Benchmark Almanac

MathBench

GPT-4o May 2024 70.9% leads since May 2024
Not in model cards

Models answer 3,709 math questions in five stages from basic arithmetic to college, in Chinese and English. Each stage also tests theory knowledge, and Circular Evaluation reshuffles answer options to check consistency.

Accepted to ACL 2024 Findings. The repository has about 118 stars.

Released
May 2024
Kind
Word problems
Level
University
Scored
Checked automatically
Answers
Multiple choice
Tasks
All public
Strongest model tested
GPT-4o May 2024 #161 on the capability index
Last model added
June 2024
Scores refreshed
November 12th, 2026

In the authors’ words

Recent advancements in large language models (LLMs) have showcased significant improvements in mathematics. However, traditional math benchmarks like GSM8k offer a unidimensional perspective, falling short in providing a holistic assessment of the LLMs' math capabilities. To address this gap, we introduce MathBench, a new benchmark that rigorously assesses the mathematical capabilities of large language models. MathBench spans a wide range of mathematical disciplines, offering a detailed evaluation of both theoretical understanding and practical problem-solving skills. The benchmark progresses through five distinct stages, from basic arithmetic to college mathematics, and is structured to evaluate models at various depths of knowledge. Each stage includes theoretical questions and application problems, allowing us to measure a model's mathematical proficiency and its ability to apply concepts in practical scenarios. MathBench aims to enhance the evaluation of LLMs' mathematical abilities, providing a nuanced view of their knowledge understanding levels and problem solving skills in a bilingual context. The project is released at https://github.com/open-compass/MathBench .

Abstract of MathBench: Evaluating the Theory and Application Proficiency of LLMs with a Hierarchical Mathematics Benchmark (arXiv:2405.12209, CC0)
33
Entries on its own leaderboard, 21 models we track

GPT-4o leads with 70.9% among models released by June 2024

Best score per entry from the benchmark's own leaderboard, read on November 12th, 2026. Where a model ran with several settings or harnesses, we keep its best. Names in gray aren't in our model list: fine-tunes, agent systems, products and older models. They don't count toward leaders.

The newest model with a score here came out in June 2024, and nobody has tested a newer one. Among the 20 highest-ranked models on the capability index, these have no score yet:

  1. 1 GPT-4o May 2024 70.9%
  2. 2 Qwen2-72B 67%
  3. 3 Claude 3 Opus 63%
  4. 4 DeepSeek-V2 (MoE-236B, May 2024) 59.9%
  5. 5 Qwen-Max-0428 59.2%
  6. 6 GPT-4 Turbo (Jan 2024) 58.8%
  7. 7 Qwen1.5-110B 58.4%
  8. 8 Llama 3-70B 56.4%
  9. 9 Qwen2-7B-Instruct 53.4%
  10. 10 Yi-1.5-34B 52.2%
  11. 11 GLM-4 51.3%
  12. 12 Yi-1.5-9B-Chat 51.1%
  13. 13 DeepSeek-Math-7B-RL 50.3%
  14. 14 Qwen-72B-Chat 49.7%
  15. 15 GLM-4-9B-Chat 47.7%
  16. 16 InternLM2-Chat-20B 42.1%
  17. 17 InternLM2-Chat-Math-20B 41.9%
  18. 18 DeepSeekMath-7B-Instruct 40.9%
  19. 19 DeepSeek LLM 67B 40.3%
  20. 20 Qwen-14B 39.5%
  21. 21 InternLM2-Chat-Math-7B 37.7%
  22. 22 Llama 3-8B 36.7%
  23. 23 InternLM2-Chat-7B 34.1%
  24. 24 Yi-34B 31.6%
  25. 25 Qwen-7B 27.7%
  26. 26 Metamath-Llemma-7B 24.9%
  27. 27 MammoTH-70B 24.7%
  28. 28 DeepSeek-7B-Chat 22.3%
  29. 29 Baichuan2-13B-Chat 20.9%
  30. 30 ChatGLM3-6B 19.9%
  31. 31 MammoTH-13B 18.5%
  32. 32 Yi-6B-Chat 17.2%
  33. 33 MammoTH-7B 11.3%

