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Luma Ray 3.2 Video Edit API

luma /

Luma Ray 3.2 Video Edit is a fast AI video-to-video editing model that re-renders an existing source video from a text prompt while preserving the original motion and timing. Ready-to-use REST inference API for video restyling, creative edits, product videos, advertising creatives, social media clips, visual storytelling, and professional video editing workflows with simple integration, no coldstarts, and affordable pricing.

video-to-video
Entrada

Ocioso

$0.72por execução·~13 / $10

Próximo:

ExemplosVer todos

Change the clothe to ballet performance clothing.

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README

Ray 3.2 Video Edit

Ray 3.2 Video Edit transforms an existing source video using a text prompt while preserving the original motion, timing, and scene structure. Upload a clip, describe the visual change you want, and generate an edited video in your selected resolution and duration.

Ray 3.2 Video Edit is ideal for restyling footage, changing visual atmosphere, modifying subjects or environments, and creating polished video variations without rebuilding the entire shot from scratch.

Why Choose This?

  • Motion-preserving video editing
    Edit an existing video while keeping the original motion, pacing, camera movement, and overall timing intact.

  • Prompt-based visual control
    Describe the exact style or change you want — from cinematic lighting and character appearance to environment, mood, material, or art direction.

  • Flexible output resolution
    Choose between 540p, 720p, and 1080p depending on your quality needs, iteration speed, and budget.

  • Short-form video generation
    Generate 5s or 10s outputs, making it suitable for fast creative iteration, social content, product previews, and visual experiments.

  • Simple editing workflow
    Advanced edit controls are handled automatically, so you only need to provide the source video, prompt, and optional output settings.

Parameters

ParameterRequiredDescription
videoYesSource video to edit. Use a clear clip with visible subjects, stable framing, and consistent motion for best results.
start_imageNoOptional starting image used to guide the first frame or initial appearance of the edited video.
promptYesText prompt describing how the source video should be edited. Be specific about style, subject changes, lighting, environment, and mood.
resolutionNoOutput resolution: 540p, 720p, or 1080p. Default: 540p.
durationNoOutput duration: 5s or 10s. Default: 5s.

How to Use

  1. Upload your source video — provide the clip you want to transform.
  2. Write your edit prompt — describe the desired visual change, style, subject details, or atmosphere.
  3. Choose output settings (optional) — select resolution and duration based on your quality and cost requirements.
  4. Submit — generate the edited video while preserving the original motion and timing.

Example Prompts

Cinematic style edit:
Transform the video into a dramatic cyberpunk night scene with neon reflections, cinematic lighting, rain-soaked streets, and a high-contrast film look.

Character or outfit edit:
Keep the same motion and camera angle, but change the person’s outfit into a futuristic white space suit with subtle metallic details.

Environment edit:
Replace the background with a tropical beach at sunset, warm golden lighting, soft ocean waves, and a relaxed cinematic atmosphere.

Pricing

Pricing depends on output resolution and duration.

Duration540p720p1080p
5s$0.72$1.08$2.16
10s$1.44$2.16$4.32

Billing Rules

  • 10s costs 2x the 5s price.
  • 720p costs 1.5x the 540p price.
  • 1080p costs 3x the 540p price.
  • Default configuration: 540p, 5s$0.72.
  • Advanced edit controls are handled automatically and are not shown in the form.

Best Use Cases

  • Creative video restyling — Turn ordinary clips into cinematic, anime, fantasy, sci-fi, watercolor, or branded visual styles.
  • Product and fashion previews — Modify scenes, outfits, materials, or lighting while preserving the original product motion.
  • Social media content — Quickly create stylized video variations for ads, reels, short-form campaigns, and visual experiments.
  • Concept visualization — Explore different moods, environments, or art directions before committing to a full production workflow.
  • Character and scene transformation — Adjust character appearance, backgrounds, props, and atmosphere while maintaining the original shot timing.
  • Fast iteration — Test multiple prompt directions at lower resolution before generating higher-quality outputs.

Pro Tips

  • Use clear source videos with stable framing and visible subjects for more consistent edits.
  • Keep prompts focused on the visual change you want rather than describing too many unrelated edits at once.
  • Mention important elements that should stay the same, such as camera angle, motion, composition, or subject identity.
  • Start with 540p when iterating quickly, then move to 720p or 1080p for final outputs.
  • Use 5s for fast prompt testing and 10s when you need a longer finished clip.
  • For style edits, include concrete visual cues such as lighting, color palette, material, era, camera style, and mood.

