CEO-Bench: Can Agents Play the Long Game?
Quick Answer
CEO-Bench evaluates AI agents' abilities in long-term, complex tasks by simulating startup operations over 500 days.
Quick Take
Only Claude Opus 4.8 and GPT-5.5 manage to exceed the $1M starting balance, highlighting significant challenges in sustained profitability and adaptability for current models.
Key Points
- CEO-Bench tests agents on long-term decision-making in a simulated startup environment.
- Agents face challenges like uncertainty, noisy data, and dynamic environments.
- Claude Opus 4.8 and GPT-5.5 are the only models to exceed the $1M starting balance.
- Most state-of-the-art models struggle with sustained profitability in this benchmark.
- The benchmark aims to measure intelligence for adaptive progress over time.
Paper Resources
Source Excerpt
Language model agents are becoming proficient executors at isolated, short-horizon tasks such as software engineering and customer service. Yet real-world challenges require a combination of sophisticated skills that remain largely untested in agents: (1) navigating long horizons amid uncertainty; (2) acquiring information in noisy environments; (3) adapting to a changing world; (4) orchestrating multiple moving parts toward a coherent goal. We introduce CEO-Bench, which evaluates these capabili
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