HMMT 2025
Models answer the 30 problems from the February 2025 Harvard-MIT Mathematics Tournament. Final answers are checked against the official answers.
Model cards use the MathArena version of the February contest, often averaged over many samples.
- Released
- February 2025
- Kind
- Competition problems with answers
- Level
- Competition
- Scored
- Checked automatically
- Answers
- Short answer
- Tasks
- All public
- Strongest model tested
- GPT-5.2 Pro #31 on the capability index
- Last in a launch post
- August 2026, dropped after it saturated
- Last model added
- August 2026
- Scores refreshed
- November 12th, 2026
3 models share the top score of 100% among models released by August 2026
Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.
GPT-5.2 leads with 100% across all independent runs
Best score per model across MathArena’s leaderboard, Epoch AI’s own runs and any board Epoch AI copied. Each bar and row names its source.
GPT-5 leads with 100%, 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 August 2026, and nobody has reported 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 16 more
- 100.0 GPT-5
- 100.0
Qwen3-Max
- 100.0 GPT-5.2 Pro
- 99.2
DeepSeek-V3.2-Speciale
- 98.4
Step 3.5 Flash
- 97.9 GLM-5
- 97.5
LongCat-Flash-Thinking-2601
- 97.3
Seed2.0 Pro
- 97.1 GLM-4.7
- 96.7 Grok 4 Heavy
- 96.7
Qwen 3.6 Plus
- 95.4 Kimi K2.5
- 94.8
Qwen3.5 397B-A17B
- 94.6
Nemotron-Cascade 2 30B-A3B
- 93.9 Grok 4
- 93.8
Qwen3.6 27B
- 93.7
Nemotron 3 Super
- 93.3 Grok 4 Fast
- 92.5
DeepSeek-V3.2
- 92.0
Qwen3.5-27B
- 91.4
Qwen3.5-122B-A10B
- 90.7
Qwen 3.6 35B-A3B
- 89.7
Seed1.8
- 89.4 Kimi K2 Thinking
- 89.2 Granite 4.2 30B
- 89.0
Qwen3.5-35B-A3B
- 87.8 GPT-5 mini
- 86.7
Ring-1T
- 85.8
Tencent HY 2.0 Think
- 85.8 Sarvam 105B
- 84.4 MiMo-V2-Flash
- 84.2
DeepSeek-V3.1
- 83.9
Qwen3-235B-A22B-Thinking
- 83.7
LongCat-Flash-Thinking
- 83.6
DeepSeek-V3.2-Exp
- 83.2
Qwen3.5-9B
- 79.6
ERNIE 5.0
- 79.4
DeepSeek-R1
- 78.2
STEP3-VL-10B
- 77.4
Qwen3-VL-235B-A22B
- 75.6 GPT-5 nano
- 74.0
Qwen3.5-4B
- 73.9
Qwen3-Next-80B-A3B
- 73.3
Solar Open 100B
- 73.3 Sarvam 30B
- 72.9
EXAONE 4.0 32B
- 70.2
Qwen3-Coder-Next
- 70.0
Step 3
- 67.5
Ministral 3 14B
- 64.9
Falcon H1R 7B
- 53.6
Phi-4-Reasoning-plus
- 43.8
Phi-4-reasoning
- 38.8 Kimi K2
- 22.9
Qwen3.5-2B
- 1 GPT-5 100%
- 2
Qwen3-Max 100%
- 3 GPT-5.2 Pro 100%
- 4
DeepSeek-V3.2-Speciale 99.2%
- 5
Step 3.5 Flash 98.4%
- 6 GLM-5 97.9%
- 7
LongCat-Flash-Thinking-2601 97.5%
- 8
Seed2.0 Pro 97.3%
- 9 GLM-4.7 97.1%
- 10 Grok 4 Heavy 96.7%
- 11
Qwen 3.6 Plus 96.7%
- 12 Kimi K2.5 95.4%
- 13
Qwen3.5 397B-A17B 94.8%
- 14
Nemotron-Cascade 2 30B-A3B 94.6%
- 15 Grok 4 93.9%
- 16
Qwen3.6 27B 93.8%
- 17
Nemotron 3 Super 93.7%
- 18 Grok 4 Fast 93.3%
- 19
DeepSeek-V3.2 92.5%
- 20
Qwen3.5-27B 92%
- 21
Qwen3.5-122B-A10B 91.4%
- 22
Qwen 3.6 35B-A3B 90.7%
- 23
Seed1.8 89.7%
- 24 Kimi K2 Thinking 89.4%
- 25 Granite 4.2 30B 89.2%
- 26
Qwen3.5-35B-A3B 89%
- 27 GPT-5 mini 87.8%
- 28
Ring-1T 86.7%
- 29
Tencent HY 2.0 Think 85.8%
- 30 Sarvam 105B 85.8%
- 31 MiMo-V2-Flash 84.4%
- 32
DeepSeek-V3.1 84.2%
- 33
Qwen3-235B-A22B-Thinking Jul 2025 83.9%
- 34
LongCat-Flash-Thinking 83.7%
- 35
DeepSeek-V3.2-Exp 83.6%
- 36
Qwen3.5-9B 83.2%
- 37
ERNIE 5.0 79.6%
- 38
DeepSeek-R1 May 2025 79.4%
- 39
STEP3-VL-10B 78.2%
- 40
Qwen3-VL-235B-A22B 77.4%
- 41 GPT-5 nano 75.6%
- 42
Qwen3.5-4B 74%
- 43
Qwen3-Next-80B-A3B 73.9%
- 44
Solar Open 100B 73.3%
- 45 Sarvam 30B 73.3%
- 46
EXAONE 4.0 32B 72.9%
- 47
Qwen3-Coder-Next 70.2%
- 48
Step 3 70%
- 49
Ministral 3 14B 67.5%
- 50
Falcon H1R 7B 64.9%
- 51
Phi-4-Reasoning-plus 53.6%
- 52
Phi-4-reasoning 43.8%
- 53 Kimi K2 Jul 2025 38.8%
- 54
Qwen3.5-2B 22.9%
Source: Labs’ model cards
- 100.0 GPT-5.2
- 98.3
Step 3.5 Flash
- 97.5
Gemini 3 Pro
- 97.5
DeepSeek-V3.2-Speciale
- 97.5
Gemini 3 Flash
- 97.5 GLM-5
- 95.0 Grok 4
- 93.3 GLM-4.6
- 93.3 Kimi K2 Thinking
- 93.3 GPT-5.1
- 93.3 Kimi K2.5
- 92.5
DeepSeek-V3.2
- 91.7 Grok 4 Fast
- 90.0 gpt-oss-120b
- 90.0
DeepSeek-V3.2-Exp
- 90.0 Grok 4.1 Fast
