AI-Model Network: Concept, Current State and Future

Computer Science > Artificial Intelligence [Submitted on 25 May 2026] AI-Model Network: Concept, Current State and Future Li Zhetao, Zeng Xiyu, Wang Jianhui, Xiao Yong, Liu Zhongren, Wu Junru, Lai Junjie, Huang Jijun, Long Saiqin While the primary function of computers lies in computation and processing, the core value of the Internet is rooted in sharing and collaboration. Computers create the Internet, and the Internet empowers the value of computers. The rapid development of the Internet, cloud computing, and big data is pushing artificial intelligence into the era of large models (LMs). However, the practical application of LMs is currently hindered by high training costs and deployment complexities, driving a shift toward lightweight, private, and domain-specific models. With the rapid proliferation and wide distribution of heterogeneous models, enabling effective interaction and collaboration among them has emerged as a critical bottleneck that urgently needs to be addressed in LM development. Drawing inspiration from the development of the Internet, this paper proposes the concept, vision, and system architecture of world wide AI-model network (AI-ModelNet). It is a novel paradigm that achieves interconnection, capability sharing, and collaborative reasoning by establishing pathways between models. We first briefly review the current state of single-model and multi-model research. Subsequently, the systemic vision and hierarchical architecture of AI-ModelNet are articulated, followed by validation of the framework's feasibility through a prototype system and diverse application cases. Finally, key directions for future research are discussed preliminarily. Comments: 31 pages, 14 figures Subjects: Artificial Intelligence (cs.AI) MSC classes: 68T01 ACM classes: C.0 Cite as: arXiv:2606.27382 [cs.AI]   (or arXiv:2606.27382v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2606.27382 Focus to learn more Journal reference: Journal of Computer Research and Development, 2026, 63(5): 1305-1318 Related DOI: https://doi.org/10.7544/issn1000-1239.202550223 Focus to learn more Submission history From: Xiyu Zeng [view email] [v1] Mon, 25 May 2026 13:46:21 UTC (9,824 KB) Access Paper: view license Current browse context: cs.AI < prev   |   next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)