Enterprise AI Research Analysis
Performance evaluation of generative pre-trained transformer on the National Veterinary Licensing Examination in Japan
This study evaluated the performance of GPT models (GPT-4o, o1, o3) on the National Veterinary Licensing Examination (NVLE) in Japan. GPT-o3, using Japanese input and a normal prompt, achieved the highest performance on the 74th NVLE, outperforming GPT-4o and o1. Validation tests on the 75th and 76th NVLEs showed GPT-o3 exceeded the minimum passing score in all sections, with an overall score of 92.9%. The findings suggest that recent GPT models can reliably answer the Japanese NVLE without translation or elaborate prompt engineering, indicating their potential as supportive tools in veterinary education and knowledge assistance in Japan.
Key Findings & Business Impact
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GPT-o3 Overall Score (76th NVLE)
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GPT-o3 Passing Rate (All Sections)
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GPT-o3 (74th NVLE) vs. GPT-4o
Deep Analysis & Enterprise Applications
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Model Performance
Prompt & Language Impact
Validation & Reliability
Model Performance
The study compared GPT-4o, o1, and o3 on the 74th NVLE. GPT-o3 consistently outperformed GPT-4o, especially in image-based sections. O1 and o3 showed significantly improved reasoning ability over GPT-4o, achieving passing scores across all sections.
93.0%
GPT-o3 Overall Score on 74th NVLE (Japanese, Normal Prompt)
| Model | Overall Score (%) |
|---|---|
| GPT-4o | 77.5% |
| GPT-o1 | 92.2% |
| GPT-o3 | 93.0% |
GPT-o3's Leap in Visual-Textual Reasoning
Notably, GPT-o3 excelled in image-based sections (C and D) where GPT-4o struggled, failing to meet the minimum passing rate in Section C. This highlights the significant advancement in visual-textual integration and reasoning capabilities in newer GPT models, crucial for complex veterinary examinations. GPT-o3's performance in image-based questions was a key differentiator, showcasing enhanced reasoning.
Prompt & Language Impact
The study analyzed the impact of prompt design (Normal vs. Optimized) and language (Japanese vs. English, with various translation prompts) on GPT-o3's performance. Surprisingly, no significant difference was observed across these conditions.
No Significant Difference
Between Prompt/Language Settings for GPT-o3
Prompt and Language Comparison Process (GPT-o3, 74th NVLE)
74th NVLE Questions (Japanese)
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Normal Prompt
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Optimized Prompt
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Japanese Input
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English Input (Normal Translation)
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English Input (Optimized Translation)
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Performance Evaluation
| Setting | Overall Score (%) |
|---|---|
| Normal/Japanese | 93.0% |
| Normal/English: Normal | 90.4% |
| Normal/English: Optimized | 91.1% |
| Optimized/Japanese | 91.8% |
| Optimized/English: Normal | 90.2% |
| Optimized/English: Optimized | 91.6% |
Validation & Reliability
GPT-o3's performance was validated on the 75th (2024) and 76th (2025) NVLEs using Japanese input and the normal solving prompt. It consistently exceeded the minimum passing rate in all sections, demonstrating high reliability and advanced Japanese comprehension.
92.9%
Average Overall Score on 75th & 76th NVLE (GPT-o3)
| Examination | Overall Score (%) |
|---|---|
| 75th NVLE (2024) | 92.3% |
| 76th NVLE (2025) | 93.4% |
Minimal Impact of Data Leakage on 76th NVLE Performance
The 76th NVLE was released after the knowledge cutoff of GPT-o3, making its high performance (93.4%) a strong indicator of the model's innate capabilities rather than just data leakage. This strengthens the reliability of GPT-o3 as a veterinary education and knowledge assistance tool. 93.4% on 76th NVLE confirms innate capability, not just data leakage.
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Annual Cost Savings
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Annual Hours Reclaimed
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Your AI Implementation Roadmap
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Phase 1: Needs Assessment & Customization
Identify specific veterinary educational and clinical support needs. Customize GPT-o3 prompts and integrate with existing systems for knowledge assistance and decision support. (Estimated: 2-4 weeks)
Phase 2: Pilot Deployment & User Training
Deploy GPT-o3 in a pilot program with a small group of veterinarians and students. Provide comprehensive training on effective interaction and ethical use of the AI. (Estimated: 4-6 weeks)
Phase 3: Feedback & Iteration
Collect user feedback and performance data. Iterate on prompt engineering, integration, and training materials to optimize utility and accuracy. (Estimated: 3-5 weeks)
Phase 4: Full-Scale Integration & Monitoring
Roll out GPT-o3 across the organization. Establish continuous monitoring protocols for performance, accuracy, and user adoption, ensuring ongoing value and ethical compliance. (Estimated: 6-8 weeks)
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