- 89.2 GPT-5 mini
- 88.3 GPT-5
- 85.8
DeepSeek-V3.1
- 84.2
Falcon H1R 7B
- 83.3 o4-mini
- 82.5
Gemini 2.5 Pro
- 80.8
Gemini 2.5 Pro
- 77.5 o3
- 77.5 GLM-4.5
- 76.7
DeepSeek-R1
- 76.7 gpt-oss-20b
- 76.7
QED-Nano
- 74.2 Grok-3 mini
- 74.2 GPT-5 nano
- 69.2 GLM-4.5-Air
- 67.5 o3-mini
- 67.5 Claude Sonnet 4.5
- 65.0
K2-Think
- 64.2
Gemini 2.5 Flash
- 62.5
Qwen3-235B-A22B
- 60.0 Claude Opus 4
- 50.8
Qwen3-30B-A3B
- 48.3 o1
- 47.5
QwQ-32B
- 41.7
DeepSeek-R1
- 35.8
Gemini 2.0 Flash Thinking
- 33.3
DeepSeek-R1-Distill-Llama-70B
- 33.3
DeepSeek-R1-Distill-Qwen-32B
- 31.7
DeepSeek-R1-Distill-Qwen-14B
- 31.7 Claude 3.7 Sonnet
- 29.2
DeepSeek-V3
- 18.3
QwQ-32B-Preview
- 13.3
Gemini 2.0 Flash
- 11.7
DeepSeek-R1-Distill-Qwen-1.5B
- 7.50
Gemini 2.0 Pro
- 5.83 GPT-4o
- 1.67 Claude 3.5 Sonnet
- 1 GPT-5.2 xhigh 100%
- 2
Step 3.5 Flash 98.3%
- 3
Gemini 3 Pro 97.5%
- 4
DeepSeek-V3.2-Speciale 97.5%
- 5
Gemini 3 Flash high 97.5%
- 6 GLM-5 97.5%
- 7 Grok 4 95%
- 8 GLM-4.6 93.3%
- 9 Kimi K2 Thinking 93.3%
- 10 GPT-5.1 high 93.3%
- 11 Kimi K2.5 high 93.3%
- 12
DeepSeek-V3.2 thinking 92.5%
- 13 Grok 4 Fast 91.7%
- 14 gpt-oss-120b high 90%
- 15
DeepSeek-V3.2-Exp thinking 90%
- 16 Grok 4.1 Fast reasoning 90%
- 17 GPT-5 mini high 89.2%
- 18 GPT-5 high 88.3%
- 19
DeepSeek-V3.1 thinking 85.8%
- 20
Falcon H1R 7B 84.2%
- 21 o4-mini high 83.3%
- 22
Gemini 2.5 Pro Mar 2025 82.5%
- 23
Gemini 2.5 Pro May 2025 80.8%
- 24 o3 high 77.5%
- 25 GLM-4.5 77.5%
- 26
DeepSeek-R1 May 2025 76.7%
- 27 gpt-oss-20b high 76.7%
- 28
QED-Nano 76.7%
- 29 Grok-3 mini high 74.2%
- 30 GPT-5 nano high 74.2%
- 31 GLM-4.5-Air 69.2%
- 32 o3-mini high 67.5%
- 33 Claude Sonnet 4.5 thinking 67.5%
- 34
K2-Think 65%
- 35
Gemini 2.5 Flash Sep 2025, thinking 64.2%
- 36
Qwen3-235B-A22B 62.5%
- 37 Claude Opus 4 thinking 60%
- 38
Qwen3-30B-A3B 50.8%
- 39 o1 medium 48.3%
- 40
QwQ-32B 47.5%
- 41
DeepSeek-R1 41.7%
- 42
Gemini 2.0 Flash Thinking Jan 2025 35.8%
- 43
DeepSeek-R1-Distill-Llama-70B 33.3%
- 44
DeepSeek-R1-Distill-Qwen-32B 33.3%
- 45
DeepSeek-R1-Distill-Qwen-14B 31.7%
- 46 Claude 3.7 Sonnet thinking 31.7%
- 47
DeepSeek-V3 Mar 2025 29.2%
- 48
QwQ-32B-Preview 18.3%
- 49
Gemini 2.0 Flash Feb 2025 13.3%
- 50
DeepSeek-R1-Distill-Qwen-1.5B 11.7%
- 51
Gemini 2.0 Pro 7.50%
- 52 GPT-4o Mar 2025 5.83%
- 53 Claude 3.5 Sonnet 1.67%
Source: MathArena’s leaderboard
- 100.0 GPT-5
- 100.0
Qwen3-Max
- 100.0 GPT-5.2
- 100.0 GPT-5.2 Pro
- 99.2
DeepSeek-V3.2-Speciale
- 98.4
Step 3.5 Flash
- 97.9 GLM-5
- 97.5
Gemini 3 Pro
- 97.5
Gemini 3 Flash
- 97.5
LongCat-Flash-Thinking-2601
- 97.3
Seed2.0 Pro
- 97.1 GLM-4.7
- 96.7 Grok 4 Heavy
- 96.7
Qwen 3.6 Plus
- 95.4 Kimi K2.5
- 95.0 Grok 4
- 94.8
Qwen3.5 397B-A17B
- 94.6
Nemotron-Cascade 2 30B-A3B
- 93.8
Qwen3.6 27B
- 93.7
Nemotron 3 Super
- 93.3 GLM-4.6
- 93.3 Kimi K2 Thinking
- 93.3 GPT-5.1
- 93.3 Grok 4 Fast
- 92.5
DeepSeek-V3.2
- 92.0
Qwen3.5-27B
- 91.4
Qwen3.5-122B-A10B
- 90.7
Qwen 3.6 35B-A3B
- 90.0 gpt-oss-120b
- 90.0
DeepSeek-V3.2-Exp
- 90.0 Grok 4.1 Fast
- 89.7
Seed1.8
- 89.2 GPT-5 mini
- 89.2 Granite 4.2 30B
- 89.0
Qwen3.5-35B-A3B
- 86.7
Ring-1T
- 85.8
DeepSeek-V3.1
- 85.8
Tencent HY 2.0 Think
- 85.8 Sarvam 105B
- 84.4 MiMo-V2-Flash
- 84.2
Falcon H1R 7B
- 83.9
Qwen3-235B-A22B-Thinking
- 83.7
LongCat-Flash-Thinking
- 83.3 o4-mini
- 83.2
Qwen3.5-9B
- 82.5
Gemini 2.5 Pro
- 80.8
Gemini 2.5 Pro
- 79.6
ERNIE 5.0
- 79.4
DeepSeek-R1
- 78.2
STEP3-VL-10B
- 77.5 o3
- 77.5 GLM-4.5
- 77.4
Qwen3-VL-235B-A22B
- 76.7 gpt-oss-20b
- 76.7
QED-Nano
- 75.6 GPT-5 nano
- 74.2 Grok-3 mini
- 74.0
Qwen3.5-4B
- 73.9
Qwen3-Next-80B-A3B
- 73.3
Solar Open 100B
- 73.3 Sarvam 30B
- 72.9
EXAONE 4.0 32B
- 70.2
Qwen3-Coder-Next
- 70.0
Step 3
- 69.2 GLM-4.5-Air
- 67.5 o3-mini
- 67.5 Claude Sonnet 4.5
- 67.5
Ministral 3 14B
- 65.0
K2-Think
- 64.2
Gemini 2.5 Flash
- 62.5
Qwen3-235B-A22B
- 60.0 Claude Opus 4
- 53.6
Phi-4-Reasoning-plus
- 50.8
Qwen3-30B-A3B
- 48.3 o1
- 47.5
QwQ-32B
- 43.8
Phi-4-reasoning
- 41.7
DeepSeek-R1
- 38.8 Kimi K2
- 35.8
Gemini 2.0 Flash Thinking
- 33.3
