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LLMs Ace Undergraduate Music Theory Test, Outperforming Expectations

A recent test evaluating Large Language Models on undergraduate music theory revealed that current models perform exceptionally well, surpassing the difficulty of the designed benchmark. GPT-5.6 Sol achieved a perfect score, while other advanced models like Claude Sonnet 5 and GPT-5.5 also scored highly. Notably, some newer models like Gemini-3.1 Pro performed worse than their predecessors, a phenomenon the author could not explain. AI

IMPACT Demonstrates advanced reasoning capabilities in LLMs, potentially impacting educational assessment tools and the need for more sophisticated benchmarks.

RANK_REASON The item describes a test of existing LLMs on a specific academic subject, not a new model release or significant industry event. [lever_c_demoted from research: ic=1 ai=0.7]

Read on LessWrong (AI tag) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

LLMs Ace Undergraduate Music Theory Test, Outperforming Expectations

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The item describes a test of existing LLMs on a specific academic subject, not a new model release or significant industry event. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. LessWrong (AI tag) TIER_1 English(EN) · Waldvogel ·

    Testing LLMs on Undergraduate Music Theory

    <p><span>I spent the past week designing a test that I hoped would serve as a benchmark. But LLMs are improving faster than I expected, and my devilishly hard questions turned out to be a cakewalk.</span></p><p><span>Here are the results of testing five modern LLMs on undergradua…