A Visual Guide to Attention Variants in Modern LLMs
Ahead of AI Sebastian Raschka, PhD
Sebastian Raschka created an LLM architecture gallery with 45 entries documenting attention variants used in modern large language models, including multi-head attention, grouped-query attention, and other mechanisms. The gallery includes visual model cards and a poster version available through Redbubble, with the Medium size measuring 26.9 x 23.4 inches. The resource serves as both a reference and learning tool for understanding how different attention mechanisms work in contemporary open-weight architectures like Llama, Qwen, and Gemma.
Why it matters
From MHA and GQA to MLA, sparse attention, and hybrid architectures