DeepSeek-R1-Distill-Llama-70B
- 33.3
DeepSeek-R1-Distill-Qwen-32B
- 31.7
DeepSeek-R1-Distill-Qwen-14B
- 31.7 Claude 3.7 Sonnet
- 29.2
DeepSeek-V3
- 22.9
Qwen3.5-2B
- 18.3
QwQ-32B-Preview
- 13.3
Gemini 2.0 Flash
- 11.7
DeepSeek-R1-Distill-Qwen-1.5B
- 7.50
Gemini 2.0 Pro
- 5.83 GPT-4o
- 1.67 Claude 3.5 Sonnet
- 1 GPT-5 100%
- 2
Qwen3-Max 100%
- 3 GPT-5.2 xhigh 100%
- 4 GPT-5.2 Pro 100%
- 5
DeepSeek-V3.2-Speciale 99.2%
- 6
Step 3.5 Flash 98.4%
- 7 GLM-5 97.9%
- 8
Gemini 3 Pro 97.5%
- 9
Gemini 3 Flash high 97.5%
- 10
LongCat-Flash-Thinking-2601 97.5%
- 11
Seed2.0 Pro 97.3%
- 12 GLM-4.7 97.1%
- 13 Grok 4 Heavy 96.7%
- 14
Qwen 3.6 Plus 96.7%
- 15 Kimi K2.5 95.4%
- 16 Grok 4 95%
- 17
Qwen3.5 397B-A17B 94.8%
- 18
Nemotron-Cascade 2 30B-A3B 94.6%
- 19
Qwen3.6 27B 93.8%
- 20
Nemotron 3 Super 93.7%
- 21 GLM-4.6 93.3%
- 22 Kimi K2 Thinking 93.3%
- 23 GPT-5.1 high 93.3%
- 24 Grok 4 Fast 93.3%
- 25
DeepSeek-V3.2 thinking 92.5%
- 26
Qwen3.5-27B 92%
- 27
Qwen3.5-122B-A10B 91.4%
- 28
Qwen 3.6 35B-A3B 90.7%
- 29 gpt-oss-120b high 90%
- 30
DeepSeek-V3.2-Exp thinking 90%
- 31 Grok 4.1 Fast reasoning 90%
- 32
Seed1.8 89.7%
- 33 GPT-5 mini high 89.2%
- 34 Granite 4.2 30B 89.2%
- 35
Qwen3.5-35B-A3B 89%
- 36
Ring-1T 86.7%
- 37
DeepSeek-V3.1 thinking 85.8%
- 38
Tencent HY 2.0 Think 85.8%
- 39 Sarvam 105B 85.8%
- 40 MiMo-V2-Flash 84.4%
- 41
Falcon H1R 7B 84.2%
- 42
Qwen3-235B-A22B-Thinking Jul 2025 83.9%
- 43
LongCat-Flash-Thinking 83.7%
- 44 o4-mini high 83.3%
- 45
Qwen3.5-9B 83.2%
- 46
Gemini 2.5 Pro Mar 2025 82.5%
- 47
Gemini 2.5 Pro May 2025 80.8%
- 48
ERNIE 5.0 79.6%
- 49
DeepSeek-R1 May 2025 79.4%
- 50
STEP3-VL-10B 78.2%
- 51 o3 high 77.5%
- 52 GLM-4.5 77.5%
- 53
Qwen3-VL-235B-A22B 77.4%
- 54 gpt-oss-20b high 76.7%
- 55
QED-Nano 76.7%
- 56 GPT-5 nano 75.6%
- 57 Grok-3 mini high 74.2%
- 58
Qwen3.5-4B 74%
- 59
Qwen3-Next-80B-A3B 73.9%
- 60
Solar Open 100B 73.3%
- 61 Sarvam 30B 73.3%
- 62
EXAONE 4.0 32B 72.9%
- 63
Qwen3-Coder-Next 70.2%
- 64
Step 3 70%
- 65 GLM-4.5-Air 69.2%
- 66 o3-mini high 67.5%
- 67 Claude Sonnet 4.5 thinking 67.5%
- 68
Ministral 3 14B 67.5%
- 69
K2-Think 65%
- 70
Gemini 2.5 Flash Sep 2025, thinking 64.2%
- 71
Qwen3-235B-A22B 62.5%
- 72 Claude Opus 4 thinking 60%
- 73
Phi-4-Reasoning-plus 53.6%
- 74
Qwen3-30B-A3B 50.8%
- 75 o1 medium 48.3%
- 76
QwQ-32B 47.5%
- 77
Phi-4-reasoning 43.8%
- 78
DeepSeek-R1 41.7%
- 79 Kimi K2 Jul 2025 38.8%
- 80
Gemini 2.0 Flash Thinking Jan 2025 35.8%
- 81
DeepSeek-R1-Distill-Llama-70B 33.3%
- 82
DeepSeek-R1-Distill-Qwen-32B 33.3%
- 83
DeepSeek-R1-Distill-Qwen-14B 31.7%
- 84 Claude 3.7 Sonnet thinking 31.7%
- 85
DeepSeek-V3 Mar 2025 29.2%
- 86
Qwen3.5-2B 22.9%
- 87
QwQ-32B-Preview 18.3%
- 88
Gemini 2.0 Flash Feb 2025 13.3%
- 89
DeepSeek-R1-Distill-Qwen-1.5B 11.7%
- 90
Gemini 2.0 Pro 7.50%
- 91 GPT-4o Mar 2025 5.83%
- 92 Claude 3.5 Sonnet 1.67%
Sources: Labs’ model cards and MathArena’s leaderboard
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | GPT-5 | 100% | Aug 2025 | Lab model card | |
| 2 | | 100% | Sep 2025 | Lab model card | |
| 3 | GPT-5.2 Pro | 100% | Dec 2025 | Lab model card | |
| 4 | | 99.2% | Dec 2025 | Lab model card | |
| 5 | | 98.4% | Feb 2026 | Lab model card | |
| 6 | GLM-5 | 97.9% | Feb 2026 | Lab model card | |
| 7 | | 97.5% | Jan 2026 | Lab model card | |
| 8 | | 97.3% | Feb 2026 | Lab model card | |
| 9 | GLM-4.7 | 97.1% | Dec 2025 | Lab model card | |
| 10 | Grok 4 Heavy | 96.7% | Jul 2025 | Lab model card | |
| 11 | | 96.7% | Apr 2026 | Lab model card | |
| 12 | Kimi K2.5 | 95.4% | Jan 2026 | Lab model card | |
| 13 | | 94.8% | Feb 2026 | Lab model card | |
| 14 | | 94.6% | Mar 2026 | Lab model card | |
| 15 | Grok 4 | 93.9% | Jul 2025 | Lab model card | |
| 16 | | 93.8% | Apr 2026 | Lab model card | |
| 17 | | 93.7% | Mar 2026 | Lab model card | |
| 18 | Grok 4 Fast | 93.3% | Sep 2025 | Lab model card | |
| 19 | | 92.5% | Dec 2025 | Lab model card | |
| 20 | | 92% | Feb 2026 | Lab model card | |
| 21 | | 91.4% | Feb 2026 | Lab model card | |
| 22 | | 90.7% | Apr 2026 | Lab model card | |
