LongCat-Avatar: Audio-Driven Avatar Video by Meituan
LongCat-Avatar is Meituan's open audio-driven avatar model, turning a single photo plus audio into lip-synchronized video, with 8-step DMD2 distilled inference.
LongCat-Avatar
AvatarAudio-to-VideoLip SyncVideo GenerationMeituan's audio-driven avatar video model, built on the LongCat-Video foundation. It turns one photo plus an audio track into a lip-synchronized talking video, supports Audio-Text-to-Video and Audio-Text-Image-to-Video as well as continuing an existing video, and works with a single audio stream or several. Version 1.5 swaps in a Whisper-Large audio encoder and adds 8-step DMD2 distilled inference.
| Developer | Meituan |
| Release Date | 2026-05 (1.5), 2025-12 (original) |
| Base Model | LongCat-Video |
| License | MIT |
| Capabilities | Audio-text-to-video, audio-text-image-to-video, video continuation |
| Audio Input | Single or multiple audio streams |
| Audio Encoder | Whisper-Large (1.5) |
| Inference | 8-step DMD2 distilled path with a rank-128 distill LoRA |
What is LongCat-Avatar?
LongCat-Avatar is Meituan's open framework for audio-driven human video, built on the LongCat-Video foundation model. Given a single photo and an audio track it produces a talking avatar with lip sync, identity preservation and full-body temporal stability over long clips, and it accepts more than one audio stream for multi-speaker input.
Version 1.5 replaced the original Wav2Vec2 encoder with Whisper-Large, which smooths out lip dynamics, and added an 8-step DMD2 distilled inference path for cheaper serving without losing visual fidelity. The release also generalizes to stylized domains, including anime, animals, multi-person interactions and object handling.
Guides and workflows related to this model series.
Comments
Sign in with GitHub to join the discussion.