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opensource
AnimatedLLM explains how large language models work through a web application.

About opensource
AnimatedLLM is an open-source educational web application that explains how large language models work. Rather than static diagrams or equations, it presents dynamic, step-by-step visualizations of the Transformer architecture in action, and it runs entirely in the browser using pre-computed data. The project is published on GitHub under an MIT license, with source built using D3.js and GSAP.
Key features
- Step-by-step animated visualizations of the Transformer architecture
- Keyboard controls to play, pause, step, reset and skip tokens
- Runs entirely in the browser using pre-computed data
- Light and dark theme toggle plus language switching
- Source code on GitHub under an MIT license
- Can be run locally with Node.js 20.9.0+ and npm
- Open source under an MIT license, with contributions welcomed
- Runs in the browser using pre-computed data, so no local model setup is needed to view it
- Documented citation for use in research or teaching
- Running the app on your own device requires Node.js version 20.9.0 or higher and npm
- The animation relies on pre-computed data rather than live model execution
opensource at a glance
- Category
- AI & Machine Learning › AI Learning & Guides
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
opensource alternatives
Tools and sites you could use instead, ranked by how closely they match.
AnimatedLLM uses animations to explain the mechanisms behind large language models.
Tensor Trust offers an interactive game about testing AI security and model robustness.
OpenAI’s API guide covers prompt engineering strategies and tactics for working with large language models.
The Prompt Engineering Guide teaches prompt engineering and provides learning materials about language models.
Test AI hacking skills and explore language model limitations through the Gandalf interactive challenge.
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