MathArena (Apex, IMO, USAMO)
Evaluates models on newly released math competitions after release. Final-answer or human/LLM-judged proof scores.
Apex holds 12 problems and Apex Shortlist holds 47, both picked in August 2025. In May 2026 MathArena found no new problems hard enough for an Apex v2. Proof scores for IMO and USAMO depend on judges.
In the authors’ words
The rapid advancement of reasoning capabilities in large language models (LLMs) has led to notable improvements on mathematical benchmarks. However, many of the most commonly used evaluation datasets (e.g., AIME 2024) are widely available online, making it difficult to disentangle genuine reasoning from potential memorization. Furthermore, these benchmarks do not evaluate proof-writing capabilities, which are crucial for many mathematical tasks. To address this, we introduce MathArena, a new benchmark based on the following key insight: recurring math competitions provide a stream of high-quality, challenging problems that can be used for real-time evaluation of LLMs. By evaluating models as soon as new problems are released, we effectively eliminate the risk of contamination. Using this framework, we find strong signs of contamination in AIME 2024. Nonetheless, evaluations on harder competitions, such as CMIMC 2025, demonstrate impressive reasoning capabilities in top-performing models. MathArena is also the first benchmark for proof-writing capabilities. On IMO 2025, top models achieve slightly less than 40%, demonstrating both notable progress and significant room for improvement. So far, we have evaluated over 50 models across seven competitions, totaling 162 problems. As an evolving benchmark, MathArena will continue to track the progress of LLMs on newly released competitions, ensuring rigorous and up-to-date evaluation of mathematical reasoning.
- Level
- Competition The strongest students, in olympiad-style contests
- Scored
- Checked automatically A program checks the result against an answer key, unit tests or the expected final state.
- Answers
- Short answer A number, word or short string matched to a key.
Claude Opus 4.8 leads with 81.3% among models released by Jul 2026
Best score per model from the benchmark's own leaderboard, read on 2 Nov 2026. Where a model ran with several settings or harnesses, we keep its best. Every run is in the next chart.
The newest model with a score here came out in Jul 2026, and nobody has tested a newer one. Among the 20 highest-ranked models on the capability index, these have no score yet:
- GPT-6 Astra
- Claude Opus 5.5
- GPT-6.1 Terra
- GPT-6.1 Sol
- and 12 more
- 81.3 Claude Opus 4.8
- 80.2 GPT-5.5
- 69.8 GPT-5.4 Pro
- 65.6 Kimi K3
- 60.9
Gemini 3.1 Pro
- 54.2 GPT-5.4
- 40.6 Claude Opus 4.7
- 34.5 Claude Opus 4.6
- 32.3
Gemini 3.5 Flash
- 28.1
DeepSeek-V4-Pro
- 27.1
DeepSeek-V4-Flash
- 26.0
Gemini 3.6 Flash
- 24.0 Kimi K2.6
- 23.4
Gemini 3 Pro
- 19.8 GLM-5.2
- 15.6
Gemini 3 Flash
- 14.6
Step 3.7 Flash
- 13.5 GPT-5.2
- 13.5
Step 3.5 Flash
- 11.5 GLM-5.1
- 10.9 GLM-5
- 9.38
DeepSeek-V3.2-Speciale
- 8.85 Kimi K2.5
- 7.81
Nemotron 3 Super
- 5.21
Qwen3-235B-A22B-Thinking
- 5.21 Grok 4 Fast
- 5.21 Grok 4.1 Fast
- 4.17
Qwen3.5-35B-A3B
- 2.08 Grok 4
- 2.08
Qwen3-4B-Thinking-2507
