The introduction of RealMath-Eval highlights the limitations of state-of-the-art Large Language Models (LLMs) in evaluating authentic human reasoning in high-school mathematics, revealing a significant 'Evaluation Gap' when compared to synthetic solutions. This suggests that current evaluation methods may not effectively capture the complexity of real student reasoning, potentially impacting the development of AI educational tools.