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OpenAI's o4-mini model achieves 90% accuracy on physics problems, but struggles with images

A new arXiv paper evaluates OpenAI's o4-mini model on introductory physics problems from Halliday and Resnick's "Fundamentals of Physics." The model achieved approximately 90% accuracy overall, but performance varied significantly based on problem representation and difficulty. Text-only problems were solved with 96% accuracy, while problems requiring interpretation of both text and images saw only 79% accuracy. The model's accuracy also decreased notably as problem difficulty increased. AI

IMPACT Demonstrates current LLM capabilities in complex problem-solving but highlights limitations in multimodal understanding and difficulty scaling.

RANK_REASON Academic paper evaluating an AI model's performance on a specific task. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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

OpenAI's o4-mini model achieves 90% accuracy on physics problems, but struggles with images

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Academic paper evaluating an AI model's performance on a specific task. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Amir Bralin, N. Sanjay Rebello ·

    Assessing AI in Introductory Physics Problem Solving

    arXiv:2607.14303v1 Announce Type: cross Abstract: Reasoning or inference-scaling models are the new generation of Large Language Models (LLMs) capable of complex problem solving. To investigate their problem-solving capability in physics, we evaluated model o4-mini by OpenAI on s…