Best AI time horizon by August 2026, per METR?
26
2kṀ6794
2026
16%
<6 hours
28%
6 to 8 hours
25%
8 to 12 hours
17%
12 to 16 hours
11%
16 to 24 hours
4%
>=24 hours

This market will resolve to the highest METR 50% time horizon for any AI model released by August 31, 2026, closing after a two-month buffer period. Left bounds inclusive, right bounds exclusive.

50% time horizon is, roughly speaking, the time that skilled humans take to complete tasks that an AI system can successfully do 50% of the time. See METR's "Measuring AI Ability to Complete Long Tasks" for more. As of August 2025, the longest 50% time horizon is GPT-5's 2h 17 min.

For reference, the buckets in this market correspond to doubling times of roughly:

  • 6 hours: 9 months

  • 8 hours: 7 months

  • 12 hours: 5.3 months

  • 16 hours: 4.5 months

  • 24 hours: 3.7 months

given that GPT-5 has a time horizon of 2.28 hours and was released in early August 2025.

Time horizon estimates will vary based on the set of tasks used, so this market will be based on the "headline" result reported by METR. METR currently uses a composite of the HCAST, RE-Bench, and SWAA benchmarks. There is a good chance that they extend this set with harder/longer tasks at some point. If METR no longer publishes a headline result, and their future evals are based on substantially different benchmarks so that it is difficult to compare to their mid-2025 estimates, then this market may become ambiguous and resolve N/A.

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filled a Ṁ50 NO at 19% order

Relevant to various time horizon markets:

https://www.lesswrong.com/posts/4oCh3x6EPHomEbcDJ/nikola-s-shortform?commentId=jfv8LdK3bHCavWSDS

I very roughly polled METR staff (using Fatebook) what the 50% time horizon will be by EOY 2026, conditional on METR reporting something analogous to today's time horizon metric.

I got the following results: 29% average probability that it will surpass 32 hours. 68% average probability that it will surpass 16 hours.

The first question got 10 respondents and the second question got 12. Around half of the respondents were technical researchers. I expect the sample to be close to representative, but maybe a bit more short-timelines than the rest of METR staff.

The average probability that the question doesn't resolve AMBIGUOUS is somewhere around 60%.

bought Ṁ5 YES

he average probability that the question doesn't resolve AMBIGUOUS is somewhere around 60%.

40% likely to be AMBIGUOUS which seems pretty bad

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