Wikibench

TheoremQA

math official site →

Multilingual: no

A theorem-driven question answering dataset containing 800 high-quality questions covering 350+ theorems from Math, Physics, EE&CS, and Finance. Designed to evaluate AI models' capabilities to apply theorems to solve challenging university-level science problems.

Methodology

Imported from llm-stats public benchmark metadata. Modality: text. Max score: 1. Categories: finance, math, physics, reasoning. Language: en. Verified by llm-stats: no.

Leaderboard

Showing 6 of 6 results

  1. Qwen2 72B Instruct self-reported llm-stats
    44.4%
  2. Qwen2.5 32B Instruct self-reported llm-stats
    44.1%
  3. Qwen2.5-Coder 32B Instruct self-reported llm-stats
    43.1%
  4. Qwen2.5 14B Instruct self-reported llm-stats
    43.0%
  5. Qwen2.5-Coder 7B Instruct self-reported llm-stats
    34.0%
  6. Qwen2 7B Instruct self-reported llm-stats
    25.3%