EntropyMath Leaderboard

TokyoMathematics · English

30 problems 7 models

K-LLM Project · 독파모 / EntropyMath 평가 차수 안내

K-LLM Project는 대한민국 과학기술정보통신부의 「독자 AI 파운데이션 모델 프로젝트」(통칭 독파모)을 뜻합니다.

Round 1·2·3은 EntropyMath의 1차·2차·3차 모델 평가를 뜻합니다. 과기정통부의 공식 단계평가 번호나 통과 여부를 뜻하지 않습니다.

프로젝트 공식 안내 공식 1차 단계평가 공식 2차 단계평가

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Evaluation details · 평가 방법 3 runs / problem
  • Accuracy counts correct answers across all three attempts. Pass@3 counts problems with at least one correct answer. Errors and timeouts count as incorrect.
  • Token averages use only runs with reported usage; missing usage is not treated as zero.
  • Select a result cell for the recorded problem, reference answer, model response, and all three attempts. Missing responses and usage remain explicitly unreported.
  • Tokyo uses a private source dataset. Review access before publishing its problem and response details.

Model Accuracy vs Pass@3

100%
75%
50%
25%
0%
KT Mi:dm 2.0 Base Instruct
Solar Pro 3
Solar Pro 3
DeepSeek V4 Pro
Claude Opus 4.8
Gemini 3.5 Flash
GPT-5.5
K-EXAONE-236B-A23B
K-EXAONE-236B-A23B
Accuracy
Pass@3

Avg Tokens per Reported Run

8,724
6,543
4,362
2,181
0
K-EXAONE-236B-A23B
K-EXAONE-236B-A23B
Solar Pro 3
Solar Pro 3
Gemini 3.5 Flash
DeepSeek V4 Pro
KT Mi:dm 2.0 Base Instruct
Claude Opus 4.8
GPT-5.5
Avg Tokens / Problem
About this benchmark

Tokyo university entrance mathematics: 30 problems, three runs per model. Select a result cell to review the recorded problem and model response.

Entrance Exams brings university entrance examinations together, including verbal reasoning and mathematics. Results remain separate by exam, year, subject, and evaluation language.

Results are reported using Pass@3 metrics to account for generation variance. Detailed execution traces are available for transparency.

Performance Legend

Mastery (100%)
3/3
Strong (66%)
2/3
Weak (33%)
1/3
Fail (0%)
0/3