HMMT Nov 2025
Models solve the 30 problems of the November 2025 Harvard-MIT Mathematics Tournament. Final answers are checked automatically against the answer key.
- Released
- November 2025
- Kind
- Competition problems with answers
- Level
- Competition
- Scored
- Checked automatically
- Answers
- Short answer
- Tasks
- All public
- Strongest model tested
- GPT-5.2 #50 on the capability index
- Last in a launch post
- June 2026, dropped after it saturated
- Last model added
- June 2026
- Scores refreshed
- November 12th, 2026
GPT-5.2 leads with 99.2% among models released by February 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.
GPT-5.2 leads with 99.2%, 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 February 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 16 more
- 99.2 GPT-5.2
- 94.2
Step 3.5 Flash
- 94.2 GLM-5
- 93.3
Gemini 3 Pro
- 93.3 Grok 4.1 Fast
- 93.3
DeepSeek-V3.2-Speciale
- 93.3
Gemini 3 Flash
- 91.7 GLM-4.6
- 91.7 GPT-5.1
- 90.8 Grok 4 Fast
- 90.0 gpt-oss-120b
- 90.0
DeepSeek-V3.2
- 89.2 GPT-5
- 89.2 Kimi K2 Thinking
- 89.2 Kimi K2.5
- 88.3 Grok 4
- 84.2 GPT-5 mini
- 84.2
DeepSeek-V3.2-Exp
- 81.7 GPT-5 nano
- 80.0
Gemini 2.5 Pro
- 79.2
Falcon H1R 7B
- 75.0
QED-Nano
- 1 GPT-5.2 xhigh 99.2%
- 2
Step 3.5 Flash 94.2%
- 3 GLM-5 94.2%
- 4
Gemini 3 Pro 93.3%
- 5 Grok 4.1 Fast reasoning 93.3%
- 6
DeepSeek-V3.2-Speciale 93.3%
- 7
Gemini 3 Flash high 93.3%
- 8 GLM-4.6 91.7%
- 9 GPT-5.1 high 91.7%
- 10 Grok 4 Fast 90.8%
- 11 gpt-oss-120b high 90%
- 12
DeepSeek-V3.2 thinking 90%
- 13 GPT-5 high 89.2%
- 14 Kimi K2 Thinking 89.2%
- 15 Kimi K2.5 high 89.2%
- 16 Grok 4 88.3%
- 17 GPT-5 mini high 84.2%
- 18
DeepSeek-V3.2-Exp thinking 84.2%
- 19 GPT-5 nano high 81.7%
- 20
Gemini 2.5 Pro Jun 2025 80%
- 21
Falcon H1R 7B 79.2%
- 22
QED-Nano 75%
Source: Official HMMT Nov 2025 leaderboard
- 99.2 GPT-5.2
- 98.3
Ring-2.5-1T
- 96.9 GLM-5
- 94.7
Qwen3-Max
- 94.6
Qwen 3.6 Plus
- 94.4
DeepSeek-V3.2-Speciale
- 94.4 GLM-5.2
- 94.2
Step 3.5 Flash
- 94.0 GLM-5.1
- 93.5 GLM-4.7
- 93.3
Gemini 3 Pro
- 93.3 Grok 4.1 Fast
- 93.3
Gemini 3 Flash
- 93.3
Seed2.0 Pro
- 92.7
Qwen3.5 397B-A17B
- 91.7 GLM-4.6
- 91.7 GPT-5.1
- 91.1 Kimi K2.5
- 90.8 Grok 4 Fast
- 90.7
Qwen3.6 27B
- 90.3
Qwen3.5-122B-A10B
- 90.2
DeepSeek-V3.2
- 90.0 gpt-oss-120b
- 89.8
Qwen3.5-27B
- 89.2
Qwen3.5-35B-A3B
- 89.2 GPT-5
- 89.2 Kimi K2 Thinking
- 89.1
Qwen 3.6 35B-A3B
- 88.3 Grok 4
- 86.8
K-EXAONE
- 85.8 Sarvam 105B
- 84.4
Qwen3.5-Omni-Plus
- 84.2 GPT-5 mini
- 84.2
DeepSeek-V3.2-Exp
- 82.9
Qwen3.5-9B
- 81.9
Ling-2.6-1T
- 81.7 GPT-5 nano
- 80.0
Gemini 2.5 Pro
- 80.0
Solar Open 100B
- 79.2
Falcon H1R 7B
