QuantBench
Models answer 25 multiple choice versions of quant trading firm reasoning puzzles. Scored as cons@16 accuracy.
OpenAI contextual evaluation. Questions come from competitions run by firms such as Jane Street.
- Made by
- OpenAI
- Released
- September 2024
- Kind
- Competition problems with answers
- Level
- Competition
- Scored
- Checked automatically
- Answers
- Multiple choice
- Tasks
- Kept private
- Strongest model tested
- o1 #117 on the capability index
- Last in a system card
- December 2024
- Last model added
- December 2024
o1 leads with 60% among models released by December 2024
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.
The newest model with a score here came out in December 2024, 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
- 1 o1 60%
- 2 o1-mini 48%
- 3 o1-preview 36%
Source: Labs’ model cards
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | o1 | 60% | Dec 2024 | Lab model card | |
| 2 | o1-mini | 48% | Sep 2024 | Lab model card | |
| 3 | o1-preview | 36% | Sep 2024 | Lab model card |
2 models have held number one in labs’ own numbers since its release in September 2024
Lab claims count from the day the card came out, independent runs from the model’s release.
Source: 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.
Source: Labs’ model cards
Labs report it only in system cards
We read the headline results of 522 launch posts from 52 labs, and none of them list this benchmark. Some system cards do, below.
3 system cards report it, from 1 lab
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 |
|---|---|---|---|---|
| Dec 5, 2024 | o1 system card | 60 | QuantBench, cons@16, o1 (post-mitigation), printed chart label (8.3) | Capabilities |
| Sep 12, 2024 | o1-preview system card | 36 | QuantBench: Multiple-Choice, pass rate cons@16, o1-preview (post-mitigation), printed chart label (8.5) | Capabilities |
| Sep 12, 2024 | o1-mini system card | 48 | QuantBench: Multiple-Choice, pass rate cons@16, o1-mini (post-mitigation), printed chart label (8.5) | Capabilities |
More in Math
- 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%
- IMO-AnswerBench In use 400 olympiad problems with short verifiable answers, robustified against memorization. Scored by answer match. GLM-5.2 91%
- 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% - MathArena (Apex, IMO, USAMO) In use Evaluates models on newly released math competitions after release. Final-answer or human/LLM-judged proof scores. Claude Opus 4.8 81.3%
- MathArena Apex Shortlist In use Models solve 47 hard final-answer problems that MathArena selected from 2025 competitions, where the best models scored about 50% at selection. Scored by accuracy over repeated attempts. GPT-5.5 98.4%