The DeepSeek controversy continues to unfold, revealing new details about the training costs of their R1 model. According to a recent report by SemiAnalysis, the company's actual costs were 400 times higher than its stated $5 million. This new data significantly changes the perception of DeepSeek's financial model.
Earlier this year, the reported costs of $5 million shocked the market and caused panic among investors, affecting the stock quotes of Nvidia and other manufacturers of chips for artificial intelligence. However, according to SemiAnalysis, DeepSeek's real costs are about $1.6 billion in capital expenditures (CapEx) and $944 million in operating expenses. These figures indicate a significant investment that was previously hidden.
DeepSeek began as a project of Chinese hedge fund High-Flyer. In 2021, before the introduction of export restrictions, the company purchased 10,000 A100 GPUs from NVIDIA. After the project became a separate entity, it gained access to 10,000 specialized H800 GPUs and 10,000 H100 chips from NVIDIA, and also actively uses AI H20 accelerators.
The $5 million figure only covered part of the costs associated with launching the final model. All other costs were ignored, creating the illusion of efficiency. However, DeepSeek has indeed achieved significant success thanks to its team, which developed an effective solution to compete with OpenAI.
Recent events have become a catalyst for understanding the difference between the declared and real costs. It is now clear that DeepSeek used a strategy of information manipulation to appear as a cost-effective alternative to other players. This tactic, although it worked temporarily, may affect the credibility of the company in the future.
SemiAnalysis also conducted detailed testing of the DeepSeek model, revealing its capabilities and limitations. The report shows significant improvements in the effectiveness of the models, but the company's financial policy remains a subject of controversy.
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