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Nvidia recently reported its earnings. As expected, they lived up to the hype.
Earnings per share (EPS) were $6.12, a staggering 461% increase from last year. Meanwhile, revenue was $26 billion, a 262% jump from a year ago.
Nvidia’s stock rose 9%, closing at $1,037 on May 24. The investors reacted to the positive announcements made by the company, aside from the impressive earnings.
The company announced a 10-for-1 stock split. Here’s a breakdown of Nvidi across various metrics:
- The company’s gaming revenue increased to $2.65 billion, which is 18% higher than the previous period.
- Professional visualization earnings were $427 million.
- GPU sales to automotive sales were $329 million.
Will Nvidia Rally Further?
An important question is, will the Nvidia rally continue or hit a roadblock?
Marc Ostwald, Chief Economist at asset compamy ADM ISI, told Techopedia:
“The AI euphoria continues until Nvidia and other chip makers see slower orders. And, more importantly, until investors ask the question, “So you spent all this money on AI, what cost savings, productivity, and profits boost are you seeing?””
Paul Hickin, an independent markets expert, believes that the AI boom will drive Nvidia to rally further:
“While the AI and tech boom continues, Nvidia will continue to be a great stock choice. Nvidia has lit the way for its peers but undoubtedly will be there for its competitors to close the gap.”
Nvidia and Competitors
Nvidia was founded in 1993 to develop graphical processing units (GPUs) widely used in computers and gaming consoles.
The company held approximately 80% of the complete market share of GPUs in Q4 of 2023. AMD and Intel are some of the distant competitors.
AMD has debuted with its MI300 accelerator, while Intel is manufacturing the Gaudi3 AI accelerator. Microsoft, Meta, and Google are also entering the application-specific integrated circuits (ASICs).
Although tech executives take pride in their GPU reserve, access to Nvidia’s GPU remains high among the companies that are aspiring to lead in the AI industry. Being the leading supplier of GPUs, Nvidia is leading the market with a market cap of over $2.6 trillion.
With Nvidia taking over, making of the competitors are trying to create chips that are compatible with the AI models in a cheaper and faster way.
Cerebras, a startup based in Sunnyvale, California, claims that its GPU maintains the same level of performance. However, it reportedly uses less than half of the energy of Nvidia’s top-tier GPU.
On the other hand, another noticeable startup, Groq, manufactures Language Processing Units (LPUs) that can run complex language models more quickly. Serving multiple purposes (like working as a router and passing data among other LPUs) apart from having their own memory, the LPUs have the potential to run Large Language Models (LLMs) ten times faster than the current system.
