An Empirical Comparative Analysis of ChatGPT and DeepSeek in NLP: Text Generation, Summarization, Translation, and User Feedback Evaluation

Authors

  • Aisha Hamed Bubaker Computer Science Department, Faculty of Education - Qmens, University of Benghazi, Benghazi, Libya
  • Nadia Mohammed Senussi Computer Science Department, Faculty of Education - Qmens, University of Benghazi, Benghazi, Libya

Keywords:

Generative AI, DeepSeek-V3, ChatGPT, Educational Applications, AI Tools in Education, (Natural Language Processing) NLP

Abstract

                Understanding the capabilities of AI tools is incredibly important, especially as they become more integrated into our daily lives. This study examines two AI tools: ChatGPT and DeepSeek-V3. This research aims to conduct a comprehensive comparison between the two tools in terms of performance, flexibility. In this paper we evaluate the capabilities of each tool in natural language processing. Data was collected by performing the same activities with each tool, and the accuracy and quality of the outcomes were recorded. Additionally, each tool's adaptability to various criteria was tested. The findings demonstrated ChatGPT's strong performance in general tasks and  natural language processing, as well as its user-friendliness and high degree of adaptability to a wide range  of needs. On the other hand, DeepSeek-V3 demonstrated outstanding performance in specialized tasks, producing precise and effective results in particular domains such as translation.

Dimensions

Published

2026-06-04

How to Cite

Aisha Hamed Bubaker, & Nadia Mohammed Senussi. (2026). An Empirical Comparative Analysis of ChatGPT and DeepSeek in NLP: Text Generation, Summarization, Translation, and User Feedback Evaluation. African Journal of Advanced Pure and Applied Sciences, 5(2), 217–225. Retrieved from https://aaasjournals.com/index.php/ajapas/article/view/2009

Issue

Section

Articles