StableAvatar
End-to-end video diffusion transformer for infinite-length audio-driven avatars.
Synthesize high-quality avatar videos from an image and audio without post-processing.
StableAvatar is an end-to-end video diffusion transformer that generates infinite-length, identity-preserving avatar videos conditioned on a reference image and audio. It suits video producers and researchers seeking realistic lip-sync and motion without face-swapping tools.
What it is
It synthesizes long avatar videos by integrating a Time-step-aware Audio Adapter and an Audio Native Guidance Mechanism to prevent latent distribution error accumulation. A Dynamic Weighted Sliding-window Strategy fuses latent over time to maintain smoothness across video clips.
Who it's for
Suits audio-visual producers and researchers who need custom avatar generation with precise audio synchronization. It does not suit casual users lacking technical hardware or those unfamiliar with Python and model weight management.
Key features
Time-step-aware Audio Adapter
Prevents latent distribution error accumulation across video clips via time-step-aware modulation.
Audio Native Guidance Mechanism
Enhances audio synchronization using the diffusion model's own joint audio-latent prediction.
Dynamic Weighted Sliding-window
Fuses latent over time to enhance the smoothness of infinite-length video outputs.
Vocal Separation Tooling
Separates vocals from audio files using ONNX models to improve lip synchronization performance.
Up and running in 3 steps
Our honest verdict
What's great
- Generates infinite-length avatar videos without requiring post-processing face restoration models
- Includes built-in audio extraction and vocal separation utilities to improve lip sync
- Supports ComfyUI integration for faster 10-step generation workflows
- Provides full fine-tuning and LoRA training code for custom model adaptation
Where it falls short
- Requires significant local GPU resources, hardware setup, and manual model checkpoint downloads
- Hugging Face public demo is restricted to Pro users due to long video generation times
- Audio-native guidance inference code is still pending implementation in the repository
Pricing & license
Free under its MIT license. The only cost is running it yourself on your own hardware, as there is no hosted SaaS platform provided by the authors beyond a Hugging Face space demo.
Open remote AI-training roles
768 open remote AI-training roles, updated November 14, 2026; most pay $20–$175 an hour. Zekai lists them free; the application goes to the employer’s platform.
Alternatives
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FAQ
What hardware is required to run StableAvatar?
It requires a powerful NVIDIA GPU with appropriate CUDA support, such as Blackwell series chips or cards supporting PyTorch 2.6.0 with adequate VRAM.
Does StableAvatar need post-processing tools like GFP-GAN?
No, the model is designed to synthesize high-quality videos directly without face-swapping or face restoration tools.
How are background noises handled in the audio?
The repository includes a vocal separation script utilizing an ONNX model to isolate vocals and minimize negative impacts from background music.