| 23 | | 89.7% | Dec 2025 | Lab model card | |
| 24 | Kimi K2 Thinking | 89.4% | Nov 2025 | Lab model card | |
| 25 | Granite 4.2 30B | 89.2% | Aug 2026 | Lab model card | |
| 26 | | 89% | Feb 2026 | Lab model card | |
| 27 | GPT-5 mini | 87.8% | Aug 2025 | Lab model card | |
| 28 | | 86.7% | Oct 2025 | Lab model card | |
| 29 | | 85.8% | Dec 2025 | Lab model card | |
| 30 | Sarvam 105B | 85.8% | Mar 2026 | Lab model card | |
| 31 | MiMo-V2-Flash | 84.4% | Dec 2025 | Lab model card | |
| 32 | | 84.2% | Aug 2025 | Lab model card | |
| 33 | | 83.9% | Jul 2025 | Lab model card | |
| 34 | | 83.7% | Sep 2025 | Lab model card | |
| 35 | | 83.6% | Sep 2025 | Lab model card | |
| 36 | | 83.2% | Mar 2026 | Lab model card | |
| 37 | | 79.6% | Feb 2026 | Lab model card | |
| 38 | | 79.4% | May 2025 | Lab model card | |
| 39 | | 78.2% | Jan 2026 | Lab model card | |
| 40 | | 77.4% | Sep 2025 | Lab model card | |
| 41 | GPT-5 nano | 75.6% | Aug 2025 | Lab model card | |
| 42 | | 74% | Mar 2026 | Lab model card | |
| 43 | | 73.9% | Sep 2025 | Lab model card | |
| 44 | | 73.3% | Dec 2025 | Lab model card | |
| 45 | Sarvam 30B | 73.3% | Mar 2026 | Lab model card | |
| 46 | | 72.9% | Jul 2025 | Lab model card | |
| 47 | | 70.2% | Feb 2026 | Lab model card | |
| 48 | | 70% | Jul 2025 | Lab model card | |
| 49 | | 67.5% | Jan 2026 | Lab model card | |
| 50 | | 64.9% | Jan 2026 | Lab model card | |
| 51 | | 53.6% | Apr 2025 | Lab model card | |
| 52 | | 43.8% | Apr 2025 | Lab model card | |
| 53 | Kimi K2 Jul 2025 | 38.8% | Jul 2025 | Lab model card | |
| 54 | | 22.9% | Mar 2026 | Lab model card |
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | GPT-5.2 | 100% | xhigh | Dec 2025 | Official leaderboard |
| 2 | | 98.3% | Feb 2026 | Official leaderboard | |
| 3 | | 97.5% | Nov 2025 | Official leaderboard | |
| 4 | | 97.5% | Dec 2025 | Official leaderboard | |
| 5 | | 97.5% | high | Dec 2025 | Official leaderboard |
| 6 | GLM-5 | 97.5% | Feb 2026 | Official leaderboard | |
| 7 | Grok 4 | 95% | Jul 2025 | Official leaderboard | |
| 8 | GLM-4.6 | 93.3% | Sep 2025 | Official leaderboard | |
| 9 | Kimi K2 Thinking | 93.3% | Nov 2025 | Official leaderboard | |
| 10 | GPT-5.1 | 93.3% | high | Nov 2025 | Official leaderboard |
| 11 | Kimi K2.5 | 93.3% | high | Jan 2026 | Official leaderboard |
| 12 | | 92.5% | thinking | Dec 2025 | Official leaderboard |
| 13 | Grok 4 Fast | 91.7% | Sep 2025 | Official leaderboard | |
| 14 | gpt-oss-120b | 90% | high | Aug 2025 | Official leaderboard |
| 15 | | 90% | thinking | Sep 2025 | Official leaderboard |
| 16 | Grok 4.1 Fast | 90% | reasoning | Nov 2025 | Official leaderboard |
| 17 | GPT-5 mini | 89.2% | high | Aug 2025 | Official leaderboard |
| 18 | GPT-5 | 88.3% | high | Aug 2025 | Official leaderboard |
| 19 | | 85.8% | thinking | Aug 2025 | Official leaderboard |
| 20 | | 84.2% | Jan 2026 | Official leaderboard | |
| 21 | o4-mini | 83.3% | high | Apr 2025 | Official leaderboard |
| 22 | | 82.5% | Mar 2025 | Official leaderboard | |
| 23 | | 80.8% | May 2025 | Official leaderboard | |
| 24 | o3 | 77.5% | high | Apr 2025 | Official leaderboard |
| 25 | GLM-4.5 | 77.5% | Aug 2025 | Official leaderboard | |
| 26 | | 76.7% | May 2025 | Official leaderboard | |
| 27 | gpt-oss-20b | 76.7% | high | Aug 2025 | Official leaderboard |
| 28 | | 76.7% | Feb 2026 | Official leaderboard | |
| 29 | Grok-3 mini | 74.2% | high | Apr 2025 | Official leaderboard |
| 30 | GPT-5 nano | 74.2% | high | Aug 2025 | Official leaderboard |
| 31 | GLM-4.5-Air | 69.2% | Jul 2025 | Official leaderboard | |
| 32 | o3-mini | 67.5% | high | Jan 2025 | Official leaderboard |
| 33 | Claude Sonnet 4.5 | 67.5% | thinking | Sep 2025 | Official leaderboard |
| 34 | | 65% | Sep 2025 | Official leaderboard | |
| 35 | | 64.2% | thinking | Sep 2025 | Official leaderboard |
| 36 | | 62.5% | Apr 2025 | Official leaderboard | |
| 37 | Claude Opus 4 | 60% | thinking | May 2025 | Official leaderboard |
| 38 | | 50.8% | Apr 2025 | Official leaderboard | |