- 2.08 GPT-5
- 2.08
DeepSeek-V3.2
- 2.08
Qwen3.5-27B
- 1.56 Claude Sonnet 4.5
- 1.56
QED-Nano
- 1.04
DeepSeek-R1
- 1.04 GLM-4.5
- 1.04 gpt-oss-120b
- 1.04 GPT-5 mini
- 1.04 GPT-5.1
- 0.52
Gemini 2.5 Pro
- 0.52
Qwen3-30B-A3B-Thinking
- 0.52
DeepSeek-V3.1
- 0.52
DeepSeek-V3.2-Exp
- 0.52 GLM-4.6
- 0.52
Qwen3.5-9B
- 0.0 Kimi K2 Thinking
- 1 Claude Opus 4.8 max 81.3%
- 2 GPT-5.5 xhigh 80.2%
- 3 GPT-5.4 Pro xhigh 69.8%
- 4 Kimi K3 thinking 65.6%
- 5
Gemini 3.1 Pro 60.9%
- 6 GPT-5.4 xhigh 54.2%
- 7 Claude Opus 4.7 xhigh 40.6%
- 8 Claude Opus 4.6 high 34.5%
- 9
Gemini 3.5 Flash 32.3%
- 10
DeepSeek-V4-Pro max 28.1%
- 11
DeepSeek-V4-Flash max 27.1%
- 12
Gemini 3.6 Flash 26%
- 13 Kimi K2.6 thinking 24%
- 14
Gemini 3 Pro 23.4%
- 15 GLM-5.2 19.8%
- 16
Gemini 3 Flash 15.6%
- 17
Step 3.7 Flash 14.6%
- 18 GPT-5.2 high 13.5%
- 19
Step 3.5 Flash 13.5%
- 20 GLM-5.1 11.5%
- 21 GLM-5 10.9%
- 22
DeepSeek-V3.2-Speciale 9.38%
- 23 Kimi K2.5 thinking 8.85%
- 24
Nemotron 3 Super 7.81%
- 25
Qwen3-235B-A22B-Thinking Jul 2025 5.21%
- 26 Grok 4 Fast 5.21%
- 27 Grok 4.1 Fast 5.21%
- 28
Qwen3.5-35B-A3B 4.17%
- 29 Grok 4 2.08%
- 30
Qwen3-4B-Thinking-2507 2.08%
- 31 GPT-5 high 2.08%
- 32
DeepSeek-V3.2 thinking 2.08%
- 33
Qwen3.5-27B 2.08%
- 34 Claude Sonnet 4.5 thinking 1.56%
- 35
QED-Nano 1.56%
- 36
DeepSeek-R1 May 2025 1.04%
- 37 GLM-4.5 1.04%
- 38 gpt-oss-120b high 1.04%
- 39 GPT-5 mini high 1.04%
- 40 GPT-5.1 high 1.04%
- 41
Gemini 2.5 Pro Jun 2025 0.52%
- 42
Qwen3-30B-A3B-Thinking Jul 2025 0.52%
- 43
DeepSeek-V3.1 thinking 0.52%
- 44
DeepSeek-V3.2-Exp thinking 0.52%
- 45 GLM-4.6 0.52%
- 46
Qwen3.5-9B 0.52%
- 47 Kimi K2 Thinking 0%
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | Claude Opus 4.8 | 81.3% | max | May 2026 | Official leaderboard |
| 2 | GPT-5.5 | 80.2% | xhigh | Apr 2026 | Official leaderboard |
| 3 | GPT-5.4 Pro | 69.8% | xhigh | Mar 2026 | Official leaderboard |
| 4 | Kimi K3 | 65.6% | thinking | Jul 2026 | Official leaderboard |
| 5 | | 60.9% | Feb 2026 | Official leaderboard | |
| 6 | GPT-5.4 | 54.2% | xhigh | Mar 2026 | Official leaderboard |
| 7 | Claude Opus 4.7 | 40.6% | xhigh | Apr 2026 | Official leaderboard |
| 8 | Claude Opus 4.6 | 34.5% | high | Feb 2026 | Official leaderboard |
| 9 | | 32.3% | May 2026 | Official leaderboard | |
| 10 | | 28.1% | max | Apr 2026 | Official leaderboard |
| 11 | | 27.1% | max | Apr 2026 | Official leaderboard |
| 12 | | 26% | Jul 2026 | Official leaderboard | |
| 13 | Kimi K2.6 | 24% | thinking | Apr 2026 | Official leaderboard |
| 14 | | 23.4% | Nov 2025 | Official leaderboard | |
| 15 | GLM-5.2 | 19.8% | Jun 2026 | Official leaderboard | |
| 16 | | 15.6% | Dec 2025 | Official leaderboard | |
| 17 | | 14.6% | May 2026 | Official leaderboard | |
| 18 | GPT-5.2 | 13.5% | high | Dec 2025 | Official leaderboard |
| 19 | | 13.5% | Feb 2026 | Official leaderboard | |
| 20 | GLM-5.1 | 11.5% | Apr 2026 | Official leaderboard | |
| 21 | GLM-5 | 10.9% | Feb 2026 | Official leaderboard | |
| 22 | | 9.38% | Dec 2025 | Official leaderboard | |
| 23 | Kimi K2.5 | 8.85% | thinking | Jan 2026 | Official leaderboard |
| 24 | | 7.81% | Mar 2026 | Official leaderboard | |
| 25 | | 5.21% | Jul 2025 | Official leaderboard | |
