Large Language Models (LLMs) have demonstrated remarkable success across a wide range of industries, primarily due to their impressive generative abilities. Yet, their potential in applications requiring cognitive abilities, such as psychological counseling, remains largely untapped. This paper investigates the key question: \textit{Can LLMs be effectively applied to psychological counseling?} To determine whether an LLM can effectively take on the role of a psychological counselor, the first step is to assess whether it meets the qualifications required for such a role, namely the ability to pass the U.S. National Counselor Certification Exam (NCE). This is because, just as a human counselor must pass a certification exam to practice, an LLM must demonstrate sufficient psychological knowledge to meet the standards required for such a role. To address this, we introduce PsychCounsel-Bench, a benchmark grounded in U.S.national counselor examinations, a licensure test for professional counselors that requires about 70\% accuracy to pass. PsychCounsel-Bench comprises approximately 2,252 carefully curated single-choice questions, crafted to require deep understanding and broad enough to cover various sub-disciplines of psychology. This benchmark provides a comprehensive assessment of an LLM's ability to function as a counselor. Our evaluation shows that advanced models such as GPT-4o, Llama3.3-70B, and Gemma3-27B achieve well above the passing threshold, while smaller open-source models (e.g., Qwen2.5-7B, Mistral-7B) remain far below it. These results suggest that only frontier LLMs are currently capable of meeting counseling exam standards, highlighting both the promise and the challenges of developing psychology-oriented LLMs. We release the proposed dataset for public use: https://github.com/cloversjtu/PsychCounsel-Bench

翻译：大语言模型（LLMs）凭借其出色的生成能力，已在众多行业展现出显著成就。然而，其在需要认知能力的应用场景（如心理咨询）中的潜力仍未被充分挖掘。本文探讨一个核心问题：\textit{LLMs 能否有效应用于心理咨询？} 要判断一个 LLM 能否有效承担心理咨询师的角色，首先需要评估其是否满足该角色所需的资质，即能否通过美国国家心理咨询师认证考试（NCE）。这是因为，正如人类咨询师必须通过认证考试才能执业，LLM 也必须展现出足够的心理学知识以满足该角色的标准。为此，我们提出了 PsychCounsel-Bench，这是一个基于美国国家心理咨询师考试的基准测试。该考试是美国专业咨询师的执业资格考试，通常要求约 70\% 的正确率才能通过。PsychCounsel-Bench 包含了约 2,252 道精心筛选的单选题，这些题目旨在考察对心理学的深入理解，并广泛覆盖了心理学的各个子学科。该基准为评估 LLM 作为咨询师的能力提供了全面的衡量标准。我们的评估结果显示，GPT-4o、Llama3.3-70B 和 Gemma3-27B 等先进模型的表现远超通过阈值，而较小的开源模型（如 Qwen2.5-7B、Mistral-7B）则远低于该阈值。这些结果表明，目前只有前沿的 LLMs 能够达到心理咨询考试的标准，这既凸显了开发面向心理学的 LLMs 的前景，也揭示了其面临的挑战。我们公开发布了所提出的数据集以供使用：https://github.com/cloversjtu/PsychCounsel-Bench