DeepSeek-R1 vs. ChatGPT: Assessing the Titans of Next-Generation AI Linguistic Models
DOI:
https://doi.org/10.63682/jns.v14i13S.4153Keywords:
Artificial intelligence, Large language models (LLMs), DeepSeek R1, ChatGPT, Natural language processing, Generative tasks, ArchitectureAbstract
Artificial intelligence models have rapidly evolved, leading to the development of advanced large language models (LLMs) like DeepSeek R1 and ChatGPT. These models represent significant advancements in natural language processing and generative tasks, each offering unique features and capabilities. This study provides a comprehensive comparison of the two, focusing on their architectures, functionalities, and applications across various domains. It highlights the strengths of DeepSeek R1, such as its versatility in handling multiple types of content, and contrasts them with ChatGPT’s conversational and interactive abilities. The analysis also addresses the limitations of both models, including computational requirements and customization challenges. Differentiation tables, flowcharts, and graphical representations are used to visually depict the key distinctions, offering a clearer understanding of their respective advantages and drawbacks. This comparison aims to guide users in choosing the most suitable model based on specific needs, technical expertise, and available resources. By offering a detailed overview of these models, the paper provides insights into how each can be leveraged in real-world applications, ensuring that users can make informed decisions that best align with their goals and requirements.
Downloads
Metrics
References
Biswas, Som S. "Role of chat gpt in public health." Annals of biomedical engineering 51.5 (2023): 868-869.
Biswas, Som S. "Potential use of chat gpt in global warming." Annals of biomedical engineering 51.6 (2023): 1126-1127.
Meyer, Jesse G., et al. "ChatGPT and large language models in academia: opportunities and challenges." BioData mining 16.1 (2023): 20.
Zhou, Ce, et al. "A comprehensive survey on pretrained foundation models: A history from bert to chatgpt." International Journal of Machine Learning and Cybernetics (2024): 1-65.
Briganti, Giovanni. "How ChatGPT works: a mini review." European Archives of Oto-Rhino-Laryngology 281.3 (2024): 1565-1569.
Ariyaratne, Sisith, et al. "A comparison of ChatGPT-generated articles with human-written articles." Skeletal radiology 52.9 (2023): 1755-1758.
Teubner, Timm, et al. "Welcome to the era of chatgpt et al. the prospects of large language models." Business & Information Systems Engineering 65.2 (2023): 95-101.
Kim, Seong-Gon. "Using ChatGPT for language editing in scientific articles." Maxillofacial plastic and reconstructive surgery 45.1 (2023): 13.
Dahmen, Jari, et al. "Artificial intelligence bot ChatGPT in medical research: the potential game changer as a double-edged sword." Knee Surgery, Sports Traumatology, Arthroscopy 31.4 (2023): 1187-1189.
Tlili, Ahmed, et al. "What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education." Smart learning environments 10.1 (2023): 15.
Carlbring, Per, et al. "A new era in Internet interventions: The advent of Chat-GPT and AI-assisted therapist guidance." Internet Interventions 32 (2023): 100621.
Shidiq, Muhammad. "The use of artificial intelligence-based chat-gpt and its challenges for the world of education; from the viewpoint of the development of creative writing skills." Proceeding of international conference on education, society and humanity. Vol. 1. No. 1. 2023.
Ausat, Abu Muna Almaududi, et al. "Can chat GPT replace the role of the teacher in the classroom: A fundamental analysis." Journal on Education 5.4 (2023): 16100-16106.
Ajmani, Prerna, et al. "Impact of AI in Financial Technology-A Comprehensive Study and Analysis." 2023 6th International Conference on Contemporary Computing and Informatics (IC3I). Vol. 6. IEEE, 2023.
Biswas, Som. "The Function of chat GPT in Social Media: According to chat GPT." Available at SSRN 4405389 (2023).
Castillo-González, William, Carlos Oscar Lepez, and Mabel Cecilia Bonardi. "Chat GPT: a promising tool for academic editing." Data and Metadata 1 (2022): 23-23.
Kalla, Dinesh, et al. "Study and analysis of chat GPT and its impact on different fields of study." International journal of innovative science and research technology 8.3 (2023).
Božić, Velibor, and Indrasen Poola. "Chat GPT and education." Preprint 10 (2023).