| 26 | Grok 4 Fast | 5.21% | Sep 2025 | Official leaderboard | |
| 27 | Grok 4.1 Fast | 5.21% | Nov 2025 | Official leaderboard | |
| 28 | | 4.17% | Feb 2026 | Official leaderboard | |
| 29 | Grok 4 | 2.08% | Jul 2025 | Official leaderboard | |
| 30 | | 2.08% | Aug 2025 | Official leaderboard | |
| 31 | GPT-5 | 2.08% | high, MathArena agent | Aug 2025 | Official leaderboard |
| 32 | | 2.08% | thinking | Dec 2025 | Official leaderboard |
| 33 | | 2.08% | Feb 2026 | Official leaderboard | |
| 34 | Claude Sonnet 4.5 | 1.56% | thinking | Sep 2025 | Official leaderboard |
| 35 | | 1.56% | Feb 2026 | Official leaderboard | |
| 36 | | 1.04% | May 2025 | Official leaderboard | |
| 37 | GLM-4.5 | 1.04% | Aug 2025 | Official leaderboard | |
| 38 | gpt-oss-120b | 1.04% | high | Aug 2025 | Official leaderboard |
| 39 | GPT-5 mini | 1.04% | high | Aug 2025 | Official leaderboard |
| 40 | GPT-5.1 | 1.04% | high | Nov 2025 | Official leaderboard |
| 41 | | 0.52% | Jun 2025 | Official leaderboard | |
| 42 | | 0.52% | Jul 2025 | Official leaderboard | |
| 43 | | 0.52% | thinking | Aug 2025 | Official leaderboard |
| 44 | | 0.52% | thinking | Sep 2025 | Official leaderboard |
| 45 | GLM-4.6 | 0.52% | Sep 2025 | Official leaderboard | |
| 46 | | 0.52% | Feb 2026 | Official leaderboard | |
| 47 | Kimi K2 Thinking | 0% | Nov 2025 | Official leaderboard |
Labs report scores for 13 models in their cards. We plot every source in the charts below.
The best score, 81.3%, costs $4.59 a task
Runs on the cost frontier score higher than any run that's cheaper. GPT-5.5 at xhigh comes within 1 points of the best for $1.42 a task, 3 times cheaper. The costs are the leaderboard's own estimates, so compare them only within this benchmark.
| Model | Effort | Harness | Score | Cost per task | Output tokens |
|---|---|---|---|---|---|
| Claude Opus 4.8 | max | 81.3% | $4.59 | 183,562 | |
| GPT-5.5 | xhigh | 80.2% | $1.42 | 47,166 | |
| GPT-5.4 Pro | xhigh | 69.8% | $8.65 | 46,663 | |
| Kimi K3 | thinking | 65.6% | $1.11 | 74,265 | |
| | 60.9% | $0.41 | 33,915 | ||
| GPT-5.4 | xhigh | 54.2% | $1.03 | 67,637 | |
| Claude Opus 4.7 | xhigh | 40.6% | $2.10 | 83,922 | |
| Claude Opus 4.6 | high | 34.5% | $2.36 | 94,457 | |
| | 32.3% | $0.30 | 32,815 | ||
| | max | 28.1% | $0.42 | 120,214 | |
| | max | 27.1% | $0.05 | 179,799 | |
| | 26% | $0.19 | 25,665 | ||
| Kimi K2.6 | thinking | 24% | $0.32 | 80,726 | |
| | 23.4% | $0.28 | 23,601 | ||
| GLM-5.2 | 19.8% | $0.18 | 43,072 | ||
| | 15.6% | $0.10 | 34,852 | ||
| | 14.6% | $0.07 | 248,920 | ||
| GPT-5.2 | high | 13.5% | $1.00 | 71,416 | |
| | 13.5% | $0.04 | 149,104 | ||
| GLM-5.1 | 11.5% | $0.27 | 85,816 | ||
| GLM-5 | 10.9% | $0.25 | 78,269 | ||
| | 9.38% | $0.03 | 73,369 | ||
| Kimi K2.5 | thinking | 8.85% | $0.18 | 60,555 | |
| | 7.81% | 101,105 | |||
| | 5.21% | $0.05 | 42,861 | ||
| Grok 4 Fast | 5.21% | $0.01 | 22,794 | ||
| Grok 4.1 Fast | 5.21% | $0.01 | 26,208 | ||
| | 4.17% | $0.09 | 65,584 | ||
| Grok 4 | 2.08% | $0.52 | 34,485 | ||
| | 2.08% | $0.008 | 28,284 | ||
| GPT-5 | high | MathArena agent | 2.08% | $3.83 | 376,117 |
| | thinking | 2.08% | $0.02 | 43,901 | |
| | 2.08% | $0.10 | 61,939 | ||
| Claude Sonnet 4.5 | thinking | 1.56% | $0.38 | 25,293 | |
| | 1.56% | 91,501 | |||
