On DeepSeek and Export Controls

DeepSeek does not "do for $6M5 what cost US AI companies billions". I can only speak for Anthropic, but Claude 3.5 Sonnet is a mid-sized model that cost a few $10M's to train (I won't give an exact number). Also, 3.5 Sonnet was not trained in any way that involved a larger or more expensive model (contrary to some rumors). Sonnet's training was conducted 9-12 months ago, and DeepSeek's model was trained in November/December, while Sonnet remains notably ahead in many internal and external evals. Thus, I think a fair statement is "DeepSeek produced a model close to the performance of US models 7-10 months older, for a good deal less cost (but not anywhere near the ratios people have suggested)".

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Publication Details

Journal
SuperIntelligence - Robotics - Safety & Alignment
Published
2025-03-05
DOI
https://doi.org/10.70777/si.v2i1.10695
Citations
4
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
16.68
Controls
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article

On DeepSeek and Export Controls

Dario Amodei
4 citations
SuperIntelligence - Robotics - Safety & Alignment
Scientific Computing and Data Management
16.68
article

On DeepSeek and Export Controls

Dario Amodei
article en
4 citations

Abstract

DeepSeek does not "do for $6M5 what cost US AI companies billions". I can only speak for Anthropic, but Claude 3.5 Sonnet is a mid-sized model that cost a few $10M's to train (I won't give an exact number). Also, 3.5 Sonnet was not trained in any way that involved a larger or more expensive model (contrary to some rumors). Sonnet's training was conducted 9-12 months ago, and DeepSeek's model was trained in November/December, while Sonnet remains notably ahead in many internal and external evals. Thus, I think a fair statement is "DeepSeek produced a model close to the performance of US models 7-10 months older, for a good deal less cost (but not anywhere near the ratios people have suggested)".

SuperIntelligence - Robotics - Safety & AlignmentVol. 2(1)
Openalex Percentile: Top 2%
Scientific Computing and Data Management
16.68
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