Reasoning Models Ace the CFA Exams
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Researchers evaluate state-of-the-art reasoning models on mock CFA exams consisting of 980 questions across all three certification levels. While previous studies reported that LLMs performed poorly on these exams, the latest reasoning models now pass all three levels, with Gemini 3.0 Pro achieving a record 97.6% on Level I. - **Top performers:** Gemini 3.0 Pro, Gemini 2.5 Pro, GPT-5, Grok 4, Claude Opus 4.1, and DeepSeek-V3.1 all pass every level. GPT-5 leads Level II with 94.3%, while Gemini 2.5 Pro achieves 86.4% on Level III multiple-choice and Gemini 3.0 Pro scores 92.0% on constructed-response questions. - **Dramatic improvement from baselines:** ChatGPT (GPT-3.5) failed all levels, GPT-4 passed Levels I and II but failed Level III, and GPT-4o passed all three. The new reasoning models achieve near-perfect scores on Levels I and II. - **Shifting difficulty patterns:** Quantitative domains, previously identified as primary weaknesses for LLMs, now show near-zero error rates for top models. Ethical and Professional Standards remains the most challenging area with 17-21% error rates on Level II. - **Chain-of-thought trade-offs:** CoT prompting helps baseline models significantly but shows inconsistent effects on reasoning models for MCQs. However, CoT remains highly effective for constructed-response questions, boosting Gemini 3.0 Pro from 86.6% to 92.0%.
Top performers: Gemini 3.0 Pro, Gemini 2.5 Pro, GPT-5, Grok 4, Claude Opus 4.1, and DeepSeek-V3.1 all pass every level. GPT-5 leads Level II with 94.3%, while Gemini 2.5 Pro achieves 86.4% on Level III multiple-choice, and Gemini 3.0 Pro scores 92.0% on constructed-response questions.
Dramatic improvement from baselines: ChatGPT (GPT-3.5) failed all levels, GPT-4 passed Levels I and II but failed Level III, and GPT-4o passed all three. The new reasoning models achieve near-perfect scores on Levels I and II.
Shifting difficulty patterns: Quantitative domains, previously identified as primary weaknesses for LLMs, now show near-zero error rates for top models. Ethical and Professional Standards remain the most challenging area, with 17-21% error rates on Level II.
Chain-of-thought trade-offs: CoT prompting helps baseline models significantly but shows inconsistent effects on reasoning models for MCQs. However, CoT remains highly effective for constructed-response questions, boosting Gemini 3.0 Pro from 86.6% to 92.0%.
Abstract
Previous research has reported that large language models (LLMs) demonstrate poor performance on the Chartered Financial Analyst (CFA) exams. However, recent reasoning models have achieved strong results on graduate-level academic and professional examinations across various disciplines. In this paper, we evaluate state-of-the-art reasoning models on a set of mock CFA exams consisting of 980 questions across three Level I exams, two Level II exams, and three Level III exams. Using the same pass/fail criteria from prior studies, we find that most models clear all three levels. The models that pass, ordered by overall performance, are Gemini 3.0 Pro, Gemini 2.5 Pro, GPT-5, Grok 4, Claude Opus 4.1, and DeepSeek-V3.1. Specifically, Gemini 3.0 Pro achieves a record score of 97.6% on Level I. Performance is also strong on Level II, led by GPT-5 at 94.3%. On Level III, Gemini 2.5 Pro attains the highest score with 86.4% on multiple-choice questions while Gemini 3.0 Pro achieves 92.0% on constructed-response questions.
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