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Released under the MIT License, DeepSeek-R1 provides responses comparable to other contemporary large language models, such as OpenAI's GPT-4o and o1.[10] Its training cost is reported to be significantly lower than other LLMs. The company claims that it trained its V3 model for US$6 million compared to $100 million for OpenAI's GPT-4 in 2023,[11] and approximately one-tenth of the computing power used for Meta's comparable model, Llama 3.1.[11][12][13][14] DeepSeek's success against larger and more established rivals has been described as "upending AI".[15][16]
DeepSeek's models are "open weight", which provides less freedom for modification than true open-source software.[17][18] The company reportedly recruits AI researchers from top Chinese universities[15] and hires from outside the computer science field to diversify its models' knowledge and abilities.[12]
The DeepSeek R1 model was trained at a significantly lower cost than other models by using techniques such as mixture of experts to reduce costs.[19] The model was also trained during ongoing trade restrictions on AI chip exports to China, causing it to be trained on weaker AI chips made for export to China,[13] and using fewer chips compared to other models.[15] This breakthrough in reducing expenses, although increasing efficiency and maintaining the model's performance power and quality in the AI industry, sent "shockwaves" through the market. It threatened the dominance of AI leaders like Nvidia and contributed to the largest drop for a single company in US stock market history, as Nvidia lost $600 billion in market valueMore Related Content
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