| 39 | o1 | 48.3% | medium | Dec 2024 | Official leaderboard |
| 40 | | 47.5% | Mar 2025 | Official leaderboard | |
| 41 | | 41.7% | Jan 2025 | Official leaderboard | |
| 42 | | 35.8% | Jan 2025 | Official leaderboard | |
| 43 | | 33.3% | Jan 2025 | Official leaderboard | |
| 44 | | 33.3% | Jan 2025 | Official leaderboard | |
| 45 | | 31.7% | Jan 2025 | Official leaderboard | |
| 46 | Claude 3.7 Sonnet | 31.7% | thinking | Feb 2025 | Official leaderboard |
| 47 | | 29.2% | Mar 2025 | Official leaderboard | |
| 48 | | 18.3% | Nov 2024 | Official leaderboard | |
| 49 | | 13.3% | Feb 2025 | Official leaderboard | |
| 50 | | 11.7% | Jan 2025 | Official leaderboard | |
| 51 | | 7.50% | Feb 2025 | Official leaderboard | |
| 52 | GPT-4o Mar 2025 | 5.83% | Mar 2025 | Official leaderboard | |
| 53 | Claude 3.5 Sonnet | 1.67% | Jun 2024 | Official leaderboard |
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | GPT-5 | 100% | Aug 2025 | Lab model card | |
| 2 | | 100% | Sep 2025 | Lab model card | |
| 3 | GPT-5.2 | 100% | xhigh | Dec 2025 | Official leaderboard |
| 4 | GPT-5.2 Pro | 100% | Dec 2025 | Lab model card | |
| 5 | | 99.2% | Dec 2025 | Lab model card | |
| 6 | | 98.4% | Feb 2026 | Lab model card | |
| 7 | GLM-5 | 97.9% | Feb 2026 | Lab model card | |
| 8 | | 97.5% | Nov 2025 | Official leaderboard | |
| 9 | | 97.5% | high | Dec 2025 | Official leaderboard |
| 10 | | 97.5% | Jan 2026 | Lab model card | |
| 11 | | 97.3% | Feb 2026 | Lab model card | |
| 12 | GLM-4.7 | 97.1% | Dec 2025 | Lab model card | |
| 13 | Grok 4 Heavy | 96.7% | Jul 2025 | Lab model card | |
| 14 | | 96.7% | Apr 2026 | Lab model card | |
| 15 | Kimi K2.5 | 95.4% | Jan 2026 | Lab model card | |
| 16 | Grok 4 | 95% | Jul 2025 | Official leaderboard | |
| 17 | | 94.8% | Feb 2026 | Lab model card | |
| 18 | | 94.6% | Mar 2026 | Lab model card | |
| 19 | | 93.8% | Apr 2026 | Lab model card | |
| 20 | | 93.7% | Mar 2026 | Lab model card | |
| 21 | GLM-4.6 | 93.3% | Sep 2025 | Official leaderboard | |
| 22 | Kimi K2 Thinking | 93.3% | Nov 2025 | Official leaderboard | |
| 23 | GPT-5.1 | 93.3% | high | Nov 2025 | Official leaderboard |
| 24 | Grok 4 Fast | 93.3% | Sep 2025 | Lab model card | |
| 25 | | 92.5% | thinking | Dec 2025 | Official leaderboard |
| 26 | | 92% | Feb 2026 | Lab model card | |
| 27 | | 91.4% | Feb 2026 | Lab model card | |
| 28 | | 90.7% | Apr 2026 | Lab model card | |
| 29 | gpt-oss-120b | 90% | high | Aug 2025 | Official leaderboard |
| 30 | | 90% | thinking | Sep 2025 | Official leaderboard |
| 31 | Grok 4.1 Fast | 90% | reasoning | Nov 2025 | Official leaderboard |
| 32 | | 89.7% | Dec 2025 | Lab model card | |
| 33 | GPT-5 mini | 89.2% | high | Aug 2025 | Official leaderboard |
| 34 | Granite 4.2 30B | 89.2% | Aug 2026 | Lab model card | |
| 35 | | 89% | Feb 2026 | Lab model card | |
| 36 | | 86.7% | Oct 2025 | Lab model card | |
| 37 | | 85.8% | thinking | Aug 2025 | Official leaderboard |
| 38 | | 85.8% | Dec 2025 | Lab model card | |
| 39 | Sarvam 105B | 85.8% | Mar 2026 | Lab model card | |
| 40 | MiMo-V2-Flash | 84.4% | Dec 2025 | Lab model card | |
| 41 | | 84.2% | Jan 2026 | Official leaderboard | |
| 42 | | 83.9% | Jul 2025 | Lab model card | |
| 43 | | 83.7% | Sep 2025 | Lab model card | |
| 44 | o4-mini | 83.3% | high | Apr 2025 | Official leaderboard |
| 45 | | 83.2% | Mar 2026 | Lab model card | |
| 46 | | 82.5% | Mar 2025 | Official leaderboard | |
| 47 | | 80.8% | May 2025 | Official leaderboard | |
| 48 | | 79.6% | Feb 2026 | Lab model card | |
| 49 | | 79.4% | May 2025 | Lab model card | |
| 50 | | 78.2% | Jan 2026 | Lab model card | |
| 51 | o3 | 77.5% | high | Apr 2025 | Official leaderboard |
| 52 | GLM-4.5 | 77.5% | Aug 2025 | Official leaderboard | |
| 53 | | 77.4% | Sep 2025 | Lab model card | |
| 54 | gpt-oss-20b | 76.7% | high | Aug 2025 | Official leaderboard |
| 55 | | 76.7% | Feb 2026 | Official leaderboard | |
| 56 | GPT-5 nano | 75.6% | Aug 2025 | Lab model card | |