Arrieta, Aitor, et al. "o3-mini vs DeepSeek-R1: Which One is Safer?." arXiv preprint arXiv:2501.18438 (2025).
Krause, David. "DeepSeek and FinTech: The Democratization of AI and Its Global Implications." Available at SSRN 5116322 (2025).
Mondillo, Gianluca, et al. "Comparative Evaluation of Advanced AI Reasoning Models in Pediatric Clinical Decision Support: ChatGPT O1 vs. DeepSeek-R1." medRxiv (2025): 2025-01.
Parmar, Manojkumar, and Yuvaraj Govindarajulu. "Challenges in Ensuring AI Safety in DeepSeek-R1 Models: The Shortcomings of Reinforcement Learning Strategies." arXiv preprint arXiv:2501.17030 (2025).
Zhou, Jie, et al. "ChatGPT: potential, prospects, and limitations." Frontiers of Information Technology & Electronic Engineering (2023): 1-6.
George, A. Shaji, and AS Hovan George. "A review of ChatGPT AI's impact on several business sectors." Partners universal international innovation journal 1.1 (2023): 9-23.
Saini, Lalit Mohan, et al. "KubeEdge for Scalable IoT Applications." 2024 7th International Conference on Contemporary Computing and Informatics (IC3I). Vol. 7. IEEE, 2024.
Williams, Andy E. "Has OpenAI achieved artificial general intelligence in ChatGPT." Artificial Intelligence and Applications, February (2023): 1-15.
Krause, David. "DeepSeek’s Potential Impact on the Magnificent 7: A Valuation Perspective."
Haque, Md Asraful. "A Brief analysis of “ChatGPT”–A revolutionary tool designed by OpenAI." EAI endorsed transactions on AI and robotics 1 (2022): e15-e15.
Kirtania, Deep Kumar. "OpenAI ChatGPT for library and information science (LIS) professionals." Available at SSRN 4404903 (2023).
Ajmani, Prerna, et al. "Machine learning and deep learning techniques for breast cancer detection using ultrasound imaging." Computational Intelligence and Modelling Techniques for Disease Detection in Mammogram Images. Academic Press, 2024. 235-257.
Aydin, Omer, and Enis Karaarslan. "OpenAI ChatGPT interprets radiological images: GPT-4 as a medical doctor for a fast check-up." arXiv preprint arXiv:2501.06269 (2025).
Naz, Irum, and Rodney Robertson. "Exploring the Feasibility and Efficacy of ChatGPT3 for Personalized Feedback in Teaching." Electronic Journal of e-Learning 22.2 (2024): 98-111.
Guo, Daya, et al. "Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning." arXiv preprint arXiv:2501.12948 (2025).
Adeshola, Ibrahim, and Adeola Praise Adepoju. "The opportunities and challenges of ChatGPT in education." Interactive Learning Environments 32.10 (2024): 6159-6172.
Ahsan, M. M., Md Saidur Rahaman, and Nishath Anjum. "From ChatGPT-3 to GPT-4: A Significant Leap in AI-Driven NLP Tools." Saidur and Anjum, Nishath, From ChatGPT-3 to GPT-4: A Significant Leap in AI-Driven NLP Tools (March 27, 2023) (2023).
Sharma, Vandana, Prerna Ajmani, and Celestine Iwendi. "Blockchain Application with Specific Reference to Smart Contracts in the Insurance Sector." The Application of Emerging Technology and Blockchain in the Insurance Industry. River Publishers, 2024. 179-208.
Rane, Nitin, Saurabh Choudhary, and Jayesh Rane. "Gemini versus ChatGPT: applications, performance, architecture, capabilities, and implementation." Performance, Architecture, Capabilities, and Implementation (February 13, 2024) (2024).
Jain, D. ., Hundekari, S. ., Upreti, K. ., Jain, N. ., Rose, M. ., Singh, N. ., Singhai, R. ., & Kumar, M. . (2024). RCBAM-CNN: Rebuild Convolution Block Attention Module-based Convolutional Neural Network for Lung Nodule Classification. Journal of Mobile Multimedia, 20(05), 1039–1066. https://doi.org/10.13052/jmm1550-4646.2053
Jain, D.; Pandey, A.K.; Chauhan, A.S.; Kushwah, J.S.; Saxena, N.; Sharma, R.; Sambrow, V.D.P. ASA-LSTM-based brain tumor segmentation and classification in MRI images. Int. J. Adv. Technol. Eng. Explor. 2024, 11, 838–851.
