On June 10, 2026, Alibaba Qwen officially launched the country's first full-cycle college entrance examination volunteer application Agent, offering free personalized application and consultation services to millions of candidates across the country, marking a further deepening of large model applications in vertical livelihood fields.
This Agent is based on the Qwen College Entrance Examination Volunteer Large Model and has been deeply integrated with Quark's eight years of experience in college entrance examination data. The product's core features include "Volunteer Calendar," "Volunteer Report," and "Volunteer Q&A." It not only masters professional application methods such as the "Ranking Method," but also provides accurate volunteer planning suggestions by combining annual university admission data and user behavior understanding. After candidates input their selected subjects and estimated scores, the system will customize a "Volunteer Calendar" according to the provincial time nodes.
This year, the newly upgraded "Volunteer Report" has enhanced its dynamic adjustment and proactive recommendation mechanisms, capturing candidates' detailed needs and adding cutting-edge data on employment prospects, civil service exams, and trends in the AI era. In addition, the upgraded college entrance examination Q&A capabilities support precise score estimation across different years and introduce a self-check mechanism to prevent excessive deviation in the direction of volunteer choices.
Industry data shows that over ten million students take the national college entrance exam each year, but less than 5% of families can afford professional volunteer application advisors. Qwen has effectively broken down regional and economic barriers to high-quality educational consulting resources by building an Agent scheduling system centered around the volunteer large model and making special optimizations for older devices and weak network rural environments, in collaboration with the "Nuomang Public Welfare" initiative. This move not only demonstrates the technical maturity of AI Agents moving from conceptual technology to high-value inclusive scenarios, but also provides a typical model for large models empowering public social services.