Source: Official MathBench leaderboard

#EntryScoreSettingDateSource
1 GPT-4o May 2024 70.9% May 2024 Official leaderboard
2 Qwen2-72B 67% Jun 2024 Official leaderboard
3 Claude 3 Opus 63% Feb 2024 Official leaderboard
4 DeepSeek-V2 (MoE-236B, May 2024) 59.9% May 2024 Official leaderboard
5 Qwen-Max-0428 59.2% Official leaderboard
6 GPT-4 Turbo (Jan 2024) 58.8% Jan 2024 Official leaderboard
7 Qwen1.5-110B 58.4% Apr 2024 Official leaderboard
8 Llama 3-70B 56.4% Apr 2024 Official leaderboard
9 Qwen2-7B-Instruct 53.4% Jun 2024 Official leaderboard
10 Yi-1.5-34B 52.2% May 2024 Official leaderboard
11 GLM-4 51.3% Jan 2024 Official leaderboard
12 Yi-1.5-9B-Chat 51.1% May 2024 Official leaderboard
13 DeepSeek-Math-7B-RL 50.3% Official leaderboard
14 Qwen-72B-Chat 49.7% Official leaderboard
15 GLM-4-9B-Chat 47.7% Jun 2024 Official leaderboard
16 InternLM2-Chat-20B 42.1% Official leaderboard
17 InternLM2-Chat-Math-20B 41.9% Official leaderboard
18 DeepSeekMath-7B-Instruct 40.9% Feb 2024 Official leaderboard
19 DeepSeek LLM 67B 40.3% Nov 2023 Official leaderboard
20 Qwen-14B 39.5% Sep 2023 Official leaderboard
21 InternLM2-Chat-Math-7B 37.7% Official leaderboard
22 Llama 3-8B 36.7% Apr 2024 Official leaderboard
23 InternLM2-Chat-7B 34.1% Official leaderboard
24 Yi-34B 31.6% Nov 2023 Official leaderboard
25 Qwen-7B 27.7% Sep 2023 Official leaderboard
26 Metamath-Llemma-7B 24.9% Official leaderboard
27 MammoTH-70B 24.7% Official leaderboard
28 DeepSeek-7B-Chat 22.3% Official leaderboard
29 Baichuan2-13B-Chat 20.9% Sep 2023 Official leaderboard
30 ChatGLM3-6B 19.9% Oct 2023 Official leaderboard
31 MammoTH-13B 18.5% Official leaderboard
32 Yi-6B-Chat 17.2% Nov 2023 Official leaderboard
33 MammoTH-7B 11.3% Official leaderboard

2 models have held number one on the official leaderboard since its release in May 2024

Lab claims count from the day the card came out, independent runs from the model’s release.

Anthropic OpenAI
Own leaderboard Not tested since Jun 2024
GPT-4o 70.9%

Source: Official MathBench leaderboard

Scores over time

All the scores we have, one dot each, so a model tested at several settings appears more than once.

On the benchmark’s own leaderboard Best so far
0% 20% 40% 60% 80% 100% 2024 Near the ceiling (85%) GPT-4o Claude 3 Opus GPT-4 Turbo (Jan 2024) GLM-4 DeepSeek LLM 67B Baichuan2-13B-Chat 0% 20% 40% 60% 80% 100% 2024 Near the ceiling (85%) GPT-4o Claude 3 Opus

Source: Official MathBench leaderboard

No lab model card reports it yet

We read the headline results of 522 launch posts from 52 labs, and none of them list this benchmark.

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  • HMMT 2026 In use Models solve the 33 final-answer problems from the February 2026 Harvard-MIT Mathematics Tournament. Scored by exact answer match. GPT-5.5 98.5%
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