Chinese startup DeepSeek recently took center stage in the tech world with its startlingly low usage of compute resources for its advanced AI model called R1, a model that is believed to be competitive with Open AI's o1 despite the company's claims that DeepSeek only cost $6 million and 2,048 GPUs to train. However, industry analyst firm SemiAnalysis reports that the company behind DeepSeek incurred $1.6 billion in hardware costs and has a fleet of 50,000 Nvidia Hopper GPUs, a finding that undermines the idea that DeepSeek reinvented AI training and inference with dramatically lower investments than the leaders of the AI industry.
DeepSeek operates an extensive computing infrastructure with approximately 50,000 Hopper GPUs, the report claims. This includes 10,000 H800s and 10,000 H100s, with additional purchases of H20 units, according to SemiAnalysis. These resources are distributed across multiple locations and serve purposes such as AI training, research, and financial modeling. The company's total capital investment in servers is around $1.6 billion, with an estimated $944 million spent on operating costs, according to SemiAnalysis.
