NEW YORK — Nvidia posted another record quarter, easing some concerns about the profitability of artificial intelligence. Chief Executive Jensen Huang again voiced confidence in future growth, saying the AI industry is passing an inflection point. Against that backdrop, the administration of U.S. President Donald Trump has moved to impose broad tariffs on semiconductors, drawing controversy because the measure could disrupt the supply chain and ecosystem of an AI industry that has only recently found its footing.
Nvidia Jumps 8.7% on Record Results as Q2 Revenue Rises 106%
Nvidia, the world's most valuable company by market capitalization, surged 8.74% on the New York market on the 27th, lifting the broader indexes. The Dow Jones Industrial Average rose 0.20%, the Standard & Poor's 500 gained 0.72% and the Nasdaq Composite added 1.57%. Nvidia's advance pulled up a wide range of chip stocks, including Broadcom (4.49%), Intel (4.36%) and SK hynix (2.27%). The Philadelphia Semiconductor Index climbed 2.33%.
Nvidia's market value increased by $442 billion (about 610 trillion won) on the day, the second-largest single-day gain on record. The record is the $450 billion added by Microsoft last month.
The rally followed a favorable reception for fiscal second-quarter results, covering May through July, released after the previous session's close. Nvidia said in a regulatory filing on the 26th that second-quarter revenue rose 106% from a year earlier to $96.22 billion (about 133.2 trillion won). That exceeded the $92.17 billion consensus compiled by the London Stock Exchange Group by more than $4 billion, and marked a 13th consecutive quarterly revenue record.
By segment, the data center business, which includes AI chip sales, generated $89 billion, up 117% from a year earlier and 18% from the prior quarter, accounting for 92% of total revenue.
Sales to hyperscalers, the operators of the largest data centers, more than doubled to $48.7 billion from $24.2 billion a year earlier. Sales to other enterprise customers also jumped to $40.3 billion from $16.9 billion.
Earnings per share came in at $2.22, above Wall Street's $2.10 estimate. Gross margin was 75% and operating margin 66.5%. Free cash flow reached $21.3 billion, up 58.7% from a year earlier.
The company also projected that the strength would carry into the fiscal third quarter, from August to October, with revenue rising to $108 billion (about 149.5 trillion won). That is above the market forecast of $104 billion.
Nvidia guided third-quarter gross margin to 74%, below the 75% posted in the second quarter, citing the surge in prices for memory chips including high-bandwidth memory. It said the margin would fall further to 71% to 72% in the fourth quarter before stabilizing at 72% to 73% from fiscal 2028.
The company said its supply-chain commitments total $279 billion (about 386 trillion won), a figure interpreted as relating mainly to long-term memory chip supply contracts with Samsung Electronics, SK hynix and Micron.
"70% Growth Even in 2028": Huang Eases Some AI Investment Concerns
Chief Financial Officer Colette Kress added that revenue in fiscal 2028 is expected to grow about 70%, far above the market forecast of 45%. Huang noted that the company had never before forecast results or given guidance a year in advance.
Huang again offered an optimistic view on arguments that AI investment has gone too far. "AI has reached an inflection point," he said, arguing that tokens are productive and highly profitable and that computing has now become revenue. "This time last year, there was only one AI lab driving infrastructure expansion, but now we are in a golden age with new labs and startups pouring out," he said, stressing that Vera Rubin, now entering full production, was developed for precisely this moment.
Huang also pushed back on the circular-transaction concerns repeatedly raised on Wall Street, saying he sees the situation differently. His explanation was that investment in major AI companies, at about $50 billion, amounts to only a small fraction of Nvidia's free cash flow, and that the financial risk is limited because its versatile and durable AI computing servers can be redeployed to other customers if needed.
On investments in OpenAI, the developer of ChatGPT, and Anthropic, the developer of Claude, Huang called them a once-in-a-generation opportunity. "The only thing I regret is not investing more and earlier," he said. "A long time ago, people asked me why we, a chip company, were working with memory chip suppliers," he added. "Now people understand that what we prepared at the upstream end of the supply chain was an ingenious strategy."
On the AI chips that OpenAI and Anthropic are developing in-house, Huang said Nvidia is building something entirely different. Many custom chip projects are focused on inference, he said, while Nvidia provides a complete AI platform that can be used across multiple clouds.
Separately, U.S. technology outlet The Information reported on the 26th that Nvidia had agreed to acquire Hugging Face, an AI model sharing platform, for $12.9 billion (about 17.9 trillion won). The move is seen as a bid to take the lead in the open-source AI model ecosystem, as opposed to the closed approach of OpenAI and Anthropic. Hugging Face is an AI model distribution platform founded in 2016 by French entrepreneur Clément Delangue and others.
Trump Administration Weighs Chip Tariffs Tied to U.S. Investment
As Nvidia revived expectations for AI profitability, the Trump administration began seriously reviewing steep tariffs on semiconductors. U.S. political outlet Politico reported that the administration is discussing a sharp expansion of the range of products subject to chip tariffs, covering not only semiconductors themselves but also finished goods such as laptops, game consoles and data center servers. Tariff rates and quotas would also vary by country.
According to sources, Commerce Secretary Howard Lutnick is considering linking tariff relief for foreign companies to their semiconductor manufacturing investment in the United States as a way to promote domestic production. Under the concept, a certain volume of imports would enter duty-free, with that allowance tied to the scale of production in the United States.
The approach is similar to the terms applied in the U.S.-Taiwan trade agreement in January. At the time, the United States lowered its reciprocal tariff on Taiwan to 15% from 20% in return for Taiwan's $250 billion semiconductor investment plan. TSMC and others were to receive partial tariff exemptions in proportion to their semiconductor production in the United States.
Trump had already signed a proclamation in January imposing a 25% tariff on semiconductors imported into the United States and then re-exported to other countries, such as Nvidia's H200 AI chip. The White House said at the time that Trump could soon impose broader tariffs on imports of semiconductors and their derivative products to encourage manufacturing in the United States. U.S. Trade Representative Jamieson Greer also said in May, when Micron decided to expand capacity domestically, that across-the-board tariffs on semiconductors would come at an appropriate time.
Separately, Nvidia said in its second-quarter earnings release that its work to optimize its products for Chinese open models, including DeepSeek's V4 Flash and Alibaba's Qwen 3.8, has come under U.S. regulation. The company said the U.S. administration is reviewing measures that would restrict its ability to support Chinese open models at all, and warned that such a step would have a material impact on its business. According to Bloomberg on the 27th, the Commerce Department's Bureau of Industry and Security has also opened an investigation into Apex Logistics, a Singapore-based company, on suspicion of shipping Nvidia AI chips to China.
Although Nvidia has used its results to ease some concerns about AI investment for the first time in a while, disputes over circular transactions and the profitability of AI model companies appear set to continue for some time. Above all, the tariff policy of the Trump administration could reshape an AI industry already struggling with a memory chip supply crunch, making the outcome a focus of attention.
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