SciCode++

Two models, one complete grid

Both models ran eight trials on every task they were both given, so these rates are measured on the same 3,451 problems rather than on whatever subset each was handed. Grading is all-or-nothing: a trial passes every test its task defines, or it fails. 2 models.

Last updated 2026-09-09

Model Scorecard · open a row for its model cardMain problem pass@8Out Tokens
  1. 1GPT-5.6 (sol)high17.7%27,608 trials10k

    Model card · evaluated Sep 2026

    reasoning: high · 27608 trials

    • Reward

      17.7%

    • Tokens

      12k

    Failure Modes

    Every verifier failure was filed under one failure mode by a stated rule, not by a reviewer, grouped into the stages above. The shares split this model's own 22696 verifier failures, worst first — grader error is excluded, so a model is never charged with its grader's mistake.

  2. 2Gemini 3.1 Pro Previewhigh14.6%27,608 trials6k

    Model card · evaluated Sep 2026

    reasoning: high · 27608 trials

    • Reward

      14.6%

    • Tokens

      8k

    Failure Modes

    Every verifier failure was filed under one failure mode by a stated rule, not by a reviewer, grouped into the stages above. The shares split this model's own 23546 verifier failures, worst first — grader error is excluded, so a model is never charged with its grader's mistake.

What an attempt costs

Tokens per trial, averaged over every run the drop recorded them on. Read the two bars against the board above: they are the only other dimension this delivery measures, and the models are not close on them. There is no clock and no price in the drop, so cost per task is not a number this bench can publish.

Avg Input Tokens

Input tokens consumed, averaged across trials and tasks — cumulative across turns, not peak context

  1. 2k

    Gemini 3.1 Pro Previewhigh

  2. 2k

    GPT-5.6 (sol)high

Avg Output Tokens

Output tokens generated, averaged across trials and tasks

  1. 10k

    GPT-5.6 (sol)high

  2. 6k

    Gemini 3.1 Pro Previewhigh