DeepSeek is a Chinese artificial intelligence company specializing in the development of large language models (LLMs) and advanced AI-powered information retrieval and reasoning platforms. Founded in 2023 by Liang Wenfeng, a graduate of Zhejiang University and co-founder of the quantitative hedge fund High-Flyer, DeepSeek is headquartered in Hangzhou, Zhejiang.
The company made global headlines in early 2025 with the release of its DeepSeek-R1 model, a highly efficient and powerful LLM focused on logical inference, mathematical reasoning, and real-time problem-solving. DeepSeek-R1, along with other models like DeepSeek-V3, was developed at a fraction of the cost and computational resources required by leading U.S. and European AI firms. For example, DeepSeek-V3 was trained for about $5.58 million—far less than the reported $100 million cost for OpenAI’s GPT-4—and uses significantly fewer computing resources than comparable models like Meta’s Llama 3.1.
DeepSeek’s models are notable for their open-source or “open weight” approach, meaning the company shares model parameters and methods publicly, though with some usage conditions that differ from typical open-source software. This transparency, combined with competitive performance, has positioned DeepSeek as a major disruptor in the AI industry, challenging established players like OpenAI, Google, and Meta.
Key features of DeepSeek include:
• Advanced Reasoning and Search: DeepSeek combines generative AI with sophisticated reasoning and real-time, multi-source search capabilities, providing contextually rich and transparent responses.
• Open-Source Models: DeepSeek’s models, such as R1 and V3, are available for free use, research, and commercial applications under open-source licenses.
• Efficiency and Cost-Effectiveness: The company leverages algorithmic innovations (like mixture of experts and multi-head latent attention transformers) to achieve high performance with lower resource consumption.
• Global Impact: DeepSeek’s rapid adoption and competitive capabilities have led to significant market reactions, including a notable drop in the stock prices of major U.S. tech companies.