SuperCLUE-Math6
DeepSeek-V2 (MoE-236B, May 2024) 83.3 Only in system cards Models solve thousands of multi-step Chinese math word problems. Scores combine reasoning-step quality and accuracy into a comprehensive score and a reasoning level.
Reports give a comprehensive score, a reasoning-steps score, an overall accuracy score and a reasoning level from 1 to 5.
In the authors’ words
We introduce SuperCLUE-Math6(SC-Math6), a new benchmark dataset to evaluate the mathematical reasoning abilities of Chinese language models. SC-Math6 is designed as an upgraded Chinese version of the GSM8K dataset with enhanced difficulty, diversity, and application scope. It consists of over 2000 mathematical word problems requiring multi-step reasoning and providing natural language solutions. We propose an innovative scheme to quantify the reasoning capability of large models based on performance over problems with different reasoning steps. Experiments on 13 representative Chinese models demonstrate a clear stratification of reasoning levels, with top models like GPT-4 showing superior performance. SC-Math6 fills the gap in Chinese mathematical reasoning benchmarks and provides a comprehensive testbed to advance the intelligence of Chinese language models.
- Level
- School Students, from grade school to high school
- Scored
- Graded by a model A language model scores each response, usually against a rubric.
- Answers
- Short answer A number, word or short string matched to a key.
DeepSeek-V2 (MoE-236B, May 2024) leads with 83.3
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.
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | DeepSeek-V2 (MoE-236B, May 2024) | 83.3 | May 2024 | Model card |
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Labs report it only in system cards
We read the headline results of 479 launch posts from 51 labs, and none of them list this benchmark. Some system cards do, below.
One system card reports it
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 |
|---|---|---|---|---|
| 7 May 2024 | DeepSeek-V2 (MoE-236B, May 2024) technical report | 83.3 | SC-Math6 Comprehensive Score, Reasoning Level 5, reasoning-steps score 85.73, overall accuracy score 84.54 (Table 11) | Capabilities |
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