ChatGPT Outperforms Humans on Japan Entrance Exams

According to LifePrompt Inc., OpenAI's ChatGPT 5.2 Thinking model took the 2026 undergraduate entrance exams for the University of Tokyo and Kyoto University and achieved scores higher than the highest successful human applicants, as reported by Kyodo News, The Straits Times, and Bangkok Post. Per LifePrompt, the model scored 503 out of 550 on the University of Tokyo Natural Sciences exam and 452 out of 550 on Humanities and Social Sciences; the university-listed top scores were 453 and 434 respectively. LifePrompt also reported a perfect score in mathematics, 90% in English, and 25% on essay-style questions such as World History. For Kyoto University, LifePrompt reported 771 in the Faculty of Law exam versus a top passing score of 734, and 1,176 in the Faculty of Medicine exam versus 1,098 for the top scorer. The tests were run by converting exam questions into image data and feeding them to the model; essay answers were graded by teachers from cram school Kawai Juku, per the reporting. Kyodo News and other outlets noted LifePrompt's prior experiments, including a failed 2024 run with ChatGPT 4 and a subsequent passing-level result with a model named o1 in 2025. The LifePrompt head Satoshi Endo was quoted saying, "The AI's capabilities have been well documented. Given the rapid pace of AI evolution, companies will need to adopt AI with an eye toward how business operations will look in 10 to 20 years," in coverage by Kyodo News and Bangkok Post.

The LifePrompt tests highlight two technical points relevant to practitioners. First, using image-based inputs to evaluate a language model requires a reliable image-to-text pipeline: question conversion, layout preservation, and OCR accuracy materially affect what the model actually receives. Second, the split performance pattern reported -- near-perfect scores on structured mathematical problems and weaker results on open-ended essays -- is consistent with recent improvements in chain-of-thought reasoning and symbolic problem solving in large multimodal models, contrasted with persistent weaknesses in long-form subjective composition and world knowledge framing. Observers should treat the numerical scores as results of a specific evaluation setup rather than as an absolute measure of general intelligence; in this case essays were human-graded, adding a subjective element to final tallies.

Industry observers have used standardized tests as repeatable probes of model capabilities because they combine domain knowledge, reasoning, and time-limited problem solving. Reporting on these Japan entrance exam results fits that pattern: public-facing academic benchmarks are low-friction ways to show progress to nontechnical audiences. At the same time, such demonstrations do not directly translate to real-world deployment readiness for education, proctoring, or assessment tasks without addressing test security, adversarial input, and human-evaluation variability.

Observers and practitioners should look for:

• •reproducibility and methodology disclosure from LifePrompt or independent researchers, including exact prompts and OCR pipeline details
• •cross-evaluator agreement on essay grading and whether rubric-based scoring changes relative rankings
• •follow-up evaluations on adversarially framed questions and time-constrained problem solving. Additionally, official statements from the examined institutions or test authorities about permitted use of their materials would clarify policy and integrity implications