Magentic Marketplace: An Open-Source Environment for Studying Agentic Markets

As LLM agents advance, they are increasingly mediating economic decisions, ranging from prod-
uct discovery to transactions, on behalf of users. Such applications promise benefits but also raise
many questions about agent accountability and value for users. Addressing these questions requires
understanding how agents behave in realistic market conditions. However, previous research has
largely evaluated agents in constrained settings, such as single-task marketplaces (e.g., negotiation)
or structured two-agent interactions. Real-world markets are fundamentally different: they require
agents to handle diverse economic activities and coordinate within large, dynamic ecosystems where
multiple agents with opaque behaviors may engage in open-ended dialogues. To bridge this gap, we
investigate two-sided agentic marketplaces where Assistant agents represent consumers and Service
agents represent competing businesses. To study these interactions safely, we develop Magentic
Marketplace– a simulated environment where Assistants and Services can operate. This environ-
ment enables us to study key market dynamics: the utility agents achieve, behavioral biases, vul-
nerability to manipulation, and how search mechanisms shape market outcomes. Our experiments
show that frontier models can approach optimal welfare—but only under ideal search conditions.
Performance degrades sharply with scale, and all models exhibit severe first-proposal bias, creating
10-30x advantages for response speed over quality. These findings reveal how behaviors emerge
across market conditions, informing the design of fair and efficient agentic marketplaces.