llm-viz is a 3D architecture visualizer and inference simulator for large language models. It provides a visual representation of network topology and the mathematical operations used during the process of generating a response.
The tool enables the exploration of internal weight distributions and the layout of layers within a neural network. It facilitates model interpretability and inference debugging by tracking the step-by-step movement of data through the architecture.
The system utilizes GPU-accelerated 3D rendering to visualize tensor flow and spatial mappings of weights. It includes capabilities for static model analysis and instruction-step playback to synchronize the visual state of the network with sequential execution.