A new interactive timeline tracks 171 Large Language Models from the 2017 Transformer paper to GPT-5.3 in 2026, documenting the explosive growth of AI development. The visualization, created by Hacker News user showHN, lets users filter models by open/closed source and search across 54 organizations, revealing how quickly the field evolved from research papers to commercial products.

The timeline captures pivotal moments like OpenAI's GPT-3 in 2020, which sparked the modern LLM revolution with 175 billion parameters and few-shot learning capabilities. It also highlights Meta's LLaMA leak in 2023 that ignited the open-source movement, showing how smaller models could match GPT-3's performance. The chronological view reveals the industry's shift from massive monolithic models to efficient architectures like Mixtral's Mixture of Experts approach.

From Google's BERT in 2018 to Mistral's breakthrough 7B model in 2023, the timeline demonstrates how each innovation built on previous work. The visualization shows that while early models like BERT and GPT-2 laid the groundwork, recent advances in instruction tuning, multimodal capabilities, and open-source alternatives have democratized access to powerful AI systems. The project serves as both a historical record and a tool for understanding the rapid pace of LLM development.