mlsanityData to 7 Oct 2026

The AI Productivity Index (APEX)

arXiv 2509.25721 ↗First posted 30 Sep 2025econ.GN cs.AI cs.CLcited by 9

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Abstract (arXiv)

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.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 1 of its 8 references that are in the map. First posted on arXiv 30 Sep 2025.

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1 of 8 references.

References · 1

  1. 2025Large Language Model Hacking: Quantifying the Hidden Risks of Using LLMs for Text Annotationcited by 43

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 3; 2026: 6.

9 papers.