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.
- Made by
- ETH Zurich SRI Lab
- Released
- February 2025
- Kind
- Competition problems with answers
- Level
- Competition
- Scored
- Checked automatically
- Answers
- Short answer
- Tasks
- All public
- Strongest model tested
- GPT-5.4 Pro #19 on the capability index
- Last in a launch post
- November 2026
- Last model added
- November 2026
- Scores refreshed
- November 12th, 2026
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.
Claude Opus 4.8 leads with 81.3% among models released by July 2026
Best score per model from the benchmark's own leaderboard, read on November 12th, 2026. Where a model ran with several settings or harnesses, we keep its best. Every run is in the next chart.
Claude Opus 4.8 leads with 81.3%, claims included
Best score per model from every source, including labs’ own numbers and claims Epoch AI collected from reports and papers. Labs pick their own settings, so a claim can beat an independent run of the same model.
The newest model with a score here came out in July 2026, and nobody has tested a newer one. Among the 20 highest-ranked models on the capability index, these have no score yet:
- Claude Fable 5.2
-
Gemini 4 Carbon
- GPT-6 Astra
- Claude Opus 5.5
- and 14 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 max 65.6%
- 5
Gemini 3.1 Pro high 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 high 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 high 24%
- 14
Gemini 3 Pro 23.4%
- 15 GLM-5.2 max 19.8%
- 16
Gemini 3 Flash high 15.6%
- 17
Step 3.7 Flash high 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 high 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 reasoning 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%
Source: Official MathArena (Apex, IMO, USAMO) leaderboard
- 81.3 Claude Opus 4.8
- 80.2 GPT-5.5
- 74.2
Tencent Hy4 preview
- 72.1
DeepSeek V4.1 Flash 1017
- 69.8 GPT-5.4 Pro
- 65.6 Kimi K3
- 65.6
DeepSeek V4.1 Flash
- 63.5
Inkling 2 Small
- 60.9
Gemini 3.1 Pro
- 54.2 GPT-5.4
- 44.5
Qwen3.7-Max
- 40.6 Claude Opus 4.7
- 38.7
Tencent Hy3
- 38.3
DeepSeek-V4-Pro
- 34.5 Claude Opus 4.6
- 33.0
DeepSeek-V4-Flash
- 32.3
Gemini 3.5 Flash
- 31.3
Seed2.1 Pro
- 26.0
Gemini 3.6 Flash
- 24.0 Kimi K2.6
- 23.4
Gemini 3 Pro
- 22.7
Qwen3.7-Plus
- 20.3
Seed2.0 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
Tencent Hy4 preview 74.2%
- 4
DeepSeek V4.1 Flash 1017 72.1%
- 5 GPT-5.4 Pro xhigh 69.8%
- 6 Kimi K3 max 65.6%
- 7
DeepSeek V4.1 Flash 65.6%
- 8
Inkling 2 Small 63.5%
- 9
Gemini 3.1 Pro high 60.9%
- 10 GPT-5.4 xhigh 54.2%
- 11
Qwen3.7-Max 44.5%
- 12 Claude Opus 4.7 xhigh 40.6%
- 13
Tencent Hy3 38.7%
- 14
DeepSeek-V4-Pro 38.3%
- 15 Claude Opus 4.6 high 34.5%
- 16
DeepSeek-V4-Flash 33%
- 17
Gemini 3.5 Flash high 32.3%
- 18
Seed2.1 Pro 31.3%
- 19
Gemini 3.6 Flash 26%
- 20 Kimi K2.6 high 24%
- 21
Gemini 3 Pro 23.4%
- 22
Qwen3.7-Plus 22.7%
- 23
Seed2.0 Pro 20.3%
- 24 GLM-5.2 max 19.8%
- 25
Gemini 3 Flash high 15.6%
- 26
Step 3.7 Flash high 14.6%
- 27 GPT-5.2 high 13.5%
- 28
Step 3.5 Flash 13.5%
- 29 GLM-5.1 11.5%
- 30 GLM-5 10.9%
- 31
DeepSeek-V3.2-Speciale 9.38%
- 32 Kimi K2.5 high 8.85%
- 33
Nemotron 3 Super 7.81%
- 34
Qwen3-235B-A22B-Thinking Jul 2025 5.21%
- 35 Grok 4 Fast 5.21%
- 36 Grok 4.1 Fast reasoning 5.21%
- 37
Qwen3.5-35B-A3B 4.17%
- 38 Grok 4 2.08%
- 39
Qwen3-4B-Thinking-2507 2.08%
- 40 GPT-5 high 2.08%
- 41
DeepSeek-V3.2 thinking 2.08%
- 42
Qwen3.5-27B 2.08%
- 43 Claude Sonnet 4.5 thinking 1.56%
- 44
QED-Nano 1.56%
- 45
DeepSeek-R1 May 2025 1.04%
- 46 GLM-4.5 1.04%
- 47 gpt-oss-120b high 1.04%
