AI Development and Innovation: A Comparison of Large Language Models from the U.S. and China

The strategic significance of Large Language Models (LLMs) in economic expansion, innovation, societal development, and national security has been increasingly recognized since the advent of ChatGPT. This study provides a comprehensive comparative evaluation of LLMs developed in the U.S. and China, in both English and Chinese contexts. We proposed an evaluation framework that encompasses natural language proficiency, disciplinary expertise, and safety and responsibility, and systematically assessed notable models from the U.S. and China under various operational tasks and scenarios. Our key findings show that GPT-4 Turbo leads in English contexts, whereas the Chinese LLM Ernie-Bot 4 stands out in Chinese contexts. The study also highlights disparities in LLM performance across languages and tasks, stressing the necessity for linguistically and culturally nuanced model development. The complementary strengths of LLMs developed in the U.S. and China highlight the cross-national collaboration value in advancing LLM technology. The research delineates the current LLM competition landscape and offers valuable insights for policymakers and businesses regarding strategic LLM investments and development.

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Publication Details

Journal
ACM Transactions on Management Information Systems
Published
2025-09-23
DOI
https://doi.org/10.1145/3769086
Primary Topic
Topic Modeling
Type
article
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article

AI Development and Innovation: A Comparison of Large Language Models from the U.S. and China

Yang Liu, Zhenhui Jiang, Jiaxin Li
ACM Transactions on Management Information Systems
Topic Modeling
article

AI Development and Innovation: A Comparison of Large Language Models from the U.S. and China

Yang Liu, Zhenhui Jiang, Jiaxin Li
article en

Abstract

The strategic significance of Large Language Models (LLMs) in economic expansion, innovation, societal development, and national security has been increasingly recognized since the advent of ChatGPT. This study provides a comprehensive comparative evaluation of LLMs developed in the U.S. and China, in both English and Chinese contexts. We proposed an evaluation framework that encompasses natural language proficiency, disciplinary expertise, and safety and responsibility, and systematically assessed notable models from the U.S. and China under various operational tasks and scenarios. Our key findings show that GPT-4 Turbo leads in English contexts, whereas the Chinese LLM Ernie-Bot 4 stands out in Chinese contexts. The study also highlights disparities in LLM performance across languages and tasks, stressing the necessity for linguistically and culturally nuanced model development. The complementary strengths of LLMs developed in the U.S. and China highlight the cross-national collaboration value in advancing LLM technology. The research delineates the current LLM competition landscape and offers valuable insights for policymakers and businesses regarding strategic LLM investments and development.

ACM Transactions on Management Information SystemsVol. 16(4)
Xi'an Jiaotong University (CN), University of Hong Kong (HK)
Openalex Percentile: Top 86%
Topic Modeling
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AI Development and Innovation: A Comparison of Large Language Models from the U.S. and China — Yang Liu, Zhenhui Jiang, et al. · ACM Transactions on Management Information Systems (2025) | TGRS Research Map | TGRS