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Science benchmarks

Separate scientific knowledge, quantitative reasoning and research code when choosing an evaluation.

Science benchmarks can evaluate knowledge about a field or the work performed inside it. Selecting the right physics answer differs from implementing a numerical method that behaves correctly. GPQA provides expert science questions; SciCode evaluates scientific programming tasks. Both are relevant to scientific assistants, but success on one cannot replace evidence about the other.

What these benchmarks test

  • Subject questions combine disciplinary knowledge with reasoning about stated conditions.
  • Scientific coding tasks connect a mathematical or physical specification to an executable implementation.
  • Multi-part tasks can reveal whether a system combines subproblem solutions into a working whole.

How to read the results

  • Check disciplinary coverage and whether the task supplies background explanations, equations or intermediate solutions.
  • Inspect numerical tolerances, test environments and dependencies when outputs are executable.
  • Separate component success from complete-task success, and knowledge questions from experimental or computational workflows.

What to watch for

  • A passing implementation does not by itself validate a scientific hypothesis or establish a novel discovery.
  • Domain averages can hide uneven ability across specialties; consider whether the benchmark resembles your actual research task.

References

  1. SciCode official project
  2. GPQA research paper

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Coding benchmarksReasoning and math benchmarksMedical benchmarks