On Tuesday, Nvidia’s stock declined following reports that the US Department of Justice (DOJ) issued the firm an antitrust subpoena.
The chipmaker closed the trading by plummeting -9.53% to $108.00 per share. It continued to dip by -0.98% to $106.94 in the pre-market session.
According to reports, Nvidia has suffered a sharp loss in a day in its market cap, deducting almost $280.00 billion in value.
Moreover, the significant slide came as the DOJ subpoenaed the chipmaker and various companies as the regulator sought evidence that Nvidia had violated US antitrust laws.
Meanwhile, a spokesperson for the chipmaker stated that customers have the flexibility to choose the solutions that best meet their needs. They added that the firm’s recent outstanding performance is a testament to its success based on merit.
However, reports indicated that the subpoena represents a step up in the process, as it legally requires the recipients to provide information. This suggests that the government might be preparing to file a formal complaint against Nvidia.
Furthermore, US antitrust officials are concerned that the chipmaker is hindering businesses from switching to other artificial intelligence (AI) and chip providers. According to sources, Nvidia has even penalized customers who don’t exclusively use its AI services.
Global Chip Stocks Fall After Nvidia Sell-Off on Wall Street
According to reports, global semiconductor-related stocks slid on Wednesday’s Asian evening session, following an overnight significant dip in Nvidia’s share price in the US.
Additionally, economic data released on Tuesday reignited concerns about the state of the US economy.
Furthermore, Nvidia’s value loss extends to South Korea’s chipmaker, SK Hynix, and conglomerate Samsung Electronics.
Meanwhile, Taiwan Semiconductor Manufacturing Company (TSMC), a contract chip producer, experienced a more than -5.00% drop.
TSMC produces Nvidia’s high-performance graphics processing units (GPUs), which are vital for powering large language models. These GPUs are also essential for advanced machine-learning systems that recognize and generate text.
