AIEvals

Benchmarks

AIME 2026

Competition mathematics from the 2026 American Invitational Mathematics Examination.

MathematicsMathematical Association of America, reported by Reflection AIVendor-reported onlyReported by Reflection AI

How it is run

Reflection AI reports scores for Beam, Inkling and GLM 5.2 in its reasoning comparison. These are publisher-reported figures.

What it cannot tell you

The 2026 questions are distinct from AIME 2025. The announcement does not identify the attempt count, reasoning effort or aggregation rule.

Why there is no independent table

No independent suite in this dataset runs AIME 2026. The numbers below are the ones model publishers report about their own models, which is a different kind of evidence: each publisher chooses its own harness and effort level, so a row is readable on its own and not against the other rows.

Read this with

Benchmarks in the same category, which usually disagree with this one on purpose.

  • AIME 2025Same category. Olympiad mathematics from the 2025 American Invitational Mathematics Examination.
  • RiemannBenchSame category. Mathematical reasoning, included in the report’s science and math evaluations.
  • ProofBench v1.1Same category. Formal and semi-formal mathematical proof construction, graded on the proof rather than the final answer.
  • FrontierMath Tier 4 (v2)Same category. Research-level mathematics problems, with Tier 4 the hardest slice of the set.
  • MathArena ApexSame category. Final-answer mathematics problems that no model had solved when the set was published — Apex exists because the standard competitions had stopped discriminating.

As reported by each publisher

Kept separate per publisher, because the settings are not shared.

Reflection AI

Introducing Beam: model capability comparisons · 5 October 2026

RankModelScore
2Beam97.8%
3Inkling97.1%
1GLM 5.299.2%

Ranks compare reported scores in the same published row; ties share a rank.

Reflection AI’s four capability tables, read 6 October 2026. All 21 rows and eight model columns are transcribed; NR means not reported and remains blank. The source’s Qwen 3.8 Max column uses this catalogue’s Qwen3.8 Max spelling. Beam results are publisher reports; Reflection AI cites Artificial Analysis and Datacurve for comparison-model evaluations. The announcement does not specify a common harness, effort or trial count for every row. Ranks are derived within each published row from reported values only, with ties sharing a rank; they do not establish an independent or overall model ranking. AutomationBench uses the public split; AA-Omniscience is an index on the public split only, calculated by Reflection AI. BrowseComp and DeepSearchQA use context management. AA-LCR has no stated version. These settings remain separate from other source fields.

reflection.ai/blog/introducing-beam

Sources

Every page used for this benchmark, read on 17 October 2026.