LongCat Avatar

Introduction to LongCat Avatar

LongCat Avatar is an advanced audio-driven video generation model designed for long-duration video creation with ultra-realistic lip synchronization, natural human dynamics, and identity consistency. Built on the LongCat-Video architecture, it enables creators to generate professional-grade avatar videos that maintain visual fidelity across infinite-length sequences without quality loss. Whether for podcasts, interviews, corporate presentations, or multi-person conversations, LongCat Avatar delivers expressive, lifelike avatars that remain consistent from start to finish.

The model supports multiple generation modes including Audio-Text-to-Video (AT2V), Audio-Text-Image-to-Video (ATI2V), and audio-conditioned video continuation. It uses innovative techniques such as Cross-Chunk Latent Stitching to prevent pixel degradation and Reference Skip Attention to preserve character identity without copy-paste artifacts. This makes it ideal for use in entertainment, education, marketing, and virtual human platforms.

Takeaways

• State-of-the-art audio-driven video generation with identity consistency
• Supports long-form and infinite-length video sequences
• Offers multiple generation modes: AT2V, ATI2V, and video continuation
• Prevents quality degradation through Cross-Chunk Latent Stitching
• Maintains natural motion and gestures even during silent segments
• Natively supports multi-person interactions
• Open-source with MIT License
• Designed for production-ready deployment

How LongCat Avatar Works

LongCat Avatar operates by taking an audio input (such as speech, music, or podcast) and optionally a reference image or text description. It then generates a video using a combination of audio processing, motion modeling, and identity preservation techniques. The model decouples speech from body motion using Disentangled Unconditional Guidance, allowing for natural gestures and idle movements even when no audio is present. Cross-Chunk Latent Stitching ensures that video quality remains consistent over long durations, while Reference Skip Attention prevents rigid, unrealistic appearances.

The process involves three main steps: uploading audio and reference, configuring generation settings, and generating the final video. Users can choose resolution, video length, and whether to include multi-person support. The result is a high-quality, realistic avatar video that maintains visual consistency and expressive motion throughout.

Core Benefits and Applications

LongCat Avatar is particularly valuable for users who need long-form content without quality loss, such as educational institutions, media companies, and SaaS platforms.