Source URL: https://www.theregister.com/2025/09/19/deepseek_cost_train/
Source: The Register
Title: Sorry, but DeepSeek didn’t really train its flagship model for $294,000
Feedly Summary: Training costs detailed in R1 training report don’t include 2.79 million GPU hours that laid its foundation
Chinese AI darling DeepSeek’s now infamous R1 research report was published in the Journal Nature this week, alongside new information on the compute resources required to train the model. Unfortunately, some people got the wrong idea about just how expensive it was to create.…
AI Summary and Description: Yes
Summary: The text discusses the training costs associated with DeepSeek’s R1 research report, highlighting the exclusion of substantial GPU hours from the reported expenses. This information is significant for professionals in AI and cloud computing, as it underscores the intricacies of computing resource allocation in AI model development.
Detailed Description: The analysis of the R1 training report from DeepSeek reveals critical insights into the costs and resources necessary for training AI models. Here are the main points:
– **Compute Resource Expenditure**: The report mentions 2.79 million GPU hours that were not included in the cost analysis, which raises concerns about the reported expenses appearing lower than they truly are.
– **Implications for AI Development**: Understanding the comprehensive costs associated with training AI models is crucial for organizations when budgeting and planning resources for AI projects.
– **Market Perception**: Misinterpretations regarding the training costs can affect market perceptions of AI capabilities and investments, influencing competition and funding dynamics within the AI sector.
– **Importance of Transparency**: This incident underscores the necessity for transparency in AI research, especially concerning resource allocation and training costs, to ensure stakeholders have accurate information on which to base decisions.
This case exemplifies the complexity of training AI models and the importance of thorough reporting on associated costs, which is particularly relevant to AI, cloud computing, and infrastructure security professionals involved in budgeting and resource management.