Reported in recent model launches

These model reports include this benchmark. Their harnesses, task subsets, scoring policies, and resource budgets can differ; follow each report’s evaluation notes before joining the numbers.

What it measures

The hardest FrontierMath tier tests advanced mathematical problem solving in a particularly demanding slice of the suite.

How to read the result

Keep the tier and release visible alongside the score, and distinguish a correct resolution from useful but incomplete research progress.

Limits and comparison traps

Launches may report revised Tier 4 sets and different tool budgets. A headline about saturation applies only to the cited evaluation contract.

Benchmark reference notes

Research-level mathematics problems handcrafted by university professors and Fields Medalists.

Where this fits in an evaluation suite

Final-answer accuracy, proof credit, and expert-reviewed research progress are distinct signals. A proof-aware evaluation should retain partial work and audit strong claims.

Start with a capability hypothesis, then choose a second test with a different failure mode. Keep the checkpoint, reasoning effort, agent tools, sampling policy, and scoring procedure fixed when measuring a training intervention. Record failures and missing outputs in the denominator.

A reproducible comparison

Pin the benchmark release, task split, model configuration, tools, sampling budget, and evaluation harness described by the primary source.

Publish the exact run configuration, item coverage, score units, and available uncertainty. If a source supplies only an aggregate or a single run, preserve that limit. A new model name or a rounded score alone does not establish a capability improvement.

PRIMARY EVIDENCE & FURTHER READING

  1. GPT-6 Astra: A new generation of intelligence ↗

    OpenAI

Reviewed 2026-10-26. Explanation and interpretation by RLTasks. Benchmark ownership remains with its original authors.