Notes

  • video and prompt are required fields.
  • resolution defaults to 540p if not specified.
  • duration defaults to 5s if not specified.
  • Output quality depends on the clarity, stability, and visual consistency of the source video.
  • Prompts should be specific, visual, and focused on the desired edit.
  • Please ensure your uploaded content and generated outputs comply with applicable usage policies.
Nota:Este site utiliza modelos de IA fornecidos por terceiros.

Ray 3.2 Video Edit API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/luma/ray-3.2/video-edit with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Ray 3.2 Video Edit below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "resolution": "540p",
    "duration": "5s"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/luma/ray-3.2/video-edit" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d "$REQUEST_BODY")

TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(printf '%s' "$TASK" | jq -r '.urls.get // empty')
if [ -z "$RESULT_URL" ]; then
  RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
fi

# 2. Poll until the prediction finishes.
while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body "$RESULT_URL" \
    -H "Authorization: Bearer $WAVESPEED_API_KEY")
  RESULT=$(printf '%s' "$RESPONSE" | jq 'if has("data") then .data else . end')
  STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
  case "$STATUS" in
    completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
    failed|cancelled|timeout) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
    created|processing) sleep 2 ;;
    *) printf 'Unexpected status: %s
' "$STATUS" >&2; exit 1 ;;
  esac
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/luma/ray-3.2/video-edit";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');

async function requestJson(url, options = {}) {
  const response = await fetch(url, options);
  if (!response.ok) throw new Error(await response.text());
  return response.json();
}

// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "resolution": "540p",
        "duration": "5s"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;

// 2. Poll until the prediction finishes.
while (true) {
  const resultBody = await requestJson(resultUrl, {
    headers: { "Authorization": `Bearer ${apiKey}` },
  });
  const result = resultBody.data ?? resultBody;
  if (result.status === "completed") {
    console.log(result.outputs);
    break;
  }
  if (["failed", "cancelled", "timeout"].includes(result.status)) throw new Error(JSON.stringify(result));
  if (!["created", "processing"].includes(result.status)) throw new Error("Unexpected status: " + result.status);
  await new Promise(resolve => setTimeout(resolve, 2000));
}
Python example
import json
import os
import time
from urllib.request import Request, urlopen

api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
    "video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "resolution": "540p",
    "duration": "5s"
}

def request_json(url, data=None):
    request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
    with urlopen(request) as response:
        return json.load(response)

# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/luma/ray-3.2/video-edit", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
    raise RuntimeError("Submission response did not contain a prediction id")
result_url = task.get("urls", {}).get("get") or f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"

# 2. Poll until the prediction finishes.
while True:
    result_body = request_json(result_url)
    result = result_body.get("data", result_body)
    status = result.get("status")
    if status == "completed":
        print(result.get("outputs", []))
        break
    if status in {"failed", "cancelled", "timeout"}:
        raise RuntimeError(result)
    if status not in {"created", "processing"}:
        raise RuntimeError(f"Unexpected status: {status}")
    time.sleep(2)

Ray 3.2 Video Edit API — Frequently asked questions

What is the Ray 3.2 Video Edit API?

Ray 3.2 Video Edit is a Luma model for video editing, exposed as a REST API on WaveSpeedAI. Luma Ray 3.2 Video Edit is a fast AI video-to-video editing model that re-renders an existing source video from a text prompt while preserving the original motion and timing. Ready-to-use REST inference API for video restyling, creative edits, product videos, advertising creatives, social media clips, visual storytelling, 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 Edit 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 result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/luma/luma-ray-3.2-video-edit.

How much does Ray 3.2 Video Edit cost per run?

Ray 3.2 Video Edit starts at $0.72 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 Edit accept?

Key inputs: `prompt`, `video`, `resolution`, `duration`, `start_image`. 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-edit.

How long does Ray 3.2 Video Edit take to generate?

Median end-to-end generation time on WaveSpeedAI is around 444 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.

Can I use Ray 3.2 Video Edit 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.

Luma Ray 3.2 Video Edit API | WaveSpeedAI