The author conducts a transparent, objective assessment of several large language models on the 2025 Chinese national math exam, converting all questions to LaTeX, applying strict Gaokao scoring rules, and revealing each model's strengths and weaknesses across single‑choice, multiple‑choice, and fill‑in‑the‑blank items.
A recent evaluation had six leading large‑language‑model products (GPT‑4o, GLM‑4, Wenxin 4.0, Doubao, Baichuan 4, and Qwen‑2.5) answer the first 14 objective questions of the new Gaokao mathematics I paper, revealing that only GLM‑4 surpassed the 60% passing threshold while the others performed far below expectations.
This case study details how Baidu Search transformed its Gaokao services by introducing a full‑process personalized companion module, an intuitive volunteer‑selection tool, and an efficient information architecture, resulting in higher user engagement, improved satisfaction, and notable growth in the 2023 exam season.
This article reviews Baidu's three‑year evolution of its Gaokao promotion—starting with youthful visual branding in 2021, moving to intelligent, AI‑enhanced experiences in 2022, and finally adopting collaborative efficiency and AI‑generated assets in 2023—to illustrate how product design, branding, and technology were aligned with changing market demands.
This article uses Python to scrape and analyze over 2,900 Chinese university and major data points, revealing trends in Gaokao participation, provincial enrollment, university types, popularity rankings, and public curiosity about majors, all illustrated with charts and code examples.
Using Python, the author analyzes Shandong’s 2020 Gaokao simulation scores, visualizing distribution patterns, pass rates, subject selection ratios, top‑student combinations, and double‑first‑class university admission thresholds, providing data‑driven insights for students and educators.
The article argues that predictability—evident in Baidu’s Gaokao essay forecasts and formulaic Hollywood blockbusters—arises when markets favor safe, widely appealing content, making simple systems like baseball easy to predict while complex systems with feedback loops resist accurate forecasting despite apparent creativity.
