aiaimodel.cards
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SWE-bench Multilingual

Fixing real issues in real open-source repositories; a patch counts only if the project's own tests pass. Variants differ in task set and languages.

  1. 1Claude Opus 5.5 · Anthropic
    93.9%
  2. 2Claude Sonnet 5.5 · Anthropic
    90.3%
  3. 3Claude Opus 5 · Anthropic
    89.5%
  4. 4Claude Fable 5.1 · Anthropic
    89.1%
  5. 5Claude Haiku 5.5 · Anthropic
    83.7%

How each maker reported it

  • Claude Opus 5.5 Table 8.1.A, p.174

    Claude results use adaptive thinking at max effort, averaged over five trials (Terminal-Bench 4.0 at xhigh). Competitor figures come from the developers' own published results.

  • Claude Sonnet 5.5 Table 8.1.A, p.109

    Claude results use adaptive thinking at max effort with default sampling, averaged over five trials. Competitor figures come from the developers' own published system cards or leaderboards.

  • Claude Opus 5 Table 8.1.A, p.148–149

    Claude Opus 5 results use adaptive thinking at max effort, averaged over five trials (ARC-AGI-3 at high effort). GPT-5.6 Sol's FrontierBench figure uses Codex and its ARC-AGI-1 figure is at xhigh. The Fable 5 HealthBench Professional figure carries a footnote reading "Mythos 5". Competitor figures come from the developers' own published results or leaderboards.

  • Claude Fable 5.1 Table 8.1.A, p.167

    Fable 5.1 and Mythos 5.1 share weights, so column 0 covers both (likewise Fable 5 / Mythos 5). Claude results use adaptive thinking at max effort, averaged over five trials. Terminal-Bench 4.0 values are from §8.6, p.171 (Mythos 5.1: 60.9%; GPT-5.6 Sol from the public leaderboard). Competitor figures come from the developers' own published results or leaderboards.

  • Claude Haiku 5.5 Table 8.1.A, p.111

    Haiku 5.5 results use adaptive thinking at max effort with default sampling, averaged over five trials. FrontierCode is shown at max effort (Sonnet 5.5 scores 52.1 at xhigh). OSWorld is the offline subset; GPT-6 Luna was run by Anthropic on the same tasks. Other competitor figures come from the developers' own published results.

Only each model's own maker's number is shown; scores a maker reports for rival models are left out.