OpenAI / MODEL EVIDENCE

O1-preview-0912

1 benchmarks · 8 observations · 1 sources

Scores at a glance

1 benchmarks · large dot: O1-preview-0912; small dots: closest models where reported

16.960.1

O1-preview-0912 · CRAFT-MD · Free response · Vignette accuracy · combined dataset ↗

7 more reported results

36.5% · O1-preview-0912 · CRAFT-MD · Free response · Multi-turn conversation accuracy · combined dataset · An evaluation framework for clinical use of large language models in patient interaction tasks — official CRAFT-MD leaderboard ↗

21.2% · O1-preview-0912 · CRAFT-MD · Free response · Single-turn conversation accuracy · combined dataset · An evaluation framework for clinical use of large language models in patient interaction tasks — official CRAFT-MD leaderboard ↗

32.1% · O1-preview-0912 · CRAFT-MD · Free response · Summarized conversation accuracy · combined dataset · An evaluation framework for clinical use of large language models in patient interaction tasks — official CRAFT-MD leaderboard ↗

93.1% · O1-preview-0912 · CRAFT-MD · Four-choice MCQ · Vignette accuracy · combined dataset · An evaluation framework for clinical use of large language models in patient interaction tasks — official CRAFT-MD leaderboard ↗

74.5% · O1-preview-0912 · CRAFT-MD · Four-choice MCQ · Multi-turn conversation accuracy · combined dataset · An evaluation framework for clinical use of large language models in patient interaction tasks — official CRAFT-MD leaderboard ↗

62.4% · O1-preview-0912 · CRAFT-MD · Four-choice MCQ · Single-turn conversation accuracy · combined dataset · An evaluation framework for clinical use of large language models in patient interaction tasks — official CRAFT-MD leaderboard ↗

76.8% · O1-preview-0912 · CRAFT-MD · Four-choice MCQ · Summarized conversation accuracy · combined dataset · An evaluation framework for clinical use of large language models in patient interaction tasks — official CRAFT-MD leaderboard ↗

Closest models by score

Similar positions on shared benchmark leaderboards. Smaller gaps are closer.

9.1 percentile-point gap

1 of 1 shared benchmark comparisons

9.1 percentile-point gap

1 of 1 shared benchmark comparisons

18.2 percentile-point gap

1 of 1 shared benchmark comparisons

How similarity is measured

Mean absolute gap in percentile positions on shared benchmark settings; lower is closer. At least 60% overlap is required, with a minimum of three when available. Independent evaluations are used when there are at least three; otherwise published report comparisons are used. Repeated model observations within one setting are averaged before ranking. Writing-style traits and composite indices are excluded. This describes similarity, not an overall quality ranking.

Sources

Every plotted observation links to its evaluation. Reported configurations, benchmark versions and task subsets can differ; similarity describes shared scores, not training lift.

  1. An evaluation framework for clinical use of large language models in patient interaction tasks — official CRAFT-MD leaderboard ↗

    Shreya Johri, Jaehwan Jeong, Benjamin A. Tran, Daniel I. Schlessinger, Shannon Wongvibulsin, Leandra A. Barnes et al. · 2025

    All 12 authors

    Shreya Johri, Jaehwan Jeong, Benjamin A. Tran, Daniel I. Schlessinger, Shannon Wongvibulsin, Leandra A. Barnes, Hong-Yu Zhou, Zhuo Ran Cai, Eliezer M. Van Allen, David Kim, Roxana Daneshjou, Pranav Rajpurkar

Names used in source tables

O1-preview-0912