- 76.8
Qwen3.5-4B
- 75.6
Qwen3-Coder-Next
- 75.0
QED-Nano
- 74.2 Sarvam 30B
- 19.6
Qwen3.5-2B
- 1 GPT-5.2 xhigh 99.2%
- 2
Ring-2.5-1T 98.3%
- 3 GLM-5 96.9%
- 4
Qwen3-Max 94.7%
- 5
Qwen 3.6 Plus 94.6%
- 6
DeepSeek-V3.2-Speciale 94.4%
- 7 GLM-5.2 94.4%
- 8
Step 3.5 Flash 94.2%
- 9 GLM-5.1 94%
- 10 GLM-4.7 93.5%
- 11
Gemini 3 Pro 93.3%
- 12 Grok 4.1 Fast reasoning 93.3%
- 13
Gemini 3 Flash high 93.3%
- 14
Seed2.0 Pro 93.3%
- 15
Qwen3.5 397B-A17B 92.7%
- 16 GLM-4.6 91.7%
- 17 GPT-5.1 high 91.7%
- 18 Kimi K2.5 91.1%
- 19 Grok 4 Fast 90.8%
- 20
Qwen3.6 27B 90.7%
- 21
Qwen3.5-122B-A10B 90.3%
- 22
DeepSeek-V3.2 90.2%
- 23 gpt-oss-120b high 90%
- 24
Qwen3.5-27B 89.8%
- 25
Qwen3.5-35B-A3B 89.2%
- 26 GPT-5 high 89.2%
- 27 Kimi K2 Thinking 89.2%
- 28
Qwen 3.6 35B-A3B 89.1%
- 29 Grok 4 88.3%
- 30
K-EXAONE 86.8%
- 31 Sarvam 105B 85.8%
- 32
Qwen3.5-Omni-Plus 84.4%
- 33 GPT-5 mini high 84.2%
- 34
DeepSeek-V3.2-Exp thinking 84.2%
- 35
Qwen3.5-9B 82.9%
- 36
Ling-2.6-1T 81.9%
- 37 GPT-5 nano high 81.7%
- 38
Gemini 2.5 Pro Jun 2025 80%
- 39
Solar Open 100B 80%
- 40
Falcon H1R 7B 79.2%
- 41
Qwen3.5-4B 76.8%
- 42
Qwen3-Coder-Next 75.6%
- 43
QED-Nano 75%
- 44 Sarvam 30B 74.2%
- 45
Qwen3.5-2B 19.6%
Sources: Official HMMT Nov 2025 leaderboard and labs’ model cards
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | GPT-5.2 | 99.2% | xhigh | Dec 2025 | Official leaderboard |
| 2 | | 94.2% | Feb 2026 | Official leaderboard | |
| 3 | GLM-5 | 94.2% | Feb 2026 | Official leaderboard | |
| 4 | | 93.3% | Nov 2025 | Official leaderboard | |
| 5 | Grok 4.1 Fast | 93.3% | reasoning | Nov 2025 | Official leaderboard |
| 6 | | 93.3% | Dec 2025 | Official leaderboard | |
| 7 | | 93.3% | high | Dec 2025 | Official leaderboard |
| 8 | GLM-4.6 | 91.7% | Sep 2025 | Official leaderboard | |
| 9 | GPT-5.1 | 91.7% | high | Nov 2025 | Official leaderboard |
| 10 | Grok 4 Fast | 90.8% | Sep 2025 | Official leaderboard | |
| 11 | gpt-oss-120b | 90% | high | Aug 2025 | Official leaderboard |
| 12 | | 90% | thinking | Dec 2025 | Official leaderboard |
| 13 | GPT-5 | 89.2% | high | Aug 2025 | Official leaderboard |
| 14 | Kimi K2 Thinking | 89.2% | Nov 2025 | Official leaderboard | |
| 15 | Kimi K2.5 | 89.2% | high | Jan 2026 | Official leaderboard |
| 16 | Grok 4 | 88.3% | Jul 2025 | Official leaderboard | |
| 17 | GPT-5 mini | 84.2% | high | Aug 2025 | Official leaderboard |
| 18 | | 84.2% | thinking | Sep 2025 | Official leaderboard |
| 19 | GPT-5 nano | 81.7% | high | Aug 2025 | Official leaderboard |
| 20 | | 80% | Jun 2025 | Official leaderboard | |
| 21 | | 79.2% | Jan 2026 | Official leaderboard | |
