According to Tesla CEO Elon Musk, the company expects to source $3 billion to $4 billion worth of products from Nvidia this year.
Musk also revealed that about half of Tesla’s $10 billion in capital spending on artificial intelligence (AI) this year will be spent internally.
“To build the AI training super cluster, Nvidia’s hardware accounts for roughly two-thirds of the cost,” he said at X.
Earlier this year, Musk announced on Tesla’s earnings call that the company plans to increase purchases of Nvidia’s H100 AI chips from 35,000 to 85,000 by the end of the year. He also revealed that Tesla intends to invest $10 billion in joint training and reasoning AI, primarily for in-car applications.
But earlier Tuesday, it was reported that Musk had prioritized the delivery of thousands of artificial intelligence chips originally intended for Tesla to his social media company X. The chips are designed to help Tesla develop into a leader in artificial intelligence and robotics.
That would delay the delivery of more than $500 million worth of chips by several months, potentially delaying Tesla’s efforts to develop self-driving cars and humanoid robots.
However, Musk quickly responded that Tesla did not send the Nvidia chips anywhere else, just in the warehouse. He noted that Tesla lacks the ability to accept Nvidia Gpus because of its unfinished factory in Austin, Texas.
However, he noted that the expansion of the Gigafactory is nearing completion and will accommodate 50,000 H100s for FSD training.
He also estimated that Tesla will spend $3 billion to $4 billion in 2024 to buy AI chips from Nvidia.
As of Tuesday’s close, Tesla was down 0.86%. Investors, who are banking on Mr Musk’s promise to deliver fully autonomous vehicles, remain slightly jittery. The company plans to launch its first self-driving taxi in August, while its Autopilot and FSD features continue to come under scrutiny due to a series of crashes.
Meanwhile, Musk’s AI startup xAI is competing with the likes of OpenAI and Google to create practical applications for generative AI and its underlying large-scale language models. Last month, the company successfully raised $6 billion based on the promise of advanced products and the infrastructure to support them.
