BEIJING, March 1 (Reuters) - Chinese AI startup

DeepSeek on Saturday disclosed some cost and revenue data

related to its hit V3 and R1 models, claiming a theoretical

cost-profit ratio of up to 545% per day, though it cautioned

that actual revenue would be significantly lower.

This marks the first time the Hangzhou-based company has

revealed any information about its profit margins from less

computationally intensive "inference" tasks, the stage after

training that involves trained AI models making predictions or

performing tasks, such as through chatbots.

The revelation could further rattle AI stocks outside China

that plunged in January after web and app chatbots powered by

its R1 and V3 models surged in popularity worldwide.

The sell-off was partly caused by DeepSeek's claims that it

spent less than $6 million on chips used to train the model,

much less than what U.S. rivals like OpenAI have spent.

The chips DeepSeek claims it used, Nvidia's ( NVDA ) H800, are also

much less powerful than what OpenAI and other U.S. AI firms have

access to, making investors question even further U.S. AI firms'

pledges to spend billions of dollars on cutting-edge chips.

DeepSeek said in a GitHub post published on Saturday that

assuming 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 contrast, 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, the firm added that its "actual revenue is

substantially lower" because the cost of using its V3 model is

lower than the R1 model, only some services are monetized as web

and app access remain free, and developers pay less during

off-peak hours.