- 48 GPT-5 mini high 1.04%
- 49 GPT-5.1 high 1.04%
- 50
Gemini 2.5 Pro Jun 2025 0.52%
- 51
Qwen3-30B-A3B-Thinking Jul 2025 0.52%
- 52
DeepSeek-V3.1 thinking 0.52%
- 53
DeepSeek-V3.2-Exp thinking 0.52%
- 54 GLM-4.6 0.52%
- 55
Qwen3.5-9B 0.52%
- 56 Kimi K2 Thinking 0%
Sources: Official MathArena (Apex, IMO, USAMO) leaderboard and labs’ model cards
| # | 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% | max | Jul 2026 | Official leaderboard |
| 5 | | 60.9% | high | 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% | high | 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% | high | Apr 2026 | Official leaderboard |
| 14 | | 23.4% | Nov 2025 | Official leaderboard | |
| 15 | GLM-5.2 | 19.8% | max | Jun 2026 | Official leaderboard |
| 16 | | 15.6% | high | Dec 2025 | Official leaderboard |
| 17 | | 14.6% | high | 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% | high | 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% | reasoning | 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 |
| # | 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 | | 74.2% | Aug 2026 | Lab model card | |
| 4 | | 72.1% | Oct 2026 | Lab model card | |
| 5 | GPT-5.4 Pro | 69.8% | xhigh | Mar 2026 | Official leaderboard |
| 6 | Kimi K3 | 65.6% | max | Jul 2026 | Official leaderboard |
| 7 | | 65.6% | Sep 2026 | Lab model card | |
| 8 | | 63.5% | Nov 2026 | Lab model card | |
| 9 | | 60.9% | high | Feb 2026 | Official leaderboard |
| 10 | GPT-5.4 | 54.2% | xhigh | Mar 2026 | Official leaderboard |
| 11 | | 44.5% | May 2026 | Lab model card | |
| 12 | Claude Opus 4.7 | 40.6% | xhigh | Apr 2026 | Official leaderboard |
| 13 | | 38.7% | Jul 2026 | Lab model card | |
| 14 | | 38.3% | Apr 2026 | Lab model card | |
| 15 | Claude Opus 4.6 | 34.5% | high | Feb 2026 | Official leaderboard |
| 16 | | 33% | Apr 2026 | Lab model card | |
| 17 | | 32.3% | high | May 2026 | Official leaderboard |
| 18 | | 31.3% | Jun 2026 | Lab model card | |
| 19 | | 26% | Jul 2026 | Official leaderboard | |
| 20 | Kimi K2.6 | 24% | high | Apr 2026 | Official leaderboard |
| 21 | | 23.4% | Nov 2025 | Official leaderboard | |
| 22 | | 22.7% | Jun 2026 | Lab model card | |
| 23 | | 20.3% | Feb 2026 | Lab model card | |
| 24 | GLM-5.2 | 19.8% | max | Jun 2026 | Official leaderboard |
| 25 | | 15.6% | high | Dec 2025 | Official leaderboard |
| 26 | | 14.6% | high | May 2026 | Official leaderboard |
| 27 | GPT-5.2 | 13.5% | high | Dec 2025 | Official leaderboard |
| 28 | | 13.5% | Feb 2026 | Official leaderboard | |
| 29 | GLM-5.1 | 11.5% | Apr 2026 | Official leaderboard | |
| 30 | GLM-5 | 10.9% | Feb 2026 | Official leaderboard | |
| 31 | | 9.38% | Dec 2025 | Official leaderboard | |
| 32 | Kimi K2.5 | 8.85% | high | Jan 2026 | Official leaderboard |
| 33 | | 7.81% | Mar 2026 | Official leaderboard | |
| 34 | | 5.21% | Jul 2025 | Official leaderboard | |
| 35 | Grok 4 Fast | 5.21% | Sep 2025 | Official leaderboard | |
| 36 | Grok 4.1 Fast | 5.21% | reasoning | Nov 2025 | Official leaderboard |
| 37 | | 4.17% | Feb 2026 | Official leaderboard | |
| 38 | Grok 4 | 2.08% | Jul 2025 | Official leaderboard | |
| 39 | | 2.08% | Aug 2025 | Official leaderboard | |
| 40 | GPT-5 | 2.08% | high, MathArena agent | Aug 2025 | Official leaderboard |
| 41 | | 2.08% | thinking | Dec 2025 | Official leaderboard |
| 42 | | 2.08% | Feb 2026 | Official leaderboard | |
| 43 | Claude Sonnet 4.5 | 1.56% | thinking | Sep 2025 | Official leaderboard |
| 44 | | 1.56% | Feb 2026 | Official leaderboard | |
| 45 | | 1.04% | May 2025 | Official leaderboard | |
