Benchmarks / Math

ArXivMath 08/2026 (MathArena)

Research-level math problems with a checkable final answer, drawn from arXiv papers submitted in August 2026; each edition is restricted to papers published within the last month to reduce training-data contamination. Maintained by MathArena. Score: Accuracy (average performance on the competition) with a 95% confidence interval (normal approximation).

11models
–Open Index weight
–last updated

ArXivMath 08/2026 (MathArena)

Higher is better · best effort per model

Chart settings
11 of 11 selected

full table below

#ModelEffortScoreCost / taskHarness
1GPT-6.1 Solmax96.5%––
2GPT-6 Solmax93.0%––
3GPT-6 Astramax88.6%––
4Fable 5.1high87.7%––
5Opus 5.5high86.0%––
6Qwen 3.8 Maxmax57.9%––
7Grok 4.7xhigh46.5%––
8Muse Spark 1.3max45.6%––
9DeepSeek V4.1 Flashmax43.9%––
10Gemini 3.8 Flashmax40.4%––
11Kimi K3max38.6%––