| | 1.04% | $0.08 | 37,304 | ||
| GLM-4.5 | 1.04% | $0.08 | 34,285 | ||
| gpt-oss-120b | high | 1.04% | $0.03 | 45,365 | |
| GPT-5 | high | 1.04% | $0.46 | 46,122 | |
| GPT-5 mini | high | 1.04% | $0.07 | 34,849 | |
| GPT-5.1 | high | 1.04% | $0.55 | 54,816 | |
| | 0.52% | $0.31 | 31,181 | ||
| | 0.52% | $0.009 | 30,727 | ||
| | thinking | 0.52% | $0.07 | 33,355 | |
| | thinking | 0.52% | $0.01 | 33,813 | |
| GLM-4.6 | 0.52% | $0.07 | 31,749 | ||
| | 0.52% | $0.009 | 59,074 | ||
| Kimi K2 Thinking | 0% | $0.15 | 58,028 |
9 models have held number one since its release in Feb 2025
Lab claims count from the day the card came out, independent runs from the model’s release. We draw one row each for the benchmark’s own leaderboard and what labs claim in their cards.
The best score passed 85% in Apr 2026
All the scores we have, one dot each, so a model tested at several settings appears more than once.
4 labs put it in a launch post in the last six months
Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.
| Date | Launch post | Score | As the post writes it |
|---|---|---|---|
| 17 Oct 2026 | 72.1 | Apex Bench v1.1 | |
| 15 Oct 2026 | 88.4 | APEX shortlist | |
| 10 Sep 2026 | 65.6 | MathArena Apex (Pass@1) | |
| 28 Aug 2026 | 74.2 | MathArena Apex 2025 | |
| 2 Jul 2026 | 38.7 | MathArena Apex | |
| 4 Jun 2026 | 74.9 | Apex-Shortlist (no tools); with tools 84.8 | |
| 1 Jun 2026 | 22.7 | Apex | |
| 20 May 2026 | 44.5 | Apex | |
| 24 Apr 2026 | 90.2 | Apex Shortlist (Pass@1) | |
| 24 Apr 2026 | 38.3 | Apex (Pass@1) | |
| 14 Feb 2026 | 20.3 | MathArenaApex 20.3 (shortlist 82.1) | |
| 18 Nov 2025 | 23.4 | MathArena Apex |
7 system cards report it, from 3 labs
Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| 15 Oct 2026 | | 88.4 | Apex-Shortlist, no tools, mean of 16 (Table 10) | Capabilities |
| 10 Sep 2026 | | 65.6 | MathArena Apex (Pass@1) (Table 3) | Capabilities |
| 23 Jun 2026 | | 31.3 | MathArena Apex (Table 11) | Capabilities |
| 9 Jun 2026 | | 74.9 | Apex-Shortlist (no tools), 84.8 with tools (Table 10) | Capabilities |
| 26 Apr 2026 | | 38.3 | Apex (Pass@1), DS-V4-Pro Max (Table 6) | Capabilities |
| 26 Apr 2026 | | 33 | Apex (Pass@1), DeepSeek-V4-Flash Max (Table 7) | Capabilities |
| 14 Feb 2026 | | 20.3 | MathArenaApex 20.3, MathArenaApex (shortlist) 82.1 (Table 3) | Capabilities |
More in Math
- IMO-AnswerBench In use 400 olympiad problems with short verifiable answers, robustified against memorization. Scored by answer match. GLM-5.2 91%
- AIME 2026 In use Models solve the 30 integer-answer problems from the 2026 AIME I and II math competitions. Scored by exact answer match. GPT-5.5 100%
- 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%
- PolyMath In use Models solve 9,000 parallel math problems in 18 languages across four difficulty levels, from school math to frontier math. Final answers are checked.
Qwen3.7-Max 86.5%
- USAMO 2026 In use Models write full proofs for the six problems of the 2026 USA Mathematical Olympiad. Judges grade each proof from 0 to 7 against rubrics. GPT-5.5 98.2%
- ArXivMath In use Final-answer research-level math problems extracted monthly from recent arXiv papers and filtered to be self-contained. GPT-6.1 Sol 94.2%