Soul-AILab/SoulX-FlashHead

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1093 stars · 127 forks observed · 2026-09-29

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

SoulX-FlashHead is a 1.3B-parameter framework for high-fidelity, infinite-length, real-time streaming talking-head portrait video generation driven by audio. It includes inference code, pretrained checkpoints, a Gradio demo, and the 782-hour VividHead training dataset.

Use cases

• generate talking head videos from audio
• real-time streaming digital human avatar
• audio-driven lip sync video generation
• build a real-time virtual presenter
• infinite-length portrait video generation
• low-latency digital human interaction

When to choose

• you need real-time streaming talking-head generation on consumer GPUs
• you want high-fidelity audio-driven portrait video with no identity drift over long sequences
• you need a lightweight model (96 FPS on a single RTX 4090) for digital human applications

When to avoid

• you need full-body or multi-person video generation
• you lack a CUDA GPU, as inference requires NVIDIA hardware
• you need training code, which is not yet fully released

Facets

library · maturity active

video-processing machine-learning deep-learning llm-inference speech-recognition deep-learning artificial-intelligence computer-vision python talking-head-generation digital-human audio-driven-video streaming-inference lip-sync avatar-generation diffusion-distillation comfyui video audio gpu linux docker

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