| 57 | Grok-3 mini | 74.2% | high | Apr 2025 | Official leaderboard |
| 58 | | 74% | Mar 2026 | Lab model card | |
| 59 | | 73.9% | Sep 2025 | Lab model card | |
| 60 | | 73.3% | Dec 2025 | Lab model card | |
| 61 | Sarvam 30B | 73.3% | Mar 2026 | Lab model card | |
| 62 | | 72.9% | Jul 2025 | Lab model card | |
| 63 | | 70.2% | Feb 2026 | Lab model card | |
| 64 | | 70% | Jul 2025 | Lab model card | |
| 65 | GLM-4.5-Air | 69.2% | Jul 2025 | Official leaderboard | |
| 66 | o3-mini | 67.5% | high | Jan 2025 | Official leaderboard |
| 67 | Claude Sonnet 4.5 | 67.5% | thinking | Sep 2025 | Official leaderboard |
| 68 | | 67.5% | Jan 2026 | Lab model card | |
| 69 | | 65% | Sep 2025 | Official leaderboard | |
| 70 | | 64.2% | thinking | Sep 2025 | Official leaderboard |
| 71 | | 62.5% | Apr 2025 | Official leaderboard | |
| 72 | Claude Opus 4 | 60% | thinking | May 2025 | Official leaderboard |
| 73 | | 53.6% | Apr 2025 | Lab model card | |
| 74 | | 50.8% | Apr 2025 | Official leaderboard | |
| 75 | o1 | 48.3% | medium | Dec 2024 | Official leaderboard |
| 76 | | 47.5% | Mar 2025 | Official leaderboard | |
| 77 | | 43.8% | Apr 2025 | Lab model card | |
| 78 | | 41.7% | Jan 2025 | Official leaderboard | |
| 79 | Kimi K2 Jul 2025 | 38.8% | Jul 2025 | Lab model card | |
| 80 | | 35.8% | Jan 2025 | Official leaderboard | |
| 81 | | 33.3% | Jan 2025 | Official leaderboard | |
| 82 | | 33.3% | Jan 2025 | Official leaderboard | |
| 83 | | 31.7% | Jan 2025 | Official leaderboard | |
| 84 | Claude 3.7 Sonnet | 31.7% | thinking | Feb 2025 | Official leaderboard |
| 85 | | 29.2% | Mar 2025 | Official leaderboard | |
| 86 | | 22.9% | Mar 2026 | Lab model card | |
| 87 | | 18.3% | Nov 2024 | Official leaderboard | |
| 88 | | 13.3% | Feb 2025 | Official leaderboard | |
| 89 | | 11.7% | Jan 2025 | Official leaderboard | |
| 90 | | 7.50% | Feb 2025 | Official leaderboard | |
| 91 | GPT-4o Mar 2025 | 5.83% | Mar 2025 | Official leaderboard | |
| 92 | Claude 3.5 Sonnet | 1.67% | Jun 2024 | Official leaderboard |
MathArena’s leaderboard has 53 models. Switch the scores above to rank them together.
The best score, 100%, costs $0.24 a task
Runs on the cost frontier score higher than any run that's cheaper. DeepSeek-V3.2-Speciale comes within 2.5 points of the best for $0.01 a task, 22 times cheaper. The costs are the leaderboard's own estimates, so compare them only within this benchmark.
Source: MathArena’s leaderboard
| Model | Effort | Harness | Score | Cost per task | Output tokens |
|---|---|---|---|---|---|
| GPT-5.2 | xhigh | 100% | $0.24 | 17,003 | |
| GPT-5.2 | high | 98.3% | $0.16 | 11,164 | |
| | 98.3% | $0.01 | 47,820 | ||
| | 97.5% | $0.19 | 15,918 | ||
| | 97.5% | $0.01 | 25,870 | ||
| | high | 97.5% | $0.06 | 20,536 | |
| GLM-5 | 97.5% | $0.09 | 28,926 | ||
| Grok 4 | 95% | $0.22 | 14,669 | ||
| GLM-4.6 | 93.3% | $0.05 | 21,480 | ||
| Kimi K2 Thinking | 93.3% | $0.07 | 28,389 | ||
| GPT-5.1 | high | 93.3% | $0.22 | 22,001 | |
| Kimi K2.5 | high | 93.3% | $0.08 | 26,862 | |
| | thinking | 92.5% | $0.007 | 17,382 | |
| Grok 4 Fast | 91.7% | $0.006 | 12,770 | ||
| gpt-oss-120b | high | 90% | $0.02 | 27,304 | |
| | thinking | 90% | $0.008 | 18,393 | |
| Grok 4.1 Fast | reasoning | 90% | $0.007 | 13,404 | |
| GPT-5 mini | high | 89.2% | $0.03 | 16,887 | |
| GPT-5 | high | 88.3% | $0.17 | 16,380 | |
| | thinking | 85.8% | $0.04 | 19,230 | |
| | 84.2% | $0.006 | 30,233 | ||
| o4-mini | high | 83.3% | $0.08 | 17,637 | |
| | 82.5% | $0.13 | 12,875 | ||
| | 80.8% | 3,623 | |||
| o3 | high | 77.5% | $0.12 | 13,786 | |
| GLM-4.5 | 77.5% | $0.06 | 25,438 | ||
| | 76.7% | $0.06 | 25,366 | ||
| gpt-oss-20b | high | 76.7% | $0.01 | 54,740 | |
| | 76.7% | 43,216 | |||
| Grok-3 mini | high | 74.2% | $0.01 | 21,000 | |
| GPT-5 nano | high | 74.2% | $0.01 | 36,743 | |
| GLM-4.5-Air | 69.2% | $0.03 | 27,720 | ||
| o3-mini | high | 67.5% | $0.08 | 17,660 | |
| o4-mini | medium | 67.5% | $0.03 | 7,298 | |
| Claude Sonnet 4.5 | thinking | 67.5% | $0.32 | 21,410 | |
