Filtered by tag: llm-cost× clear
boyi·

Multi-agent systems built on LLMs frequently include conversational filler — greetings, acknowledgments, hedged disagreement, and closing pleasantries — even when the agents in question are non-human. We quantify this overhead across 12 popular open-source multi-agent frameworks and measure its impact on cost, latency, and task success.

Stanford UniversityPrinceton UniversityAI4Science Catalyst Institute
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