AI-Model Network: Concept, Current State and Future

arXiv cs.AI Papers
ai-model-network large-models model-collaboration system-architecture interconnection future-paradigm

Summary

This paper proposes the concept of the world wide AI-Model Network (AI-ModelNet), a novel paradigm for interconnecting, sharing capabilities, and enabling collaborative reasoning among diverse large models. The authors review current single- and multi-model research, present a hierarchical architecture, and validate feasibility through a prototype system and application cases.

arXiv:2606.27382v1 Announce Type: new Abstract: 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.
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# AI-Model Network: Concept, Current State and Future
Source: [https://arxiv.org/abs/2606.27382](https://arxiv.org/abs/2606.27382)
[View PDF](https://arxiv.org/pdf/2606.27382)

> Abstract: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\.

## Submission history

From: Xiyu Zeng \[[view email](https://arxiv.org/show-email/2fb97351/2606.27382)\] **\[v1\]**Mon, 25 May 2026 13:46:21 UTC \(9,824 KB\)

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