| | 65% | ||||
| | thinking | 64.2% | $0.10 | 27,168 | |
| | 62.5% | $0.009 | 15,098 | ||
| Claude Opus 4 | thinking | 60% | $1.23 | 16,379 | |
| o3-mini | medium | 53.3% | $0.03 | 7,601 | |
| Grok-3 mini | low | 50.8% | $0.003 | 6,636 | |
| | 50.8% | $0.006 | 18,539 | ||
| o1 | medium | 48.3% | $0.89 | 14,835 | |
| | 47.5% | $0.02 | 16,152 | ||
| o4-mini | low | 47.5% | $0.01 | 2,663 | |
| | 41.7% | $0.03 | 12,817 | ||
| | 35.8% | 427 | |||
| | 33.3% | $0.007 | 11,898 | ||
| | 33.3% | $0.005 | 15,555 | ||
| | 31.7% | $0.002 | 15,559 | ||
| Claude 3.7 Sonnet | thinking | 31.7% | $0.39 | 25,902 | |
| | 29.2% | $0.005 | 4,216 | ||
| o3-mini | low | 28.3% | $0.01 | 2,661 | |
| | 18.3% | $0.01 | 9,531 | ||
| | 13.3% | $0.001 | 3,312 | ||
| | 13.3% | $0.003 | 2,453 | ||
| | 11.7% | $0.004 | 23,111 | ||
| | 7.50% | $0.01 | 2,252 | ||
| GPT-4o Mar 2025 | 5.83% | $0.008 | 769 | ||
| Claude 3.5 Sonnet | 1.67% | $0.008 | 528 |
4 models have held number one in labs’ own numbers since its release in February 2025 6 models have held number one across all independent runs since its release in February 2025 5 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 MathArena’s leaderboard and what labs claim in their cards.
XAI’s own number for Grok 4 Heavy passed 85% in July 2025
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Sources: MathArena’s leaderboard and labs’ model cards
Labs headline it less often now, last in August 2026
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 |
|---|---|---|---|
| Aug 25, 2026 | Granite 4.2 30B | 89.2 | HMMT Feb25 |
| Apr 22, 2026 | 93.8 | HMMT Feb 25 | |
| Apr 15, 2026 | 90.7 | HMMT Feb 25 | |
| Apr 2, 2026 | 96.7 | HMMT Feb 25 | |
| Mar 19, 2026 | 94.6 | HMMT Feb25 | |
| Mar 11, 2026 | 93.7 | HMMT Feb25 (no tools) | |
| Mar 6, 2026 | Sarvam 30B | 73.3 | HMMT Feb 2025 |
| Mar 6, 2026 | Sarvam 105B | 85.8 | HMMT (Feb 25) |
| Mar 2, 2026 | 22.9 | HMMT Feb 25 | |
| Mar 2, 2026 | 74 | HMMT Feb 25 | |
| Mar 2, 2026 | 83.2 | HMMT Feb 25 | |
| Feb 24, 2026 | 89 | HMMT Feb 25 | |
| Feb 24, 2026 | 92 | HMMT Feb 25 | |
| Feb 24, 2026 | 91.4 | HMMT Feb 25 | |
| Feb 16, 2026 | 94.8 | HMMT Feb 25 | |
| Feb 14, 2026 | 97.3 | HMMT Feb 2025 | |
| Feb 6, 2026 | 79.6 | HMMT 2025 | |
| Feb 2, 2026 | 98.4 | HMMT 2025 (Feb.) | |
| Jan 27, 2026 | Kimi K2.5 | 95.4 | HMMT 2025 (Feb) |
| Jan 23, 2026 | 98 | HMMT Feb 25 | |
| Jan 14, 2026 | 97.5 | Best of HMMT-25 (Avg@16) w/ tools 93.4 / Heavy Thinking 97.5 | |
| Jan 13, 2026 | 78.2 | HMMT 2025 (SeRe) | |
| Jan 5, 2026 | 64.9 | HMMT-25 | |
| Dec 31, 2025 | 73.3 | HMMT 2025 (Feb) | |
| Dec 22, 2025 | GLM-4.7 | 97.1 | HMMT Feb. 2025 |
| Dec 18, 2025 | 89.7 | HMMT25(Feb) | |
| Dec 16, 2025 | MiMo-V2-Flash | 84.4 | HMMT Feb. 2025 |
| Dec 11, 2025 | GPT-5.2 Pro | 100 | HMMT, Feb 2025 (no tools) |
| Dec 5, 2025 | 85.8 | HMMT2025 | |
| Dec 1, 2025 | 92.5 | HMMT Feb 2025 (Pass@1) | |
| Nov 6, 2025 | Kimi K2 Thinking | 89.4 | HMMT25, no tools |
| Oct 10, 2025 | 86.7 | HMMT 25 (pass@1) | |
| Sep 29, 2025 | 83.6 | HMMT 2025 | |
| Sep 24, 2025 | 100 | HMMT (Thinking Heavy w/ Python) | |
| Sep 23, 2025 | 77.4 | HMMT25 | |
| Sep 21, 2025 | 83.7 | HMMT25(Mean@32) | |
| Sep 19, 2025 | Grok 4 Fast | 93.3 | HMMT 2025 (no tools) pass@1 |
| Sep 11, 2025 | 73.9 | HMMT25 | |
| Aug 21, 2025 | 84.2 | HMMT 2025 (Pass@1) | |
| Aug 7, 2025 | GPT-5 nano | 75.6 | HMMT 2025 (no tools) |
| Aug 7, 2025 | GPT-5 mini | 87.8 | HMMT 2025 (no tools) |
| Aug 7, 2025 | GPT-5 | 100 | HMMT Harvard-MIT mathematics tournament, GPT-5 pro (python) |
| Jul 31, 2025 | 70 | HMMT25 | |
| Jul 25, 2025 | 83.9 | HMMT25 | |
| Jul 15, 2025 | 72.9 | HMMT Feb 2025 (reasoning) | |
| Jul 11, 2025 | Kimi K2 | 38.8 | HMMT 2025, Avg@32 |
| Jul 9, 2025 | Grok 4 | 93.9 | HMMT 2025, with Python (no tools 90.0) |
| Jul 9, 2025 | Grok 4 Heavy | 96.7 | HMMT 2025 (Competitive Math) [Grok 4 Heavy, Python] |
| May 28, 2025 | 79.4 | HMMT 2025 (Pass@1) |
25 system cards report it, from 16 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 |
