aiaimodel.cards
← All benchmarks

MMLU

Multiple-choice questions across dozens of academic subjects.

Your workloadRAG over docs · 12K in · 600 out · 50K requests/mo · 30% cached
  1. 1GPT-4.1 · OpenAIbest value
    90.2%
  2. 2gpt-oss-120b · OpenAIbest value
    90.0%
  3. 3GPT-4.1 Mini · OpenAI
    87.5%
  4. 4gpt-oss-20b · OpenAIbest value
    85.3%
  5. 5GPT-4o Mini · OpenAI
    82.0%

“Best value”: no other model here reports a higher score at a lower cost for your workload. Scores are self-reported by each maker with different settings, so treat close calls as ties.

How each maker reported it

  • GPT-4.1 openai/simple-evals README; Prompting Guide §1

    OpenAI's simple-evals results (zero-shot chain-of-thought, system prompt "You are a helpful assistant."). MATH is MATH-500 for models released on or after o1; OpenAI considers MGSM and DROP saturated for newer models. The repo stopped adding results in July 2025. SWE-bench Verified is OpenAI's own agentic harness result from the prompting guide.

  • gpt-oss-120b Figures 1, 2, 4; Table 2

    OpenAI's own pass@1 results at reasoning level high. AIME and HLE with tools; Codeforces with a terminal tool. o4-mini and o3 values read from OpenAI's charts.

  • GPT-4.1 Mini openai/simple-evals README

    OpenAI's simple-evals results (zero-shot chain-of-thought, system prompt "You are a helpful assistant."). MATH is MATH-500 for models released on or after o1; OpenAI considers MGSM and DROP saturated for newer models. The repo stopped adding results in July 2025.

  • gpt-oss-20b Figures 1, 2, 4; Table 2

    OpenAI's own pass@1 results at reasoning level high. AIME and HLE with tools; Codeforces with a terminal tool. o3-mini was run without tools on AIME, HLE and Codeforces, so those cells are left empty. Baseline values read from OpenAI's charts.

  • GPT-4o Mini openai/simple-evals README; GPT-4o System Card Tables 8–10, p.24–25

    OpenAI's simple-evals results (zero-shot chain-of-thought, system prompt "You are a helpful assistant."). MATH is MATH-500 for models released on or after o1; OpenAI considers MGSM and DROP saturated for newer models. The repo stopped adding results in July 2025. Language rows are 0-shot accuracy from the GPT-4o System Card (translated ARC-Easy, translated TruthfulQA, Uhura-Eval). GPT-4o values: simple-evals uses the gpt-4o-2024-05-13 snapshot; the system card does not name a snapshot.

Only each model's own maker's number is shown; scores a maker reports for rival models are left out.