Expert Q&A: China's new DeepSeek AI model

Meet the experts

Professor Harin Sellahewa, Professor of Computing and Dean of Faculty of Computing, Law and Psychology, University of Buckingham

Prof Anthony G Cohn, FREng, FLSW, Professor of Automated Reasoning, University of Leeds, and Foundation Models Lead at the Alan Turing Institute

Dr Lukasz Piwek, Senior Lecturer in Data Science and member of the University's Institute for Digital Security and Behaviour, University of Bath

Q: How does DeepSeek R1 differ from other models?

LP: DeepSeek R1 distinguishes itself by merging chain‐of‐thought reasoning with a highly cost‐efficient, open‐source architecture. It attains performance levels comparable to top models like OpenAI’s o1 and GPT-4o. For example, its score of approximately 90.8% on the MMLU (Massive Multitask Language Understanding) benchmark - an assessment spanning diverse academic and professional tasks - places it among leading systems, yet it’s trained for only about US$5.6 million, roughly 5–6% of competitors’ costs. R1 also utilises computational innovations such as mixture-of-experts (MoE) and multi-head latent attention (MLA) to reduce memory overhead and boost efficiency. Most impressively, it has been released as open-source under the MIT License with full code and detailed documentation—making it one of the only models of this power level to be released so openly besides Meta's products like LLaMA.