TokenPrint Lets Developers Visualize LLM Inference Layer by Layer in 3D

A developer has released TokenPrint, a free open-source tool that lets users visually explore how transformer-based large language models process tokens during inference. The interactive 3D environment allows users to navigate through each layer of a model and inspect individual operations such as attention scores, embeddings, normalization, and MLP projections. Rather than presenting the model as a static diagram or raw code, TokenPrint frames inference as a step-by-step computational journey through the network. Users can select any component to view plain-language explanations, mathematical equations, tensor dimensions, parameter counts, and actual model data. The project is available to try online at tokenprint.in and its source code is hosted publicly on GitHub.