MerchantBench

Agent benchmarks tend to focus on bounded tasks with immediate success criteria, which flatters systems that cannot hold a plan for a month. MerchantBench targets long-term coherence instead, running a 365-day order-level e-commerce simulation grounded in 98,843 real product records with 26 tools for agent interaction. Agents handle product sourcing, listing and pricing control, cash-flow management, and feedback arriving at wildly different delays, with promptly observable supplier events coupled to delayed downstream order outcomes so earlier decisions must be revisited. Scoring runs on cumulative net assets, so incoherence compounds rather than averaging out. Across eight LLMs under two agent frameworks and 48 runs of 365 simulated days each, the best configuration reaches only 27.3% of the mean final net assets achieved by human participants.