HMMT Nov 25
HMMT Nov 25 - Harvard-MIT Mathematics Tournament November 2025.
Category
STEM & Reasoning
Score type
percent
Scale
100%
higher is better
Models tested
12
What is HMMT Nov 25?
HMMT Feb 26 is the February round of the Harvard-MIT Mathematics Tournament 2026. HMMT problems are considerably harder than AIME and count among the most difficult high-school competition math in the USA. Models must solve the problems with exact answers — recent tournaments are almost immune to training-data leakage.
What does it test?
HMMT Nov 25 measures hard reasoning in science, technology, engineering and math. In detail, it checks:
- olympiade-level insight instead of memorising standard tasks
- correct exact answers within a fixed time window
- advanced algebra, combinatorics, number theory and geometry
- resistance to data contamination thanks to very recent problems
How to read the score
The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better.
Frequently asked questions
What is the HMMT Nov 25 benchmark?
HMMT Feb 26 is the February round of the Harvard-MIT Mathematics Tournament 2026. HMMT problems are considerably harder than AIME and count among the most difficult high-school competition math in the USA. Models must solve the problems with exact answers — recent tournaments are almost immune to training-data leakage.
What does HMMT Nov 25 test?
HMMT Nov 25 mainly measures hard reasoning in science, technology, engineering and math. Concretely, it checks: olympiade-level insight instead of memorising standard tasks; correct exact answers within a fixed time window; advanced algebra, combinatorics, number theory and geometry.
How is the HMMT Nov 25 score calculated?
The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better. The declared maximum score of this benchmark is 100.0.
Where do I get HMMT Nov 25 data and scores?
The official benchmark page/reference is linked on this page. Every score on Open LLM Radar is also available as open data: download the scores JSON (http://open-llm-radar-api:8000/api/v1/benchmarks/hmmt-nov-25/scores) or pull it directly from the Open LLM Radar API with any HTTP client.
Benchmark data & downloads
Where to get, inspect and reuse the data behind this benchmark.
Benchmark dataset
The question/task data itself — download and evaluate locally
Benchmark metadata (JSON)
This page's benchmark record from the Open LLM Radar API
All model scores (JSON download)
Full score table as JSON; paginate with limit/offset params
Open LLM Radar API docs
Swagger UI to explore and reuse all radar API endpoints
Model scores 12 models tested
| # | Model | Score | Date | Source | Verified |
|---|---|---|---|---|---|
| 1 |
GLM-5.2
Zhipu AI
|
94.4%
|
17.06.2026 | Report | Verified |
| 2 |
DeepSeek-V4-Pro
DeepSeek
|
94.4%
|
17.06.2026 | Report | Unverified |
| 3 |
Qwen3.6-27B
Qwen Team (Alibaba Cloud)
|
90.7%
|
22.04.2026 | Qwen Team (official model card) | Verified |
| 4 |
Qwen3.5-122B-A10B
Qwen Team (Alibaba Cloud)
|
90.3%
|
01.02.2026 | Report | Verified |
| 5 |
Qwen3.5-27B
Qwen Team (Alibaba Cloud)
|
89.8%
|
16.04.2026 | Qwen Team (official model card - comparison) | Unverified |
| 6 |
Qwen3-235B-A22B
Qwen Team (Alibaba Cloud)
|
89.5%
|
01.02.2026 | Report | Unverified |
| 7 |
Qwen3.5-35B-A3B
Qwen Team (Alibaba Cloud)
|
89.2%
|
16.04.2026 | Qwen Team (official model card - comparison) | Unverified |
| 8 |
Qwen3.6-35B-A3B
Qwen Team (Alibaba Cloud)
|
89.1%
|
16.04.2026 | Qwen Team (official model card) | Verified |
| 9 |
Gemma4-31B-it
Google
|
87.5%
|
16.04.2026 | Qwen Team (official model card - comparison) | Unverified |
| 10 |
Gemma4-26B-A4B
Google
|
87.5%
|
16.04.2026 | Qwen Team (official model card - comparison) | Unverified |
| 11 |
MiniMax-M3
MiniMaxAI
|
84.4%
|
17.06.2026 | Report | Unverified |
| 12 |
Qwen3.5-4B
Qwen
|
76.8%
|
01.02.2026 | Report | Verified |