| 22 | | 75% | Feb 2026 | Official leaderboard |
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | GPT-5.2 | 99.2% | xhigh | Dec 2025 | Official leaderboard |
| 2 | | 98.3% | Feb 2026 | Lab model card | |
| 3 | GLM-5 | 96.9% | Feb 2026 | Lab model card | |
| 4 | | 94.7% | Jan 2026 | Lab model card | |
| 5 | | 94.6% | Apr 2026 | Lab model card | |
| 6 | | 94.4% | Dec 2025 | Lab model card | |
| 7 | GLM-5.2 | 94.4% | Jun 2026 | Lab model card | |
| 8 | | 94.2% | Feb 2026 | Official leaderboard | |
| 9 | GLM-5.1 | 94% | Apr 2026 | Lab model card | |
| 10 | GLM-4.7 | 93.5% | Dec 2025 | Lab model card | |
| 11 | | 93.3% | Nov 2025 | Official leaderboard | |
| 12 | Grok 4.1 Fast | 93.3% | reasoning | Nov 2025 | Official leaderboard |
| 13 | | 93.3% | high | Dec 2025 | Official leaderboard |
| 14 | | 93.3% | Feb 2026 | Lab model card | |
| 15 | | 92.7% | Feb 2026 | Lab model card | |
| 16 | GLM-4.6 | 91.7% | Sep 2025 | Official leaderboard | |
| 17 | GPT-5.1 | 91.7% | high | Nov 2025 | Official leaderboard |
| 18 | Kimi K2.5 | 91.1% | Jan 2026 | Lab model card | |
| 19 | Grok 4 Fast | 90.8% | Sep 2025 | Official leaderboard | |
| 20 | | 90.7% | Apr 2026 | Lab model card | |
| 21 | | 90.3% | Feb 2026 | Lab model card | |
| 22 | | 90.2% | Dec 2025 | Lab model card | |
| 23 | gpt-oss-120b | 90% | high | Aug 2025 | Official leaderboard |
| 24 | | 89.8% | Feb 2026 | Lab model card | |
| 25 | | 89.2% | Feb 2026 | Lab model card | |
| 26 | GPT-5 | 89.2% | high | Aug 2025 | Official leaderboard |
| 27 | Kimi K2 Thinking | 89.2% | Nov 2025 | Official leaderboard | |
| 28 | | 89.1% | Apr 2026 | Lab model card | |
| 29 | Grok 4 | 88.3% | Jul 2025 | Official leaderboard | |
| 30 | | 86.8% | Dec 2025 | Lab model card | |
| 31 | Sarvam 105B | 85.8% | Mar 2026 | Lab model card | |
| 32 | | 84.4% | Mar 2026 | Lab model card | |
| 33 | GPT-5 mini | 84.2% | high | Aug 2025 | Official leaderboard |
| 34 | | 84.2% | thinking | Sep 2025 | Official leaderboard |
| 35 | | 82.9% | Mar 2026 | Lab model card | |
| 36 | | 81.9% | Jun 2026 | Lab model card | |
| 37 | GPT-5 nano | 81.7% | high | Aug 2025 | Official leaderboard |
| 38 | | 80% | Jun 2025 | Official leaderboard | |
| 39 | | 80% | Dec 2025 | Lab model card | |
| 40 | | 79.2% | Jan 2026 | Official leaderboard | |
| 41 | | 76.8% | Mar 2026 | Lab model card | |
| 42 | | 75.6% | Feb 2026 | Lab model card | |
| 43 | | 75% | Feb 2026 | Official leaderboard | |
| 44 | Sarvam 30B | 74.2% | Mar 2026 | Lab model card | |
| 45 | | 19.6% | Mar 2026 | Lab model card |
Labs report scores for 28 models in their cards. Switch the scores above to rank them together.
