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We recently compiled a list of the 10 AI Stocks to Watch Now. In this article, we are going to take a look at where NVIDIA Corporation (NASDAQ:NVDA) stands against the other AI stocks.
The tech world was already spooked when it got to know AI models could be developed more cheaply and efficiently. However, the landscape is shifting even further now that DeepSeek has revealed some cost and revenue data related to its V3 and R1 models.
Its potential for massive profit margins — up to 545% in ideal conditions — highlights just how effective AI models can be. The new information from DeepSeek reveals the profit margins from less computationally intensive "inference" tasks. This is the stage after training that involves trained AI models making predictions or performing tasks, such as through chatbots.
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In a GitHub post published on Saturday, DeepSeek revealed that if we assume that the cost of renting one H800 chip is $2 per hour, the total daily inference cost for its V3 and R1 models is $87,072.
In comparison, the theoretical daily revenue generated by these models is $562,027, leading to a cost-profit ratio of 545%. In a year, this would add up to just over $200 million in revenue.
However, DeepSeek has cautioned that its "actual revenue is substantially lower" because the cost of using its V3 model is lower than the R1 model. Moreover, only some services are monetized as web and app access is free and developers pay less during off-peak hours.
DeepSeek’s AI models are notably a product of what is known as “distillation”. Distillation, now a buzz word in the tech world, is a technique used to make cheaper and more efficient AI models. This process involves taking a large AI model, called the ‘teacher,’ and allowing it to train a smaller, more efficient ‘student’ model.
Eventually, this helps companies transfer knowledge from big AI systems into smaller, faster, and cheaper versions. Companies such as OpenAI, Microsoft, and even Meta are joining in on the bandwagon to develop such models. Thanks to this model, AI models can be made cheaply and efficiently, allowing businesses to save money while keeping their AI performances high.
For this article, we selected AI stocks by going through news articles, stock analysis, and press releases. These stocks are also popular among hedge funds. The hedge fund data is as of Q4 2024.
Why are we interested in the stocks that hedge funds pile into? The reason is simple: our research has shown that we can outperform the market by imitating the top stock picks of the best hedge funds. Our quarterly newsletter’s strategy selects 14 small-cap and large-cap stocks every quarter and has returned 373.4% since May 2014, beating its benchmark by 218 percentage points (see more details here).