FrontierMath Tiers 1–3
Unpublished research-level maths problems, tiers 1–3 (v2 private set). Run by Epoch AI.
As of 24 Oct 2026, GPT-6 Astra leads FrontierMath Tiers 1–3 on BenchLeader with 93.7%, ahead of GPT-6.1 Sol at 93.7%, across 118 model configurations with a published result.
- Published by
- Epoch AI Benchmarking Hub
- Category
- Maths
- Index weight
- 1.0
- Models
- 118
- Data as of
- 24 Oct 2026
- Newest result
- 17 Oct 2026
CC BY 4.0 — Epoch AI, ‘AI Benchmarking Hub’, epoch.ai/benchmarks. Mirrored boards credit their original publishers.
What the test looks like
FrontierMath is a private set of research-level mathematics problems written by professional mathematicians, each with a definite, automatically checkable answer. Tiers 1 to 3 range from hard undergraduate to problems that take a specialist hours. The problems are unpublished, so they cannot appear in training data.
How it is scored
Percent of problems solved, verified by running the model's final answer through an automatic checker. Epoch AI runs the models itself, usually with a code tool available, and reports the mean of several runs.
What to keep in mind
Scores are low and noisy: a handful of problems separates models, and the confidence intervals Epoch publishes are wide. OpenAI funded the benchmark's creation and holds access to most of the problems, which Epoch discloses.
- 1GPT-6 Astra (max)93.7%
- 2GPT-6.1 Sol (max)93.7%
- 3Claude Opus 5.5 (max)91.2%
- 4Claude Fable 5.1 (max)90.2%
- 5GPT-6 Sol (max)89.8%
- 6GPT-5.6 Sol (max)89.1%
- 7Claude Sonnet 5.5 (max)88.8%
- 8GPT-5.5 Pro (xhigh)87.7%
- 9Claude Fable 5 (max)87.0%
- 10Gemini 4 Argon (high)86.0%
- 11GPT-5.6 Terra (max)86.0%
- 12Claude Opus 5 (max)85.6%
- 13GPT-5.5 (xhigh)85.3%
- 14GPT-5.4 Pro (xhigh)82.5%
- 15Muse Wonder (max)82.1%
| # | ||||
|---|---|---|---|---|
| 1 | 93.7% | 70.4 | 2026-09-03 | |
| 2 | 93.7% | 69.9 | 2026-09-29 | |
| 3 | 91.2% | 72.6 | 2026-09-22 | |
| 4 | 90.2% | 70.5 | 2026-09-01 | |
| 5 | 89.8% | 66.4 | 2026-09-22 | |
| 6 | 89.1% | 68.0 | 2026-07-09 | |
| 7 | 88.8% | 69.3 | 2026-09-28 | |
| 8 | 87.7% | 65.3 | 2026-04-23 | |
| 9 | 87.0% | 69.3 | 2026-06-09 | |
| 10 | 86.0% | 70.8 | 2026-09-30 | |
| 11 | 86.0% | 64.4 | 2026-07-09 | |
| 12 | 85.6% | 68.8 | 2026-07-24 | |
| 13 | 85.3% | 66.1 | 2026-04-23 | |
| 14 | 82.5% | 61.9 | 2026-03-05 | |
| 15 | 82.1% | 67.5 | 2026-10-12 | |
| 16 | 82.1% | 59.9 | 2026-07-09 | |
| 17 | 80.0% | 63.3 | 2026-05-28 | |
| 18 | 79.0% | 60.0 | 2026-09-22 | |
| 19 | 78.6% | 64.7 | 2026-03-05 | |
| 20 | 75.1% | 60.5 | 2026-10-07 | |
| 21 | 74.7% | 57.1 | 2026-08-02 | |
| 22 | 74.4% | 64.9 | 2026-09-02 | |
| 23 | 74.0% | 67.1 | 2026-09-02 | |
| 24 | 74.0% | – | 2025-12-11 | |
| 25 | 72.2% | 64.7 | 2026-07-16 | |
