LTX-2 Lipsync generates synchronized talking head videos from a reference image and audio input. Powered by the 19B DiT architecture, it produces high-fidelity lip-synced videos with natural head movements. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle
$0.1per run·~10 / $1
bear looks into the camera and begin to talk
A weathered elderly man with a gentle, slightly weary expression sits in a sunlit garden chair, his hands resting loosely in his lap. He wears a faded, button-up shirt and worn trousers, with a subtle smile playing on his lips as he speaks softly, his voice warm and thoughtful. His eyes, lined with age but still bright, look slightly off-camera as if engaged in a candid, unscripted conversation with someone nearby. The background is softly blurred, showing greenery and dappled sunlight, enhancing the natural, relaxed atmosphere. The scene feels intimate and authentic — no forced performance, just the quiet truth of a man sharing his thoughts in a moment of peace.
LTX-2 Lipsync is an audio-driven digital human model that generates synchronized talking head videos from a reference image and audio input. Powered by the 19B-parameter DiT (Diffusion Transformer) architecture, it produces high-fidelity lip-synced videos with natural head movements and expressions.
Audio-driven generation Simply provide an audio file and optional reference image — the model handles lip-sync, head motion, and expressions automatically.
High-fidelity output Leverages the 19B-parameter LTX-2 architecture for detailed, temporally consistent video with natural mouth movements.
Flexible resolution Supports 480p, 720p, and 1080p outputs to balance quality and cost.
Variable duration Video length is automatically determined by audio duration (5-20 seconds max).
| Parameter | Required | Description |
|---|---|---|
| audio | Yes | Audio file URL for lip-sync (determines video length) |
| image | No | Reference portrait image (JPG or PNG) |
| prompt | No | Optional text to guide generation style |
| resolution | No | Output resolution: 480p, 720p (default), or 1080p |
| seed | No | Random seed for reproducibility (-1 for random) |
| Resolution | Best For |
|---|---|
| 480p | Fast previews, iteration, lowest cost |
| 720p | Balanced quality and cost (default) |
| 1080p | Final delivery, maximum detail |
| Resolution | 5s | 10s | 15s | 20s |
|---|---|---|---|---|
| 480p | $0.075 | $0.15 | $0.225 | $0.30 |
| 720p | $0.10 | $0.20 | $0.30 | $0.40 |
| 1080p | $0.15 | $0.30 | $0.45 | $0.60 |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/ltx-2-19b/lipsync 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 Ltx 2 19b Lipsync below.
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/ltx-2-19b/lipsync" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d '{
"audio": "https://example.com/your-audio.mp3",
"image": "https://example.com/your-input.jpg",
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"resolution": "720p",
"seed": -1
}'
# 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].// npm install wavespeed
const WaveSpeed = require('wavespeed');
const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env
const result = await client.run("wavespeed-ai/ltx-2-19b/lipsync", {
"audio": "https://example.com/your-audio.mp3",
"image": "https://example.com/your-input.jpg",
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"resolution": "720p",
"seed": -1
});
console.log(result.outputs[0]); // → URL of the generated output# pip install wavespeed
import wavespeed
output = wavespeed.run(
"wavespeed-ai/ltx-2-19b/lipsync",
{
"audio": "https://example.com/your-audio.mp3",
"image": "https://example.com/your-input.jpg",
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"resolution": "720p",
"seed": -1
}
)
print(output["outputs"][0]) # → URL of the generated outputLtx 2 19b Lipsync is a WaveSpeedAI model for talking-avatar generation, exposed as a REST API on WaveSpeedAI. LTX-2 Lipsync generates synchronized talking head videos from a reference image and audio input. Powered by the 19B DiT architecture, it produces high-fidelity lip-synced videos with natural head movements. 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 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/wavespeed-ai/ltx-2-19b-lipsync.
Ltx 2 19b Lipsync starts at $0.10 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: `prompt`, `image`, `audio`, `resolution`, `seed`. 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/wavespeed-ai/ltx-2-19b-lipsync.
Average end-to-end generation time on WaveSpeedAI is around 87 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.
Commercial usage rights depend on the model's license, set by its provider (WaveSpeedAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.