Generate realistic lip-sync animations from audio using advanced algorithms for high-quality facial synchronization. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Bereit
$0.025pro Durchlauf·~40 / $1
sync/lipsync-1.9.0-beta takes an existing video and a separate audio track, then reanimates the speaker’s mouth so the lips match the new speech. It’s a zero-shot lipsync model from Sync Labs—no training or cloning step required.
video* Required. Input video to be edited (URL or upload). Use a shot with a clearly visible face for best results.
audio* Required. Target speech track (URL or upload, e.g. MP3/WAV). The model will align lip movements to this audio.
sync_mode Controls behavior when video and audio durations differ. Options:
loop
bounce
cut_off
silence
remap
Choose how you want the shorter stream to be treated (looped, trimmed, padded with silence, or time-remapped).
Output: a new video where the speaker’s lips follow the uploaded audio.
Rate: $0.025 per second of processed video.
| Clip length (s) | Price (USD) |
|---|---|
| 5 | $0.13 |
| 10 | $0.25 |
| 20 | $0.50 |
| 30 | $0.75 |
| 60 | $1.50 |
You will only be charged for the actual duration of the input video after upload.
WaveSpeedAI / InfiniteTalk WaveSpeedAI’s single-avatar talking-head model that turns one photo plus audio into smooth, lip-synced digital presenter videos for tutorials, marketing, and social content.
WaveSpeedAI / InfiniteTalk Multi Multi-avatar version of InfiniteTalk that drives several characters in one scene from separate audio tracks, ideal for dialog-style explainers, interviews, and role-play videos.
Kwaivgi / Kling V2 AI Avatar Standard Cost-effective Kling-based AI avatar model that generates natural talking-face videos from a single reference image and voice track, suitable for everyday content and customer support.
Kwaivgi / Kling V2 AI Avatar Pro Higher-fidelity Kling V2 avatar model for premium digital humans, offering smoother motion, better lip-sync, and more stable faces for commercials, brand spokespeople, and product demos.
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/sync/lipsync-1.9.0-beta with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Lipsync 1.9.0 Beta below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
"audio": "https://interactive-examples.mdn.mozilla.net/media/cc0-audio/t-rex-roar.mp3",
"sync_mode": "cut_off"
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/sync/lipsync-1.9.0-beta" \
-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
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/sync/lipsync-1.9.0-beta";
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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
"audio": "https://interactive-examples.mdn.mozilla.net/media/cc0-audio/t-rex-roar.mp3",
"sync_mode": "cut_off"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
`https://api.wavespeed.ai/api/v3/predictions/${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));
}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",
"audio": "https://interactive-examples.mdn.mozilla.net/media/cc0-audio/t-rex-roar.mp3",
"sync_mode": "cut_off"
}
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/sync/lipsync-1.9.0-beta", 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 1.9.0 Beta is a Sync model for talking-avatar generation, exposed as a REST API on WaveSpeedAI. Generate realistic lip-sync animations from audio using advanced algorithms for high-quality facial synchronization. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.
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/sync/sync-lipsync-1.9.0-beta.
Lipsync 1.9.0 Beta starts at $0.025 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.
Key inputs: `video`, `audio`, `sync_mode`. 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/sync/sync-lipsync-1.9.0-beta.
Median end-to-end generation time on WaveSpeedAI is around 275 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.
Commercial usage rights depend on the model's license, set by its provider (Sync). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.