The best score, 99.2%, costs $0.19 a task
Runs on the cost frontier score higher than any run that's cheaper. Step 3.5 Flash comes within 5 points of the best for $0.01 a task, 14 times cheaper. The costs are the leaderboard's own estimates, so compare them only within this benchmark.
Source: Official HMMT Nov 2025 leaderboard
| Model | Effort | Harness | Score | Cost per task | Output tokens |
|---|---|---|---|---|---|
| GPT-5.2 | xhigh | 99.2% | $0.19 | 13,192 | |
| GPT-5.2 | high | 95.8% | $0.14 | 10,015 | |
| | 94.2% | $0.01 | 45,001 | ||
| GLM-5 | 94.2% | $0.10 | 30,083 | ||
| | 93.3% | $0.18 | 14,837 | ||
| Grok 4.1 Fast | reasoning | 93.3% | $0.005 | 10,401 | |
| | 93.3% | $0.01 | 25,249 | ||
| | high | 93.3% | $0.06 | 20,413 | |
| GLM-4.6 | 91.7% | $0.04 | 16,843 | ||
| GPT-5.1 | high | 91.7% | $0.20 | 19,593 | |
| Grok 4 Fast | 90.8% | $0.005 | 10,639 | ||
| gpt-oss-120b | high | 90% | $0.01 | 18,543 | |
| | thinking | 90% | $0.007 | 17,165 | |
| GPT-5 | high | 89.2% | $0.15 | 15,483 | |
| Kimi K2 Thinking | 89.2% | $0.07 | 28,752 | ||
| Kimi K2.5 | high | 89.2% | $0.08 | 26,085 | |
| Grok 4 | 88.3% | $0.22 | 14,792 | ||
| GPT-5 mini | high | 84.2% | $0.03 | 14,859 | |
| | thinking | 84.2% | $0.007 | 17,348 | |
| GPT-5 nano | high | 81.7% | $0.01 | 26,955 | |
| | 80% | $0.22 | 21,190 | ||
| | 79.2% | $0.006 | 28,381 | ||
| | 75% | 39,270 |
3 models have held number one on the official leaderboard since its release in November 2025 4 models have held number one with claims included since its release in November 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 HMMT Nov 2025 leaderboard and labs’ model cards
Grok 4 on the official leaderboard 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: Official HMMT Nov 2025 leaderboard and labs’ model cards
Labs headline it less often now, last in June 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 |
|---|---|---|---|
| Jun 16, 2026 | GLM-5.2 | 94.4 | HMMT Nov. 2025 |
| Apr 22, 2026 | 90.7 | HMMT Nov 25 | |
| Apr 15, 2026 | 89.1 | HMMT Nov 25 | |
| Apr 7, 2026 | GLM-5.1 | 94 | HMMT Nov. 2025 |
| Apr 2, 2026 | 94.6 | HMMT Nov 25 | |
| Mar 30, 2026 | 84.4 | HMMT Nov 25 | |
| Mar 6, 2026 | Sarvam 30B | 74.2 | HMMT Nov 2025 |
| Mar 6, 2026 | Sarvam 105B | 85.8 | HMMT (Nov 25) |
| Mar 2, 2026 | 19.6 | HMMT Nov 25 | |
| Mar 2, 2026 | 76.8 | HMMT Nov 25 | |
