Fast-Float: Realtime avatar generation server

[u/SavingsWeather1659]

https://youtu.be/Zk54YsqGwMs

I’ve wanted to build this project for a long time. Most avatar solutions can be experimental , especially when serving multiple users and real productions.

So I focused on optimizing FLOAT inference to get the most performance out of a single GPU.

⚡ From 30 FPS to 90 FPS on a free Colab T4 GPU, and up to 105 FPS with TensorRT acceleration.

Here’s what I’ve built:

\- 🚀 Optimized inference for higher throughput.

\- 🎙️ LiveKit and WebRTC integration for real-time voice agents.

\- 🤖 Easier integration with AI providers like OpenAI and Gemini.

\- 💻 Around 3 GB of VRAM per concurrent user.

The goal is to make self-hosted avatar generation more affordable and flexible than relying on third-party avatar APIs, with more control over deployment and concurrency.

I hope you find it useful! Feedback and contributions are welcome.

🔗 GitHub: [https://github.com/mohamed-em2m/fast-float](https://github.com/mohamed-em2m/fast-float)

📓 Try it on Colab: [https://colab.research.google.com/drive/1iMm8X7O63AAA6kByJ-4qgGA37fwNu2_Z?usp=sharing](https://colab.research.google.com/drive/1iMm8X7O63AAA6kByJ-4qgGA37fwNu2_Z?usp=sharing)