Generative AI in Academic Writing: A Comparison of DeepSeek, Qwen, ChatGPT, Gemini, Llama, Mistral, and Gemma

Ömer Aydın; Enis Karaarslan; Fatih Safa Erenay; Nebojsa Bacanin

doi:10.31127/tuje.1838765

Generative AI in Academic Writing: A Comparison of DeepSeek, Qwen, ChatGPT, Gemini, Llama, Mistral, and Gemma

Abstract

DeepSeek v3, developed in China, was released in December 2024, followed by Alibaba’s Qwen 2.5 Max in January 2025 and Qwen3 235B in April 2025. These free and open-source models offer significant potential for academic writing and content creation. This study evaluates their academic writing performance by comparing them with ChatGPT, Gemini, Llama, Mistral, and Gemma. There is a critical gap in the literature concerning how extensively these tools can be utilized and their potential to generate original content in terms of quality, readability, and effectiveness. Using 40 papers on Digital Twin and Healthcare, texts were generated through AI tools based on posed questions and paraphrased abstracts. The generated content was analyzed using similarity detection, AI detection, word count comparisons, semantic similarity, and readability assessments. Results indicate that paraphrased abstracts showed higher similarity rates, while question-based responses also exceeded acceptable levels. AI detection tools consistently identified all outputs as AI-generated. Word count analysis revealed that all chatbots produced a sufficient volume of content. Semantic similarity tests showed a strong overlap between generated and original texts. However, readability assessments indicated that the texts were insufficient in terms of clarity and accessibility. This study comparatively highlights the potential and limitations of popular and latest large language models for academic writing. While these models generate substantial and semantically accurate content, concerns regarding plagiarism, AI detection, and readability must be addressed for their effective use in scholarly work.

Keywords

Supporting Institution

Assoc. Prof. Dr. Omer Aydin was funded by the Scientific and Technological Research Council of Türkiye (TUBITAK) under the 2219 International Postdoctoral Research Fellowship Program for Turkish Citizens.

Project Number

1059B192302744

Ethical Statement

The authors affirm our commitment to upholding ethical standards in academic research and publishing.

Thanks

Assoc. Prof. Dr. Omer Aydin was supported by the Scientific and Technological Research Council of Türkiye (TUBITAK) under the 2219 International Postdoctoral Research Fellowship Program for Turkish Citizens under the supervision of Assoc. Prof. Dr. Fatih Safa Erenay at the University of Waterloo Department of Management Science and Engineering. The authors thank to Scientific and Technological Research Council of Türkiye (TUBITAK) and the University of Waterloo.

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Details

Primary Language

English

Subjects

Management Information Systems, Computer Software

Journal Section

Research Article

Authors

Ömer Aydın ^*
0000-0002-7137-4881
Türkiye

Enis Karaarslan
0000-0002-3595-8783
Türkiye

Fatih Safa Erenay
0000-0002-3408-0366
Canada

Nebojsa Bacanin
0000-0002-2062-924X
Serbia

Publication Date

May 1, 2026

Submission Date

December 9, 2025

Acceptance Date

February 1, 2026

Published in Issue

Year 2026 Volume: 10 Number: 2

DOI

https://doi.org/10.31127/tuje.1838765

IZ

https://izlik.org/JA45ZG84ZN

Cite

RIS / Bibtex

APA

Aydın, Ö., Karaarslan, E., Erenay, F. S., & Bacanin, N. (2026). Generative AI in Academic Writing: A Comparison of DeepSeek, Qwen, ChatGPT, Gemini, Llama, Mistral, and Gemma. Turkish Journal of Engineering, 10(2), 592-607. https://doi.org/10.31127/tuje.1838765

AMA

1.Aydın Ö, Karaarslan E, Erenay FS, Bacanin N. Generative AI in Academic Writing: A Comparison of DeepSeek, Qwen, ChatGPT, Gemini, Llama, Mistral, and Gemma. TUJE. 2026;10(2):592-607. doi:10.31127/tuje.1838765

Chicago

Aydın, Ömer, Enis Karaarslan, Fatih Safa Erenay, and Nebojsa Bacanin. 2026. “Generative AI in Academic Writing: A Comparison of DeepSeek, Qwen, ChatGPT, Gemini, Llama, Mistral, and Gemma”. Turkish Journal of Engineering 10 (2): 592-607. https://doi.org/10.31127/tuje.1838765.

EndNote

Aydın Ö, Karaarslan E, Erenay FS, Bacanin N (May 1, 2026) Generative AI in Academic Writing: A Comparison of DeepSeek, Qwen, ChatGPT, Gemini, Llama, Mistral, and Gemma. Turkish Journal of Engineering 10 2 592–607.

IEEE

[1]Ö. Aydın, E. Karaarslan, F. S. Erenay, and N. Bacanin, “Generative AI in Academic Writing: A Comparison of DeepSeek, Qwen, ChatGPT, Gemini, Llama, Mistral, and Gemma”, TUJE, vol. 10, no. 2, pp. 592–607, May 2026, doi: 10.31127/tuje.1838765.

ISNAD

Aydın, Ömer - Karaarslan, Enis - Erenay, Fatih Safa - Bacanin, Nebojsa. “Generative AI in Academic Writing: A Comparison of DeepSeek, Qwen, ChatGPT, Gemini, Llama, Mistral, and Gemma”. Turkish Journal of Engineering 10/2 (May 1, 2026): 592-607. https://doi.org/10.31127/tuje.1838765.

JAMA

1.Aydın Ö, Karaarslan E, Erenay FS, Bacanin N. Generative AI in Academic Writing: A Comparison of DeepSeek, Qwen, ChatGPT, Gemini, Llama, Mistral, and Gemma. TUJE. 2026;10:592–607.

MLA

Aydın, Ömer, et al. “Generative AI in Academic Writing: A Comparison of DeepSeek, Qwen, ChatGPT, Gemini, Llama, Mistral, and Gemma”. Turkish Journal of Engineering, vol. 10, no. 2, May 2026, pp. 592-07, doi:10.31127/tuje.1838765.

Vancouver

1.Ömer Aydın, Enis Karaarslan, Fatih Safa Erenay, Nebojsa Bacanin. Generative AI in Academic Writing: A Comparison of DeepSeek, Qwen, ChatGPT, Gemini, Llama, Mistral, and Gemma. TUJE. 2026 May 1;10(2):592-607. doi:10.31127/tuje.1838765