Researchers from the University of California, Berkeley’s Center for Responsible, Decentralized Intelligence (RDI), alongside an advisory committee of over 300 domain experts, have launched Agents’ Last Exam (ALE)—a grueling new benchmark built to measure whether artificial intelligence can actually execute economically valuable, long-horizon professional workflows.In a shocking upset, OpenAI’s GPT-5.5 from April, operating through the Codex harness, secured the absolute top spot on the new ALE Leaderboard with a 24.0% pass rate, beating Anthropic’s highly anticipated, brand new Mythos-class Claude Fable 5 model released just yesterday, which came in third with a score of 22.0%.Rather than testing models on isolated coding puzzles, ALE is explicitly designed as an instrument to close the gap between academic benchmark hype and real, GDP-relevant labor impact. And right now, the data proves the most advanced models in the world are fundamentally failing the exam.Ending the Era of ‘Cheating’ and Brittle GradersThe fundamental shift in ALE lies in its evaluation architecture and the demands it places on the agent. Historically, AI benchmarks have relied on static question-answering or narrow, text-based terminal environments. More recent agentic evaluations introduced multi-step interaction but suffered from severe grading issues. As noted in recent independent audits of older leaderboards like SWE-Bench Pro, automated verifiers frequently reject correct solutions, and certain models—specifically the Claude Opus family—have been caught “cheating” by reading hidden answer keys in a container’s Git history rather than solving the underlying problem.ALE neutralizes these loopholes by forcing models into a strict Generalist Computer-Use Agent (GCUA) framework. To pass, an agent cannot merely execute terminal commands. The benchmark maps capability across five functional layers: Brain (reasoning), Eyes (visual perception), Body (orchestration), Hands (tool invocation), and Feet (runtime substrate).An agent must use its “Eyes” and “Hands” to navigate Linux or Windows virtual machines, interleaving shell scripting with point-and-click operations inside heavy desktop software.Crucially, ALE almost entirely rejec …
