A comprehensive curated collection of Large Language Model (LLM) architecture figures and technical fact sheets. This gallery provides a visual and data-driven overview of modern model designs, ranging from classic dense architectures like GPT-2 to advanced sparse Mixture-of-Experts (MoE) systems and hybrid attention models. Users can explore detailed specifications including parameter scales, context windows, attention mechanisms, and intelligence indices for various prominent models.
Key features include:
* Detailed architecture fact sheets for a wide array of models such as Llama, DeepSeek, Qwen, Gemma, and Mistral.
* An architecture diff tool to compare two different model designs side-by-side.
* Comparative analysis across dense, MoE, MLA, and hybrid decoder families.
* Links to original source articles and technical reports for deeper research.
Key features include:
* Detailed architecture fact sheets for a wide array of models such as Llama, DeepSeek, Qwen, Gemma, and Mistral.
* An architecture diff tool to compare two different model designs side-by-side.
* Comparative analysis across dense, MoE, MLA, and hybrid decoder families.
* Links to original source articles and technical reports for deeper research.
