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VEED Lipsync V2 generates production-quality lip-synced videos from a source video and a replacement audio track, matching mouth movements to the new audio for dubbing, localization, creator content, and talking-video workflows. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

digital-human
Input

Idle

$0.075per run·~13 / $1

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VEED Lipsync V2

VEED Lipsync V2 generates production-quality lip-synced video from a source video and replacement audio track. Upload a video with a visible speaker, provide the new audio, and the model produces a video where the mouth movement follows the supplied audio.

Why Choose This?

  • Production-quality lipsync Generate natural mouth movement that follows the replacement audio track.

  • Simple video-to-video workflow Provide one source video and one audio file without extra tuning parameters.

  • Audio-driven duration The output video follows the uploaded audio duration.

  • Standard video output The generated video is returned as a URL in the standard WaveSpeed prediction response.

Parameters

ParameterRequiredDescription
videoYesSource video containing the face to be lip-synced.
audioYesAudio track that drives the mouth movement.

How to Use

  1. Upload source video - Provide a video with a clear, visible face.
  2. Upload audio - Provide the replacement audio track.
  3. Submit - Generate the lip-synced video.
  4. Review output - The result is returned as a video URL.

Pricing

Pricing is $0.075 per second of uploaded audio duration, rounded up to the next full second.

Audio DurationPrice
5s$0.375
10s$0.75
30s$2.25
60s$4.50

Best Use Cases

  • Video dubbing - Replace speech while keeping the original speaker video.
  • Localization - Create translated versions of existing presenter videos.
  • Dialogue replacement - Update spoken lines without reshooting footage.
  • Marketing content - Adapt spokesperson videos for different messages.
  • Education and training - Reuse presenter footage with new narration.

Pro Tips

  • Use clear audio with minimal background noise.
  • Use a source video where the mouth is visible and well-lit.
  • Avoid heavy face occlusion or fast camera movement for best results.
  • Match the style and pacing of the audio to the source footage when possible.
  • Ensure both URLs are publicly accessible.
Note:This website uses AI models provided by third parties. Documentation prices are for reference and may be outdated. The Generate button shows an estimate; the final task charge prevails.

Lipsync v2 API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/veed/lipsync-v2 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 Lipsync v2 below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "audio": "https://interactive-examples.mdn.mozilla.net/media/cc0-audio/t-rex-roar.mp3",
    "video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/veed/lipsync-v2" \
  -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/veed/lipsync-v2";
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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "audio": "https://interactive-examples.mdn.mozilla.net/media/cc0-audio/t-rex-roar.mp3",
        "video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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 = {
    "audio": "https://interactive-examples.mdn.mozilla.net/media/cc0-audio/t-rex-roar.mp3",
    "video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4"
}

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/veed/lipsync-v2", 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)

Lipsync v2 API — Frequently asked questions

What is the Lipsync v2 API?

Lipsync v2 is a Veed model for talking-avatar generation, exposed as a REST API on WaveSpeedAI. VEED Lipsync V2 generates production-quality lip-synced videos from a source video and a replacement audio track, matching mouth movements to the new audio for dubbing, localization, creator content, and talking-video workflows. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Lipsync v2 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/veed/veed-lipsync-v2.

How much does Lipsync v2 cost per run?

Lipsync v2 starts at $0.075 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 Lipsync v2 accept?

Key inputs: `video`, `audio`. 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/veed/veed-lipsync-v2.

How long does Lipsync v2 take to generate?

Median end-to-end generation time on WaveSpeedAI is around 47 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 Lipsync v2 outputs commercially?

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

VEED Lipsync V2 Video Lip Sync API on WaveSpeedAI