BitNet Chat: Interactive 1.58-bit LLM Demo

BitNet Chat is an interactive web interface for chatting with extremely compressed large language models in real time. It demonstrates that 1.58-bit quantized models can deliver responsive, coherent conversation while using a fraction of the memory and compute of their full-precision counterparts.

View the BitNet Chat GitHub Repository

Overview

The application wraps ternary-quantized BitNet models in a Gradio chat interface, providing a tangible demonstration of the BitCore and BitOps stack in action. Users can interact with compressed LLMs and switch between different backend configurations to compare performance.

Key Features

• Real-time streaming responses with token-by-token generation
• Backend switching between different inference engines at runtime
• 24x speedup over PyTorch FP32 baseline on ARM M4 hardware
• 80% memory reduction enabling deployment on consumer devices
• Gradio interface for zero-setup browser-based interaction

How It Works

The demo sits at the top of the ternary neural network stack:

1. BitCore provides the quantization-aware model layers
2. BitOps supplies the hardware-optimized ternary matrix multiplication kernels
3. BitNet Chat wraps everything in an accessible chat interface

When a user sends a message, the model generates tokens using packed ternary weights and optimized CUDA or ARM NEON kernels, streaming the response back to the browser in real time.

Performance

Requirements

• Python 3.9+
• PyTorch 2.0+
• Gradio
• BitCore & BitOps

License

MIT License