Attention Tax, Handoff Tax: A Stylised Model of When Multi-Agent LLM Systems Help
Recent work on multi-agent LLM systems reaches sharply different conclusions: some results show that a single agent with the same information and compute should dominate a delegated system, others that multi-agent gains grow with task depth. We argue that much of the disagreement comes from modelling different bottlenecks, and introduce a stylised reliability model built around two trade-offs. Decomposition reduces the burden of long contexts but incurs a handoff tax when information is compressed or transferred between agents. Redundancy gains from multiple samples, but its benefit depends on how much their failures are shared. With reasoning budget, verification, and task structure adde...
| Authors | Akshit Anchan, Nayonika Sen |
|---|---|
| Primary category | cs.MA |
| Published | 5 October 2026 |
| Last updated at source | 5 October 2026 |
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