The Billion-Dollar Reality Behind DeepSeek's AI Training

DeepSeek has been in the news, and for good reason. The controversial claim that the Chinese startup used just $6 million within two months to build an AI model shocked developers across the globe.

DeepSeek, a Chinese startup, has been making headlines for its impressive feat in building a large AI model with a relatively small budget.

While initial reports claimed that the model cost just $6 million to train, new information suggests that the actual expenses are significantly higher.

David Sacks, White House AI and Crypto Czar, took to X to share an update with his 1.2 million followers.

In his post, Sacks highlighted a report by Dylan Patel, a semiconductor analyst at SemiAnalysis.

According to Patel's analysis, DeepSeek might have spent over $1 billion on its compute cluster, which is hundreds of millions more than the widely reported figure of $6 million.

Sacks further explained that the $6 million figure only pertains to the final training run and does not include critical aspects of DeepSeek's major expenditure.

Some notable expenses excluded from the reported amount are capital expenditure (the cost of buying and setting up the hardware for DeepSeek) and Research and Development (R&D) costs.

All expenses related to researching the AI model, developing it, and optimizing DeepSeek were not factored into the $6 million calculation.

Based on this information, Sacks implies that the cost of building DeepSeek's AI model falls within the billion-dollar range.

Moreover, he dismissed the $6 million reports as untrue and misleading, possibly intended to just score points.

Interestingly, SemiAnalysis provided a more detailed breakdown of DeepSeek's alleged misleading claims.

It insisted that the $6 million only accounts for the Graphics Processing Unit (GPU) pre-training.

It pegs the actual total infrastructure cost and R&D and server capital expenditure at around $1.3 billion.

Another notable claim it debunked relates to the chips. SemiAnalysis noted that while DeepSeek operates 50,000 Hopper GPUs, they are not all top-tier H100s.

Rather, it is a mix of H100s, H800s and H20s. The H20s are China's version due to the U.S export restriction.

However, SemiAnalysis also highlighted U.S. export restrictions as a potential hurdle to DeepSeek's expansion ambitions.

Despite the varying figures and differing opinions on the true cost of DeepSeek's AI model training, analysts believe that the development could have a significant impact on the crypto sector.

As it suggests more can be achieved for less, blockchains and different crypto projects will likely demand greater efficiency and value for money from developers.

This might lead to new upgrades in the crypto space that aim for scalability and efficiency.

Following the update, AI tokens went on a rebound streak. Internet Computer jumped 2.80% to $9.9336, Injective rallied 1.82% to $20.40, with Near Protocol jumping 2.2% to $4.616.