Why the once dominant Nvidia did not save the AI trade
Investors tracked every signal from interest rates, employment numbers, and comments from OpenAI. Nvidia’s latest earnings arrived during this tense period, and they did not change market direction.
Nvidia posted fiscal third-quarter results in October. The numbers came in above Wall Street expectations. Gil Luria from D.A. Davidson said the company delivered its best quarter of the year. The stock opened higher the next day but closed lower. Other AI stocks followed the same path. Sandisk, which had climbed on demand for storage in AI systems, dropped sharply that same day.
Jamie Zakalik from Neuberger Berman said that if such strong results did not lift AI stocks, then nothing else was likely to support them through the winter.
The market is dealing with several pressures. These range from interest-rate questions to concerns about the real strength of AI spending. Ken Mahoney from Mahoney Asset Management described this as a “perfect storm.”
Some traders think the selling came from large funds reducing exposure, not from a judgment about Nvidia itself. Nvidia said it has visibility on 500 billion dollars in expected revenue from its Blackwell and Rubin platforms through 2026. That is the longest forward view it has given in three years.
There were concerns as well. Ipek Ozkardeskaya of Swissquote pointed to large prepaid revenue and high inventory levels. Nvidia has been recognizing revenue before delivering chips. This is legal, but it creates a gap if orders slow. She said traders only dig this deep when they feel nervous, and that discomfort is rising.
Luria said recent debate on whether the market is in a bubble has grown more active. Mandeep Singh of Bloomberg Intelligence is not worried about high inventory levels. Nvidia is raising GPU capacity each year and wants to hold on to its allocation from Taiwan Semiconductor Manufacturing. Singh said that keeping that allocation is about staying ahead of AMD and Google’s tensor processing units. He also said a large revenue goal for next year will naturally require more inventory.
Some were concerned about accounts receivable growth, but Zakalik said Nvidia’s major customers have large cash flow positions, so the risk looks limited.
Interest-rate uncertainty continues to shape price action. September unemployment numbers were delayed because of a government shutdown. The Federal Reserve will not have October or November data before the December rate decision. Mark Malek of Siebert Financial said investors have become so focused on the Fed that they struggle to make practical decisions about company performance.
AI companies face borrowing-cost pressure in a higher-rate environment. That introduces added risk across hyperscalers.
Another issue is OpenAI. Many AI infrastructure projects require large debt financing, and traders are now asking whether OpenAI can fund what it has committed to. Luria gave the example of CoreWeave, which is borrowing heavily to build data centers for OpenAI. OpenAI does not yet have the revenue to cover these large obligations. Some investors are reminded of past bubbles and are reacting with caution.
OpenAI’s recent public comments added stress. Its chief financial officer spoke about a possible government support “backstop” during an event, which she later walked back. The remark shook confidence among traders already questioning spending levels across the sector.
Google’s launch of Gemini 3 also influenced market reactions. Gemini 3 was trained on Google’s tensor processing units and performed better than OpenAI’s most recent models in some technical areas. Singh said this shows Google’s capital spending is delivering results, and this could affect others that depend mainly on Nvidia hardware.
Singh said Nvidia will continue supplying Google, but large revenue growth next year will depend more on Microsoft, Meta, OpenAI, and other major buyers.
He also pointed out a growing question. How much spending goes toward training and how much goes toward inferencing. Training improves the models, but inferencing produces the revenue that supports long-term growth.
This mix of strong earnings, growing financial commitments, and rate uncertainty shows why the AI trade is under pressure. The market is no longer reacting with excitement. It is reading every detail with caution.
#Nvidia #AIStocks #StockMarket #FederalReserve #OpenAI