Autors: Sharabov, M. Z., Georgieva P., Tsochev, G. R., Trifonov R.
Title: Comparative Analysis of Large Language Models: Case Study of GPT, Gemini, DeepSeek
Keywords: AI Benchmarking, Artificial Intelligence, ChatGPT, Code Generation, DeepSeek-R1, Gemini 2.0 Pro, Large Language Models (LLMs), Model Comparison, Natural Language Processing, Transformer

Abstract: This article gives a comparative overview of three of the top large language models (LLMs) in February 2025: Gemini 2.0 Pro (Google), DeepSeek-R1 (DeepSeek AI), and ChatGPT (OpenAI). The article begins with summarizing the general working patterns of LLMs, i.e., the transformer architecture on which they are developed. The architecture, features, performance parameters, and usage for each model are described. A battery of tests drawn from standardized benchmarks such as MMLU-Pro, LiveCodeBench, and MATH-500 are used to assess their performance in areas such as reason, code generation, and response time.

References

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Issue

2025 13th International Scientific Conference on Computer Science, COMSCI 2025 - Proceedings, 2025, Albania, https://doi.org/10.1109/COMSCI67172.2025.11225122

Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus