mlsanityData to 14 Oct 2026

WorkBench Revisited: Workplace Agents Two Years On

arXiv 2606.13715 ↗First posted 10 Jun 2026cs.AI cs.CL cs.MAcited by 0

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Abstract (arXiv)

The best agent on WorkBench in March 2024, GPT-4, completed just 43% of tasks. We revisit the benchmark in June 2026 and find that the best agent to date, Claude Fable 5, now completes 98%. Beyond this considerable progress in frontier agent performance, three things stand out. First, unintended harmful actions, such as emailing the wrong person, fell from 26% of tasks for GPT-4 to 1.9% for Claude Fable 5; capability and safety go together on WorkBench rather than trade off, so the models that finish the most tasks also do the least unintended damage. Second, the rise of open-weight models has drastically lowered costs for a performance level that was only accessible to proprietary models, while frontier costs have stayed stable. Third, while several classes of error have been eliminated, frontier models still make some basic mistakes that occasionally result in irreversible harm. We release an updated version of the benchmark with data and code quality improvements, new model scores, and analysis of agent progress on WorkBench since 2024.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 6 references that are in the map. First posted on arXiv 10 Jun 2026.

Builds on

2 of 6 references.

References · 2

  1. 2023WebArena: A Realistic Web Environment for Building Autonomous Agentscited by 2,006
  2. 2024WorkBench: a Benchmark Dataset for Agents in a Realistic Workplace Settingcited by 53

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