Video-to-Video model

LatentSync

Diffusion‑based sync with strong temporal consistency.

Audio‑conditioned latent diffusion model for lip sync, designed for high‑fidelity results and strong temporal consistency over time.

Best for: Longer clips

Inputs: Video + Audio

Outputs: Video

What this model is best at

Short answer: Audio‑conditioned latent diffusion model for lip sync, designed for high‑fidelity results and strong temporal consistency over time.

Use this workspace to preview the model, compare example output, and start creating with the recommended workflow for this model.

Highlight 1

End‑to‑end audio‑conditioned latent diffusion.

Highlight 2

Temporal consistency enhancements with TREPA.

Highlight 3

Language‑agnostic lip sync.

Video-to-Video

LatentSync workspace

Start from the built-in workflow below, then tune the model inside the standard LipsyncX creation surface.

Photo Parlante Doublage Vidéo Vidéo Longue Animaux et Anime

1. Choisir un visage

Choisir un modèle ou téléchargerGlissez et déposez une vidéo ou une photoou cliquez pour télécharger

2. Model

3. Ajoutez votre audio

clean-male-demo-3s.mp3Prend en charge MP3, WAV et M4A. 30 Mo / 10 min max. Pour une meilleure qualité de lip sync, importez un audio de moins de 1 min.

Aperçu de l'audio téléchargéImportez un nouvel audio pour remplacer cette démo.

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Étape 1/3

Choisir un visage

Suivez l'étape suivante pour continuer à construire votre vidéo.

Est. total10/Solde0

Temps de rendu moyen

7 min

Langues prises en charge

50+

Créateurs intégrés

3 200+

Approuvé par les équipes

StudioBlendAudioNovaCourseWaveMintlyVisionSpark

Long‑form segment

Stable mouth motion across a longer scene.

Original

Synced

Popular use cases

Use case 1

Podcast videos

Maintain sync over time.

Use case 2

Training lessons

Consistency across segments.

Use case 3

Series content

Keep identity stable.

Quick specs

Primary use

High‑fidelity video‑to‑video lip sync

Inputs

Source video + target audio

Output

Synced video

Best strength

Temporal consistency on longer clips

Best practices

Use steady, well‑lit footage for the cleanest temporal consistency.

Keep the face centered to minimize occlusion artifacts.

Match audio cadence to the original pacing.

FAQ

How does it keep frames consistent?

It uses temporal representation alignment (TREPA) to stabilize results across frames.

Is it language‑specific?

No. LatentSync is designed to be language‑agnostic.

What resolution is it optimized for?

The model targets 512×512 output resolution.

Ready to try LatentSync?

Use the built-in workspace to test prompts, compare outputs, and see how this model fits your content workflow.