A Technical Review of DeepSeek AI: Capabilities and Comparisons with Insights from Q1 2025

Abstract

This paper provides a review of DeepSeek AI, a rapidly emerging artificial intelligence model that has garnered significant attention for its capabilities and cost-effectiveness. We examine its features, compare it with other leading AI models like ChatGPT and Gemini, and discuss its potential implications across various sectors. We examine DeepSeek's technical architecture, performance benchmarks, and business applications. Key findings indicate that DeepSeek's V3-0324 model demonstrates particularly strong performance in programming tasks while operating at significantly lower training costs ($6M vs. $100M+ for comparable models). The open-source nature of DeepSeek's models has accelerated adoption but also raised security concerns. This paper provides valuable insights for AI researchers, business leaders, and policymakers evaluating the evolving competitive landscape of large language models. The paper further explores DeepSeek’s rapid adoption in finance, insurance, and marketing, where it delivers measurable efficiency gains (e.g., 30\% faster underwriting, 40\% reduction in compliance review time). However, its open-source strategy, while accelerating accessibility, raises sustainability and security concerns, including geopolitical tensions and data privacy risks. Comparative analyses reveal trade-offs: DeepSeek excels in energy efficiency (40\% lower consumption than GPT-4) but lags in creative tasks and multimodal capabilities.

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