H. Malhotra, K. Arora, K. Gogia, P. Raj, D. Jain and P. Singh, "Machine Learning for Diabetes, Heart Disease, Pneumonia, and Covid-19 Diagnostics," 2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N), Greater Noida, India, 2022, pp. 265-270, doi: 10.1109/ICAC3N56670.2022.10074463.
D. Jain, P. Singh, V. Rohatgi, R. Raj, A. Sharma and S. Bansal, "Pneumonia Detection using Customized CNN," 2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N), Greater Noida, India, 2022, pp. 261-264, doi: 10.1109/ICAC3N56670.2022.10074473.
S. Mahajan, L. Kriplani, V. K. Dhanraj, D. Jain and P. Singh, "Lane Line Detection for Self Driving Cars," 2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N), Greater Noida, India, 2022, pp. 311-316, doi: 10.1109/ICAC3N56670.2022.10074429.
Sharma, Chavikant, T. Singh, T. Aggarwal, D. Jain and P. Singh, "Blockchain based E-Voting," 2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N), Greater Noida, India, 2022, pp. 2054-2058, doi: 10.1109/ICAC3N56670.2022.10074034.
D. Jain, P. Singh, A. K. Pandey, M. Singh, H. Singh and A. Singh, "Lung Cancer Detection Using Convolutional Neural Network," 2022 3rd International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT), Ghaziabad, India, 2022, pp. 1-4, doi: 10.1109/ICICT55121.2022.10064513.
S. Ghulyani, D. Jain, P. Singh, S. Joshi and A. Ahlawat, "A Data Entry Optical Character Recognition Tool using Convolutional Neural Networks," 2022 IEEE IAS Global Conference on Emerging Technologies (GlobConET), Arad, Romania, 2022, pp. 721-728, doi: 10.1109/GlobConET53749.2022.9872395.
K. Kaul, P. Singh, D. Jain, P. Johri and A. K. Pandey, "Monitoring and Controlling of Energy Consumption using IOT-based Predictive Maintenance," 2021 10th International Conference on System Modeling & Advancement in Research Trends (SMART), MORADABAD, India, 2021, pp. 587-594, doi: 10.1109/SMART52563.2021.9676268.
Kshirsagar, P.R., Upreti, K., Kushwah, V.S. et al. Prediction and modeling of mechanical properties of concrete modified with ceramic waste using artificial neural network and regression model. SIViP 18 (Suppl 1), 183–197 (2024). https://doi.org/10.1007/s11760-024-03142-z
Pandey, A.K.; Singh, P.; Jain, D.; Sharma, A.K.; Jain, A.; Gupta, A. Generative Adversarial Network and Bayesian Optimization in Multi-class Support Vector Machine for Intrusion Detection System. Int. J. Intell. Eng. Syst. 2023, 16, 110–119.
Amit Kumar Pandey, Dhyanendra Jain, Tarun Kumar Gautam, Jitendra Singh Kushwah, Saurabh Shrivastava, Rajeev Sharma, and Prashant Vats, "Tomato Leaf Disease Detection using Generative Adversarial Network-based ResNet50V2," Engineering Letters, vol. 32, no. 5, pp. 965-973, 2024.
Upreti, K., Singh, P., Jain, D. et al. Progressive loss-aware fine-tuning stepwise learning with GAN augmentation for rice plant disease detection. Multimed Tools Appl 83, 84565–84588 (2024). https://doi.org/10.1007/s11042-024-19255-z
Upreti, K., Kushwah, V. S., Vats, P., Alam, M. S., Singhai, R., Jain, D., & Tiwari, A. (2024). A SWOT analysis of integrating cognitive and non-cognitive learning strategies in education. European Journal of Education, 59, e12614. https://doi.org/10.1111/ejed.12614
V. Bhadra Pratap Singh, P. Singh, D. Jain, A. K. Pandey and S. Das, "Hierarchical Cluster Analysis Implementation Using the Algorithm of Clustering Using Representatives," 2022 IEEE IAS Global Conference on Emerging Technologies (GlobConET), Arad, Romania, 2022, pp. 993-998, doi: 10.1109/GlobConET53749.2022.9872414.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
Terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
