Unveiling the 2025 Open‑Source Large Model Landscape: Trends and Insights

The 2025 Inclusion Bund conference revealed a rapidly evolving open‑source large‑model ecosystem, highlighting 114 top projects across 22 fields, a 35% update rate, global developer distribution, community initiatives like Modak and Silicon Flow, and forward‑looking discussions on Vibe Coding, AI Agents, and the future of AI development.

AntTech
AntTech
AntTech
Unveiling the 2025 Open‑Source Large Model Landscape: Trends and Insights

Panorama and Trends: Data‑Driven Insights into the Open‑Source Large Model Ecosystem

During the Inclusion Bund Conference on September 13, 2025, experts from Ant Open Source, Modak Community, Silicon Flow and other organizations presented the 2.0 edition of the “Open‑Source Large Model Development Panorama and Trends” report, covering 114 top projects across 22 technical fields.

The new panorama splits the ecosystem into two major directions—AI Infra and AI Agent—showing a 35% update rate since version 1.0, with 39 new projects added and 60 removed. Over 62% of projects were created after the “GPT moment” in October 2022, highlighting rapid innovation.

Developer distribution shows more than 360 000 contributors worldwide, about 24% from the United States and 18% from China, with comparable numbers in the AI Agent area and a US lead in AI Infra and AI Data.

Community Highlights

Modak Community has become China’s largest model‑open‑source community, hosting 100 000 models and serving 18 million users, and promotes a four‑layer experience architecture: Find Model, Use Model, Learn Model, Play Model.

Silicon Flow reported explosive growth after the DeepSeek open‑source launch, reaching 600 000 users in three days and 2 million in a week, and noted that the gap in AI capability between China and the US has narrowed to a few months.

Round‑Table Discussions

Vibe Coding was discussed as a tool‑stack that shifts development from component libraries to intent‑driven AI coding, with experts emphasizing the need for strong code‑review practices and new metrics such as “Token efficiency”.

AI Agent discussions explored definitions, technical challenges (context engineering, multimodal fusion), commercialization prospects, and future scenarios where multi‑agent systems could transform work.

Overall, the report concludes that open‑source is becoming the core driver of AI technology evolution and industry adoption, lowering barriers, fostering innovation, and moving AI from elite technology to a universal productivity tool.

AIVibe Codinglarge modelsecosystemtrends
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