| 46 | GLM-4.5 | 1.04% | Aug 2025 | Official leaderboard | |
| 47 | gpt-oss-120b | 1.04% | high | Aug 2025 | Official leaderboard |
| 48 | GPT-5 mini | 1.04% | high | Aug 2025 | Official leaderboard |
| 49 | GPT-5.1 | 1.04% | high | Nov 2025 | Official leaderboard |
| 50 | | 0.52% | Jun 2025 | Official leaderboard | |
| 51 | | 0.52% | Jul 2025 | Official leaderboard | |
| 52 | | 0.52% | thinking | Aug 2025 | Official leaderboard |
| 53 | | 0.52% | thinking | Sep 2025 | Official leaderboard |
| 54 | GLM-4.6 | 0.52% | Sep 2025 | Official leaderboard | |
| 55 | | 0.52% | Feb 2026 | Official leaderboard | |
| 56 | Kimi K2 Thinking | 0% | Nov 2025 | Official leaderboard |
Labs report scores for 12 models in their cards. Switch the scores above to rank them together.
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.
Source: Official MathArena (Apex, IMO, USAMO) leaderboard
| 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 | max | 65.6% | $1.11 | 74,265 | |
| | high | 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 | |
| | high | 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 | high | 24% | $0.32 | 80,726 | |
| | 23.4% | $0.28 | 23,601 | ||
| GLM-5.2 | max | 19.8% | $0.18 | 43,072 | |
| | high | 15.6% | $0.10 | 34,852 | |
| | high | 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 | high | 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 | reasoning | 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 on the official leaderboard since its release in February 2025 9 models have held number one with claims included since its release in February 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.
Sources: Official MathArena (Apex, IMO, USAMO) leaderboard and labs’ model cards
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Sources: Official MathArena (Apex, IMO, USAMO) leaderboard and labs’ model cards
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 |
|---|---|---|---|
| Nov 5, 2026 | 63.5 | Apex 2025 | |
| Oct 17, 2026 | 72.1 | Apex Bench v1.1 | |
| Sep 10, 2026 | 65.6 | MathArena Apex (Pass@1) | |
| Aug 28, 2026 | 74.2 | MathArena Apex 2025 | |
| Jul 2, 2026 | 38.7 | MathArena Apex | |
| Jun 1, 2026 | 22.7 | Apex | |
| May 20, 2026 | 44.5 | Apex | |
| Apr 24, 2026 | 33 | Apex (Pass@1), V4-Flash Max | |
| Apr 24, 2026 | 38.3 | Apex (Pass@1) | |
| Feb 14, 2026 | 20.3 | MathArenaApex 20.3 (shortlist 82.1) | |
| Nov 18, 2025 | 23.4 | MathArena Apex |
5 system cards report it, from 2 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 |
|---|---|---|---|---|
| Sep 10, 2026 | | 65.6 | MathArena Apex (Pass@1) (Table 3) | Capabilities |
| Jun 23, 2026 | | 31.3 | MathArena Apex (Table 11) | Capabilities |
| Apr 26, 2026 | | 38.3 | Apex (Pass@1), DS-V4-Pro Max (Table 6) | Capabilities |
| Apr 26, 2026 | | 33 | Apex (Pass@1), DeepSeek-V4-Flash Max (Table 7) | Capabilities |
| Feb 14, 2026 | | 20.3 | MathArenaApex 20.3, MathArenaApex (shortlist) 82.1 (Table 3) | Capabilities |
The lab's number comes out ahead in 2 of 2 pairs that differ
Each score a lab reported for its own model, beside the same model's best score on the leaderboard. Gaps mostly come from different harnesses, effort levels and task subsets. 1 of them match, which usually means one side copied the other. Every benchmark.
| Model | Lab says | Board says | Gap |
|---|---|---|---|
| | 38.3% Apex (Pass@1) | 28.1% Leaderboard, max | +10 pts |
| | 33% Apex (Pass@1), V4-Flash Max | 27.1% Leaderboard, max | +5.9 pts |
| | 23.4% MathArena Apex | 23.4% Leaderboard | Same |
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