mlsanityData to 14 Oct 2026

LemonadeBench: Evaluating the Economic Intuition of Large Language Models in Simple Markets

arXiv 2602.13209 ↗First posted 14 Jan 2026q-fin.GN cs.AIcited by 0

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Abstract (arXiv)

We introduce LemonadeBench v0.5, a minimal benchmark for evaluating economic intuition, long-term planning, and decision-making under uncertainty in large language models (LLMs) through a simulated lemonade stand business. Models must manage inventory with expiring goods, set prices, choose operating hours, and maximize profit over a 30-day period-tasks that any small business owner faces daily. All models demonstrate meaningful economic agency by achieving profitability, with performance scaling dramatically by sophistication-from basic models earning minimal profits to frontier models capturing 70% of theoretical optimal, a greater than 10x improvement. Yet our decomposition of business efficiency across six dimensions reveals a consistent pattern: models achieve local rather than global optimization, excelling in select areas while exhibiting surprising blind spots elsewhere.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 5 of its 7 references that are in the map. First posted on arXiv 14 Jan 2026.

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References · 5

  1. 2020Measuring Massive Multitask Language Understandingcited by 7,963
  2. 2023GPQA: A Graduate-Level Google-Proof Q&A Benchmarkcited by 2,879
  3. 2025ARC-AGI-2: A New Challenge for Frontier AI Reasoning Systemscited by 190
  4. 2025SWE-Lancer: Can Frontier LLMs Earn 1 Million from Real-World Freelance Software Engineering?cited by 105
  5. 2025Vending-Bench: A Benchmark for Long-Term Coherence of Autonomous Agentscited by 80

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