Year: 2025
Type: preprint
Abstract: We present an extended version of the AI Productivity Index (APEX-v1-extended), a benchmark for assessing whether frontier models are capable of performing economically valuable tasks in four jobs: investment banking associate, management consultant, big law associate, and primary care physician (MD). This technical report details the extensions to APEX-v1, including an increase in the held-out evaluation set from n = 50 to n = 100 cases per job (n = 400 total) and updates to the grading methodology. We present a new leaderboard, where GPT5 (Thinking = High) remains the top performing model with a score of 67.0%. APEX-v1-extended shows that frontier models still have substantial limitations when performing typical professional tasks. To support further research, we are open sourcing n = 25 non-benchmark example cases per role (n = 100 total) along with our evaluation harness.
Source: arXiv (Cornell University)
Authors: Vidgen, Bertie, Fennelly, Abby, Pinnix, Evan, Benchek, Julien, Khan, Daniyal, Richards, Zach, Bridges, Austin, Huang, Calix, Sahu, Kanishka, Kottamasu, Abhishek, Ma, Bo, Hunsberger, Ben, Robinson, Isaac, Datta, Akul, Mahapatra, Chirag, Barton, Dominic, Sunstein, Cass R., Topol, Eric, Foody, Brendan, Nitski, Osvald
Institutions: Harvard University, Scripps Research Institute
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7084447673
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