Open Source

I made an interactive timeline of 171 LLMs (2017–2026)

Visual database shows 108 models released in just two years, with open source reaching parity in 2025.

Deep Dive

An independent developer has launched a comprehensive, interactive timeline visualizing the explosive growth of the large language model (LLM) ecosystem from 2017 to 2026. The project, available at llm-timeline.com, catalogs 171 major models from 54 different organizations, providing a searchable and filterable interface to track the evolution from the foundational 'Attention Is All You Need' paper to the latest frontier models like GPT-5.3 Codex.

The data reveals the staggering pace of development in recent years. The 2024-2025 period alone saw the release of 108 models, highlighting the intense competition and rapid iteration in the field. A key milestone emerged in 2025, where the number of significant open-source model releases (29) officially reached parity with closed-source ones (28), a shift with major implications for accessibility and innovation. Furthermore, the timeline quantifies the global scale of the race, showing that Chinese research labs from 10 different organizations are responsible for approximately 20% of all major model releases, accounting for 32 models in the dataset.

For professionals, this tool moves beyond anecdotal trends to offer data-driven insight into the market's trajectory. It allows users to filter by model type (open/closed source), search for specific organizations, and see critical milestones plotted visually. This context is invaluable for strategic planning, competitive analysis, and understanding the technological landscape's velocity. The creator invites community contributions to keep the resource updated, positioning it as a living document for tracking one of tech's fastest-moving sectors.

Key Points
  • Tracks 171 LLMs from 54 organizations, from the 2017 Transformer to GPT-5.3 Codex.
  • Reveals 108 models were released in the 2024-2025 period alone, marking the peak of development.
  • Shows open-source model releases (29) reached parity with closed-source (28) in 2025.

Why It Matters

Provides data-driven context for market analysis, competitive strategy, and tracking the velocity of AI development.