WanGP 5.4: Unlocking High-Quality 15‑Second Audio‑Driven Video with Just 10 GB VRAM 🚀

A new update—WanGP 5.4—has just landed, making audio-driven video generation more accessible than ever. Here’s everything you need to know:

Key points

• WanGP 5.4 now supports Hunyuan Video Avatar and delivers 15-second speech- or song-driven video on just 10 GB of GPU memory, where 80 GB or 32 GB of VRAM had been required.
• WanGP, also known as Wan2GP, provides a web UI that auto-downloads the right model for the user’s hardware and prioritizes video speed and efficiency.
• It supports 20+ video models including Wan, Hunyuan Video models, and LTX Video models, with tooling such as Mask Editor, Prompt Enhancer, temporal and spatial control, LoRA support, and queue-based generation.
• The release builds on Tencent’s open-source HunyuanVideo-Avatar, incorporating TeaCache and a single-GPU mode optimized for 10GB setups.
• HunyuanVideo-Avatar is a multimodal diffusion transformer for emotion-aligned, multi-character audio-to-video generation that uses character image injection, an Audio Emotion Module, and a Face-Aware Audio Adapter.

• 15‑second, speech‑or song‑driven video with low VRAM
  You no longer need 80 GB or 32 GB of VRAM. WanGP 5.4 now supports Hunyuan Video Avatar, delivering rapid 15‑second videos on just 10 GB of GPU memory—without compromising quality (github.com).
• Easy web-based interface
  WanGP (aka Wan2GP) provides an intuitive web UI, auto-downloading the right model for your hardware and prioritizing video speed and efficiency (github.com).
• Support for 20+ video models
  Including Wan, Hunyuan Video models, and LTX Video models. It also features advanced tooling like:
  • Mask Editor
  • Prompt Enhancer
  • Temporal and Spatial control
  • LoRA support
  • Queue-based generation workflow (github.com)
• Gratitude to Tencent/Hunyuan Video team
  WanGP’s latest leap builds on Tencent’s open-source HunyuanVideo‑Avatar, made possible through the incorporation of TeaCache and a single‑GPU mode optimized for 10GB setups (github.com).

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Tech Highlights: Why This Matters

• Low VRAM & fast performance
  Tailored for GPUs with 10 GB VRAM, WanGP 5.4 achieves speed and fidelity without demanding high-end hardware.
• Audio emotion preservation
  Utilizing the HunyuanVideo‑Avatar model, it produces emotionally aligned facial expressions and body motion based solely on audio input (youtube.com, github.com).
• Web-ready accessibility
  No deep CLI knowledge required—just clone the GitHub repo, install dependencies, and run the web UI interface.

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How to Get Started

1. Clone the repo: git clone https://github.com/deepbeepmeep/Wan2GP.git cd Wan2GP
2. Set up your environment:
   • Use conda for Python 3.10
   • Install PyTorch (2.x) with appropriate CUDA support
   • Run pip install -r requirements.txt (github.com)
3. Run the app:
   • For text‑to‑video: python wgp.py
   • For image‑to‑video: python wgp.py --i2v (github.com)
4. Use the web UI to configure your model (choose Hunyuan Video Avatar), upload audio, optionally set a reference image, and generate a 15‑second video—all using your single‑GPU setup.

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Community Spotlight

• Reddit thread r/StableDiffusion: “Wan2GP is what people should be using as their frontend … always including the latest new features … I’m just happy I don’t have to touch ComfyUI anymore.” (reddit.com)
• Lemmy cross-post:
  Shared widely with praise for the 10 GB GPU compatibility (lemmy.dbzer0.com, x.com).

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Broader Context

The core model, HunyuanVideo‑Avatar, is a multimodal diffusion transformer designed for emotion-aligned, multi-character audio-to-video generation. It uses advanced techniques:

• Character image injection ensures realism and consistency
• Audio Emotion Module captures emotional nuance
• Face‑Aware Audio Adapter enables multi-character scenes (github.com)

This update represents a significant democratization of advanced AI video creation, no longer restricted to massive GPU clusters.

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Summary

WanGP 5.4 delivers on its promise: fast, emotion-rich, high-quality audio-driven video on a single 10 GB GPU. With easy setup and a powerful web interface, it unlocks state-of-the-art video creation for everyday users. Explore the GitHub repo—and start generating!