| Mar 2, 2026 | 82.9 | HMMT Nov 25 | |
| Feb 24, 2026 | 89.2 | HMMT Nov 25 | |
| Feb 24, 2026 | 89.8 | HMMT Nov 25 | |
| Feb 24, 2026 | 90.3 | HMMT Nov 25 | |
| Feb 16, 2026 | 92.7 | HMMT Nov 25 | |
| Feb 14, 2026 | 93.3 | HMMT Nov 2025 | |
| Feb 11, 2026 | GLM-5 | 96.9 | HMMT Nov. 2025 |
| Feb 10, 2026 | 98.3 | Best of HMMT (Nov. 25) (Mean@64) 97.34 / Heavy Thinking 98.33 | |
| Feb 2, 2026 | 94 | HMMT 2025 (Nov.) | |
| Jan 23, 2026 | 94.7 | HMMT Nov 25 | |
| Dec 31, 2025 | 80 | HMMT 2025 (Nov) | |
| Dec 31, 2025 | 86.8 | HMMT Nov 2025 | |
| Dec 22, 2025 | GLM-4.7 | 93.5 | HMMT Nov. 2025 |
| Dec 1, 2025 | 90.2 | HMMT Nov 2025 (Pass@1) |
11 system cards report it, from 9 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 |
|---|---|---|---|---|
| Jun 13, 2026 | | 81.9 | HMMT-Nov25, Mean@64, CoT (Table 5) | Capabilities |
| Apr 17, 2026 | | 84.4 | HMMT Nov 25 (Table 4) | Capabilities |
| Feb 28, 2026 | | 75.6 | HMMT25 Nov (Table 9) | Capabilities |
| Feb 17, 2026 | GLM-5 technical report | 96.9 | HMMT Nov. 2025 (Table 7) | Capabilities |
| Feb 14, 2026 | | 93.3 | HMMT Nov 2025 (Table 3) | Capabilities |
| Feb 11, 2026 | | 94 | HMMT 2025 Nov., avg of 64 (Table 5). PaCoRe 97.8, with Python 98.0 (Table 12) | Capabilities |
| Jan 30, 2026 | Kimi K2.5 technical report | 91.1 | HMMT Nov 2025, average 24k output tokens (Table 5) | Capabilities |
| Jan 11, 2026 | | 80 | HMMT 2025 (Nov) (Table 6) | Capabilities |
| Jan 5, 2026 | | 86.8 | HMMT Nov 2025 (Table 3, Reasoning mode). Non-reasoning 43.2 (Table 4) | Capabilities |
| Dec 1, 2025 | | 90.2 | HMMT Nov 2025 (Pass@1), DeepSeek-V3.2 Thinking (Table 2) | Capabilities |
| Dec 1, 2025 | | 94.4 | HMMT Nov 2025 (Pass@1), DeepSeek-V3.2-Speciale (Table 3) | Capabilities |
The lab's number comes out ahead in 4 of 5 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. Every benchmark.
| Model | Lab says | Board says | Gap |
|---|---|---|---|
| GLM-5 | 96.9% HMMT Nov. 2025 | 94.2% Leaderboard | +2.7 pts |
| Kimi K2.5 | 91.1% HMMT Nov 2025, average 24k output tokens (Table 5) | 89.2% Leaderboard, high | +1.9 pts |
| | 94.4% HMMT Nov 2025 (Pass@1), DeepSeek-V3.2-Speciale (Table 3) | 93.3% Leaderboard | +1.1 pts |
| | 90.2% HMMT Nov 2025 (Pass@1) | 90% Leaderboard, thinking | +0.2 pts |
| | 94% HMMT 2025 (Nov.) | 94.2% Leaderboard | −0.2 pts |
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