Token Economics for LLM Agents: A Dual-View Study from Computing and Economics

Yuxi Chen; Junming Chen; Chenyu He; Yiwei Li; Yicheng Ji; Yifan Wu; Dingyu Yang; Lansong Diao; Lidan Shou; Hongliang Zhang; Huan Li; Gang Chen

arXiv · 2605.09104

Token Economics for LLM Agents: A Dual-View Study from Computing and Economics

Yuxi Chen·Junming Chen·Chenyu He·Yiwei Li·Yicheng Ji·Yifan Wu·Dingyu Yang·Lansong Diao·Lidan Shou·Hongliang Zhang·Huan Li·Gang Chen

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Abstract

As LLM agents evolve, tokens have emerged as the core economic primitives of Agentic AI. However, their exponential consumption introduces severe computational, collaborative, and security bottlenecks. Current surveys remain fragmented across system optimization, architecture design, and trust, lacking a unified framework to evaluate the fundamental trade-off between output quality and economic cost. To bridge this gap, this survey presents the first comprehensive survey of Token Economics. By unifying computer science and economics, we conceptualize tokens as production factors, exchange mediums, and units of account. We synthesize existing literature across a four-dimensional taxonomy: (1) Micro-level (Single Agent): Optimizing budget-constrained factor substitution via neoclassical firm theory. (2) Meso-level (Multi-Agent Systems): Minimizing collaboration friction using transaction cost and principal-agent theories. (3) Macro-level (Agent Ecosystems): Addressing congestion externalities and pricing via mechanism design. (4) Security: Internalizing adversarial threats as endogenous economic constraints. Finally, we outline frontier directions, including differentiable token budgets and dynamic markets, to lay the theoretical foundation for scalable next-generation agent systems.

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Yuxi Chen, Junming Chen, Chenyu He, Yiwei Li, Yicheng Ji, Yifan Wu, Dingyu Yang, Lansong Diao, Lidan Shou, Hongliang Zhang, Huan Li, Gang Chen. 2026-05-09. Token Economics for LLM Agents: A Dual-View Study from Computing and Economics. https://arxiv.org/abs/2605.09104

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