What it means for leaders

The length of task AI agents can handle on their own has been doubling in months, not years. Work that needed a person for a full day is coming into range, so redesign processes around supervised agents now rather than after the next jump.

What would change the reading: Records at higher success rates (80%), which matter more for production work.

The trend

March 14, 2023April 7, 2026

Every reading

DateValueChangeDetailSource
17.4 hours+45.4%claude-mythos-preview-earlySource
12.0 hours+104.1%claude-opus-4-6_unknownSource
5.9 hours+20.2%gpt-5.2-2025-12-11_highSource
4.9 hours+30.6%claude-opus-4-5-20251101Source
3.7 hours+10.5%gemini-3-pro-previewSource
3.4 hours+69.6%gpt-5-2025-08-07_highSource
120 minutes+98.2%o3-2025-04-16_unknownSource
60 minutes+55.7%claude-3-7-sonnet-20250219Source
39 minutes+89.3%o1-2024-12-17_mediumSource
21 minutes+1.0%claude-3-5-sonnet-20241022Source
20 minutes+78.1%o1-preview-2024-09-12Source
11 minutes+62.9%claude-3-5-sonnet-20240620Source
7 minutes+75.0%gpt-4o-2024-05-13Source
4 minutes—gpt-4-0314Source

Definition and method

What it measures
The longest task, measured by how long it takes a skilled human, that the best measured model completes successfully half the time (METR's 50% time horizon), recorded each time a model sets a new record.
Population
AI models measured by METR on its current task suite
Updated
When new models are measured

Caveats

  • The tasks are mostly software and research work; other domains may differ.
  • A 50% success rate is far from the reliability most business processes need.

Cite this

Enterprise AI in Numbers, "Length of tasks the best AI agents can complete", https://lucianoayres.com/ai-brief/data/ai-agent-task-length/, retrieved October 25, 2026. Data: METR time horizons, via Epoch AI.

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