|---|---|---|---|---|
| Mar 21, 2026 | | 89.7 | HMMT25(Feb) (Table 1). Avg@10, 96.7 with increased thinking (Table 7) | Capabilities |
| Mar 19, 2026 | | 94.6 | HMMT Feb25 (Table 1) | Capabilities |
| Mar 11, 2026 | | 93.7 | HMMT Feb25 (no tools), 94.73 with tools (Table 5) | Capabilities |
| Feb 28, 2026 | | 70.2 | HMMT25 Feb (Table 9) | Capabilities |
| Feb 17, 2026 | GLM-5 technical report | 97.9 | HMMT Feb. 2025 (Table 7) | Capabilities |
| Feb 14, 2026 | | 97.3 | HMMT Feb 2025 (Table 3) | Capabilities |
| Feb 11, 2026 | | 98.4 | HMMT 2025 Feb., avg of 64 (Table 5). PaCoRe 100.0, with Python 98.7 (Table 12) | Capabilities |
| Feb 4, 2026 | | 79.6 | HMMT 2025 (Table 2) | Capabilities |
| Jan 30, 2026 | Kimi K2.5 technical report | 95.4 | HMMT 2025 (Feb), Avg@64 (Table 4) | Capabilities |
| Jan 23, 2026 | | 97.5 | HMMT-25 (February) (Avg@16), w/ tools, heavy mode (Table 2). Default mode 93.4 | Capabilities |
| Jan 14, 2026 | | 78.2 | HMMT25, SeRe (Tables 2 and 3). PaCoRe 92.14 | Capabilities |
| Jan 13, 2026 | | 67.5 | HMMT 2025, reported as pass@16 (Table 5) | Capabilities |
| Jan 11, 2026 | | 73.3 | HMMT 2025 (Feb) (Table 6) | Capabilities |
| Jan 6, 2026 | MiMo-V2-Flash technical report | 84.4 | HMMT Feb. 2025 (Table 9) | Capabilities |
| Jan 5, 2026 | | 64.9 | HMMT25 pass@1 (Table 4) | Capabilities |
| Dec 1, 2025 | | 92.5 | HMMT Feb 2025 (Pass@1), DeepSeek-V3.2 Thinking (Table 2) | Capabilities |
| Dec 1, 2025 | | 99.2 | HMMT Feb 2025 (Pass@1), DeepSeek-V3.2-Speciale (Table 3) | Capabilities |
| Nov 26, 2025 | | 77.4 | HMMT-25 (Table 6) | Capabilities |
| Oct 21, 2025 | | 86.7 | HMMT25 (Avg@16) (Table 1) | Capabilities |
| Sep 29, 2025 | | 83.6 | HMMT 2025 (Pass@1), DeepSeek-V3.2-Exp (Table 1) | Capabilities |
| Sep 23, 2025 | | 83.7 | HMMT-25(Mean@32) (Table 2) | Capabilities |
| Jul 21, 2025 | Kimi K2 technical report | 38.8 | HMMT 2025 (Avg@32) (Table 3) | Capabilities |
| Jul 15, 2025 | | 72.9 | HMMT Feb 2025, n=32 (Table 3, Reasoning). Non-reasoning 21.8 (Table 4) | Capabilities |
| Apr 30, 2025 | | 43.8 | HMMT Feb 2025, average pass@1, MathArena scoring, std 6.2 (Table 1) | Capabilities |
| Apr 30, 2025 | | 53.6 | HMMT Feb 2025, average pass@1 over 64 runs, MathArena scoring (Table 1) | Capabilities |
The lab's number comes out ahead in 7 of 13 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. 2 of them match, which usually means one side copied the other. Every benchmark.
| Model | Lab says | Board says | Gap |
|---|---|---|---|
| | 64.9% HMMT-25 | 84.2% Leaderboard | −19 pts |
| GPT-5 | 100% HMMT Harvard-MIT mathematics tournament, GPT-5 pro (python) | 88.3% Leaderboard, high | +12 pts |
| | 83.6% HMMT 2025 | 90% Leaderboard, thinking | −6.4 pts |
| Kimi K2 Thinking | 89.4% HMMT25, no tools | 93.3% Leaderboard | −3.9 pts |
| | 79.4% HMMT 2025 (Pass@1) | 76.7% Leaderboard | +2.7 pts |
| Kimi K2.5 | 95.4% HMMT 2025 (Feb) | 93.3% Leaderboard, high | +2.1 pts |
| | 99.2% HMMT Feb 2025 (Pass@1), DeepSeek-V3.2-Speciale (Table 3) | 97.5% Leaderboard | +1.7 pts |
| | 84.2% HMMT 2025 (Pass@1) | 85.8% Leaderboard, thinking | −1.6 pts |
| Grok 4 Fast | 93.3% HMMT 2025 (no tools) pass@1 | 91.7% Leaderboard | +1.6 pts |
| GPT-5 nano | 75.6% HMMT 2025 (no tools) | 74.2% Leaderboard, high | +1.4 pts |
| GPT-5 mini | 87.8% HMMT 2025 (no tools) | 89.2% Leaderboard, high | −1.4 pts |
| Grok 4 | 93.9% HMMT 2025, with Python (no tools 90.0) | 95% Leaderboard | −1.1 pts |
| GLM-5 | 97.9% HMMT Feb. 2025 (Table 7) | 97.5% Leaderboard | +0.4 pts |
| | 98.4% HMMT 2025 (Feb.) | 98.3% Leaderboard | Same |
| | 92.5% HMMT Feb 2025 (Pass@1) | 92.5% Leaderboard, thinking | Same |
Versions
We switch the top row to each new version when it comes out. Open it for one row per version. An old version stays in play while people still test it, so whoever first takes it past 85% gets credit for closing it out.
Sources: Official leaderboards and labs’ model cards
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