertical conversion — Turn horizontal footage into 9:16 clips for short-form platforms.
  • Social media repurposing — Reframe one source video for multiple channels and formats.
  • Cinematic expansion — Extend footage into wider formats such as 21:9.
  • Creative canvas filling — Add scene-consistent content around the original video.
  • Marketing adaptation — Resize existing ad clips for different placements without reshooting.

Pro Tips

  • Use clear, stable source videos for more consistent reframing results.
  • Keep prompts focused on the newly exposed canvas area, not the original content.
  • Match the prompt to the source scene’s lighting, mood, and environment for more natural results.
  • Start with 540p or 720p when testing, then switch to 1080p for higher-end final delivery.
  • Shorter clips are usually easier to validate before reframing longer source footage.

Notes

  • video and prompt are required.
  • Source videos must be 30 seconds or less.
  • Pricing depends on billed source duration and selected resolution.
  • Better prompts usually improve the realism of the expanded canvas.

Related Models

  • Luma image-to-video workflows — Useful when you want to animate a still image instead of reframing existing footage.
  • Luma text-to-video workflows — Useful when you want to generate a new clip from scratch.
  • Luma video editing workflows — Useful when you want to transform motion or style rather than only change framing.
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Ray 3.2 Video Reframing API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/luma/ray-3.2/video-reframing with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for Ray 3.2 Video Reframing below.

HTTP example
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/luma/ray-3.2/video-reframing" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d '{
    "video": "https://example.com/your-input.mp4",
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "size": "16:9",
    "resolution": "540p"
}'

# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY"

# When status is "completed", read the output from data.outputs[0].
Node.js example
// npm install wavespeed
const WaveSpeed = require('wavespeed');

const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env

const result = await client.run("luma/ray-3.2/video-reframing", {
        "video": "https://example.com/your-input.mp4",
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "size": "16:9",
        "resolution": "540p"
});

console.log(result.outputs[0]); // → URL of the generated output
Python example
# pip install wavespeed
import wavespeed

output = wavespeed.run(
    "luma/ray-3.2/video-reframing",
    {
    "video": "https://example.com/your-input.mp4",
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "size": "16:9",
    "resolution": "540p"
}
)

print(output["outputs"][0])  # → URL of the generated output

Ray 3.2 Video Reframing API — Frequently asked questions

What is the Ray 3.2 Video Reframing API?

Ray 3.2 Video Reframing is a Luma model for video editing, exposed as a REST API on WaveSpeedAI. Luma Ray 3.2 Video Reframing is a fast AI video reframing model that changes an existing video’s aspect ratio and fills the newly exposed canvas from a prompt while preserving the source footage. Ready-to-use REST inference API for aspect ratio conversion, social media resizing, cinematic reframing, video outpainting, creator content, advertising creatives, and professional video editing workflows with simple integration, no coldstarts, and affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Ray 3.2 Video Reframing API?

POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID; poll the prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/luma/luma-ray-3.2-video-reframing.

How much does Ray 3.2 Video Reframing cost per run?

Ray 3.2 Video Reframing starts at $0.060 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.

What inputs does Ray 3.2 Video Reframing accept?

Key inputs: `prompt`, `video`, `resolution`, `size`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/luma/luma-ray-3.2-video-reframing.

How do I get started with the Ray 3.2 Video Reframing API?

Sign up for a free WaveSpeedAI account to claim starter credits, copy your API key from /accesskey, then call the endpoint shown in the API tab of the playground. The playground also auto-generates a code sample in Python, JavaScript, or cURL for the parameters you've set.

Can I use Ray 3.2 Video Reframing outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (Luma). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.