Math23K
Models solve Chinese elementary-school math word problems from a set of about 23,000. Scored by final-answer accuracy.
Introduced with the Deep Neural Solver paper at EMNLP 2017.
- Made by
- Tencent AI Lab (Wang et al.)
- Released
- September 2017
- Kind
- Word problems
- Level
- School
- Scored
- Checked automatically
- Answers
- Short answer
- Tasks
- All public
- Strongest model tested
-
Qwen-14B #213 on the capability index
- Last in a system card
- June 2024
- Last model added
- June 2024
GLM-4 leads with 88.5% among models released by January 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 January 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
Source: Labs’ model cards
2 models have held number one in labs’ own numbers since 2023
Lab claims count from the day the card came out, independent runs from the model’s release.
Source: Labs’ model cards
Z.ai’s own number for GLM-4 passed 85% in June 2024
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 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 |
|---|---|---|---|---|
| Jun 18, 2024 | GLM-4 technical report | 88.5 | GLM-4 All Tools (Web, 0116), Python Interpreter, Math23K (Table 9) | Capabilities |
| Sep 28, 2023 | | 51.2 | Math23K, greedy decoding (Table 12) | Capabilities |
| Sep 28, 2023 | | 67 | Math23K, greedy decoding (Table 12) | Capabilities |
More in Math
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- 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%