| 26 | 71.6% | 63.5 | 2026-08-13 | |
| 27 | New | 71.2% | 64.0 | 2026-10-17 |
| 28 | 70.2% | 62.4 | 2026-04-16 | |
| 29 | New | 69.8% | 58.6 | 2026-10-15 |
| 30 | 68.8% | 63.5 | 2026-08-14 | |
| 31 | 68.4% | 64.4 | 2026-09-02 | |
| 32 | 67.4% | 60.7 | 2025-12-11 | |
| 33 | 67.4% | 61.2 | 2026-09-09 | |
| 34 | 66.0% | 62.5 | 2026-08-12 | |
| 35 | 66.0% | 57.4 | 2026-02-05 | |
| 36 | 65.6% | 58.4 | 2026-06-30 | |
| 37 | 64.6% | 60.8 | 2026-08-13 | |
| 38 | 64.6% | 60.6 | 2026-05-19 | |
| 39 | 62.8% | 63.1 | 2026-05-19 | |
| 40 | 59.6% | 60.6 | 2026-02-19 | |
| 41 | 59.2% | 62.3 | 2026-06-16 | |
| 42 | 59.0% | 62.0 | 2026-07-21 | |
| 43 | 58.6% | 49.8 | 2026-10-06 | |
| 44 | 57.5% | 59.4 | 2026-07-31 | |
| 45 | 57.2% | 59.3 | 2026-07-08 | |
| 46 | 57.2% | 55.4 | 2026-04-20 | |
| 47 | 55.8% | 54.2 | 2026-08-20 | |
| 48 | 55.8% | – | 2025-10-07 | |
| 49 | 55.4% | 57.9 | 2025-08-07 | |
| 50 | 54.7% | – | 2026-06-16 | |
| 51 | 54.0% | 55.8 | 2026-06-12 | |
| 52 | 53.0% | 61.6 | 2026-09-21 | |
| 53 | 51.2% | 57.0 | 2025-12-17 | |
| 54 | 51.2% | 56.3 | 2026-03-17 | |
| 55 | 46.7% | 54.1 | 2025-08-07 | |
| 56 | Inkling Smallxhighopen ↗ | 46.3% | 47.6 | 2026-07-15 |
| 57 | 44.9% | 58.6 | 2026-02-17 | |
| 58 | 44.9% | 48.4 | 2026-03-17 | |
| 59 | 42.8% | 57.0 | 2026-04-17 | |
| 60 | 42.5% | 48.0 | 2026-06-16 |
More maths benchmarks · All LLM benchmarks
Cite as: BenchLeader, “FrontierMath Tiers 1–3 leaderboard”, data as of 24 Oct 2026, https://www.benchleader.com/benchmarks/frontiermath_t1_3.
FrontierMath Tiers 1–3: questions
- What does FrontierMath Tiers 1–3 measure?
- FrontierMath is a private set of research-level mathematics problems written by professional mathematicians, each with a definite, automatically checkable answer. Tiers 1 to 3 range from hard undergraduate to problems that take a specialist hours. The problems are unpublished, so they cannot appear in training data. Scores are reported in percent of tasks solved; higher is better.
- Which AI model leads FrontierMath Tiers 1–3?
- GPT-6 Astra leads FrontierMath Tiers 1–3 with 93.7% as of 24 Oct 2026, ahead of GPT-6.1 Sol at 93.7%.
- How many models have FrontierMath Tiers 1–3 results?
- 118 model configurations have a FrontierMath Tiers 1–3 result on BenchLeader, all taken from Epoch AI Benchmarking Hub.
- Who runs FrontierMath Tiers 1–3 and how often is it updated?
- FrontierMath Tiers 1–3 is published by Epoch AI Benchmarking Hub. BenchLeader re-reads the published results once a day and records the date each result was published.
- Does FrontierMath Tiers 1–3 count toward the BenchLeader Index?
- Yes. FrontierMath Tiers 1–3 contributes to the maths category of the BenchLeader Index, normalised so that 50 is the average of the evaluated models.