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Is Nvidia’s slip below $200 just a bad day?

ByNoor BazmiNoor Bazmi
2 mins read
Is Nvidia's slip below $200 just a bad day?
  • Nvidia’s stock dipped below $200 as Google prepares new inference chips.
  • Even OpenAI has grown frustrated with Nvidia’s inference hardware.
  • The real threat is not any single rival but a wave of competition arriving at the same time.

Nvidia’s share price fell to $199.86 on Monday, a drop of less than 1%. On its own, that barely registers. But zoom out, and the picture looks more complicated. Google is coming for Nvidia’s fastest-growing market, billions of dollars are flowing into rivals, and a South Korean startup just raised $400 million with Nvidia squarely in its sights.

Nvidia closed at $199.48, down 0.79% on the day. The stock still sits well above its 20-day, 50-day, and 200-day moving averages, which are clustered around $181-$183, so the longer-term trend remains intact.

The MACD is still flashing a buy signal, and the ADX reading of 15.28 points to a weak but continuing upward trend.

Google takes aim at Nvidia’s fastest-growing market

While Nvidia’s stock treads water, Google is making its most direct push yet into the chip market.

The Alphabet-owned company is preparing to announce a new generation of tensor processing units, known as TPUs, at its Google Cloud Next conference in Las Vegas this week, with a focus on inference: the process of running AI models once they have already been trained.

“It now becomes sensible to specialize chips more for training or more for inference workloads,” Google Chief Scientist Jeff Dean said. The company is “looking at a whole bunch of different things,” he added, including how fast it can deliver AI results to users.

Big names are now in for the TPUs. Anthropic has signed a contract for 1 million TPU’s while Meta is using them through Google’s cloud as part of a multi-billion-dollar agreement. In the upcoming Google conference, Citadel Securities will be talking about how TPU’s are faster at training models than GPUs. This isn’t where it ends. Abu Dhabi’s G42 is also in discussion to access them.

Google is also loosening the rules around TPU access, letting some customers run the chips inside their own data centers and supporting outside tools like PyTorch, rather than locking users into Google’s own software stack.

Not to forget, OpenAI is also growing frustrated by Nvidia’s inference hardware and looking for alternatives, as reported by Cryptopolitan previously.

Billions are flowing into chip startups

Google is not the only one sensing an opening. AI chip startups pulled in $8.3 billion globally in 2026, according to data from Dealroom, putting the sector on track for a record year. In the U.S., Cerebras raised $1 billion in February. MatX, Ayar Labs, and Etched each secured $500 million rounds. In Europe, Axelera and Olix both raised over $200 million.

“It’s no longer a niche bet,” said Carlos Espinal of European VC firm Seedcamp. “It’s becoming a core part of how people think about AI infrastructure.”

Samsung-backed South Korean startup Rebellions raised $400 million at a $2.34 billion valuation, led by Mirae Asset Financial Group and South Korea’s state-backed National Growth Fund. The company has raised $650 million in the past six months alone, more than 75% of its total funding, and is now targeting U.S. customers and preparing for a public listing.

Its Rebel100 chip is built specifically for inference.

One constraint is memory. High-bandwidth memory is tight across the industry, and prices have risen sharply. “Memory is not very easy to get. But our demand is so huge,” Park said. Rebellions has an edge there: both Samsung and SK Hynix are investors, giving it better access than most rivals.

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Noor Bazmi

Noor Bazmi

Noor Bazmi contributes to Cryptopolitan news team equipped with a Media Studies degree. Noor covers news on blockchain, cryptocurrency, artificial intelligence, Big Tech, EV markets, global economics, and government policy shifts. She is taking studies in marketing to connect with global audiences.

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