The Santa Clara-based chipmaker’s stock climbed nearly 5% in premarket trading on Wednesday, briefly touching $4.94 trillion before settling around $4.89 trillion in market value.

The rally followed Chief Executive Jensen Huang’s announcement of $500 billion in AI chip bookings and plans to build seven new supercomputers for the U.S. government.

Speaking at Nvidia’s developer conference in Washington, Huang disclosed that one of the supercomputers will be developed in partnership with Oracle and powered by 100,000 of Nvidia’s advanced Blackwell chips. 

The firm also confirmed a $100 billion partnership with OpenAI to develop GPU supercomputers and a $2 billion equity investment in Elon Musk’s xAI.

Nvidia’s transformation from a niche graphics card maker into the backbone of the artificial intelligence ecosystem has been commendable. The company now sits ahead of Apple, Microsoft, and Alphabet in valuation growth.

“In many ways, everything that could have gone right for the firm, has gone right over the last sort of 24 hours,” said Michael Brown, senior research strategist at Pepperstone.

For its fiscal second quarter of 2026, Nvidia reported revenue of $46.7 billion, a 56% increase year-on-year, with data-centre GPUs accounting for 88% of sales. The company’s stock added roughly $230 billion in value within a single day, illustrating its market-moving power.

Analysts, however, warn that Nvidia’s valuation, trading at about 50 times forward earnings, leaves little room for error. Given its dominant weighting in the S&P 500 and Nasdaq 100, any major price movement could send ripples through pension funds, ETFs, and technology portfolios across global markets.

Beyond the markets, Nvidia has also become an important player in U.S.–China technology diplomacy. Its Blackwell processors are at the heart of Washington’s export restrictions, aimed at limiting China’s access to advanced AI computing systems. U.S. President Donald Trump said on Wednesday he might raise the issue of the high-end chips when he meets Chinese President Xi Jinping.

To remain compliant with these export rules, Nvidia is designing modified versions of its chips for overseas markets, a strategy to sustain demand while scaling through geopolitical pressure. This could ultimately speed up the $5 trillion valuation reach for Nvidia.

But the growth comes with a price, where massive spending on research and development is driving heavy losses.

According to financial disclosures seen by The Information, the company spent $6.7 billion on R&D in the first half of the year, most of it tied to training models and maintaining the infrastructure behind ChatGPT. That pushed its cash burn to $2.5 billion, with its ability to strike a balance between rapid expansion and steep operating costs in question.

Despite the high outflow, OpenAI appears to be on solid footing for now. It closed June with around $17.5 billion in cash and securities, enough to sustain its aggressive investment strategy while targeting $13 billion in revenue and $8.5 billion in full-year cash burn by December.

The company is also manoeuvring to ensure value for insiders. In August, OpenAI entered early-stage talks for a stock sale that would allow employees to cash out, a deal that could peg its valuation at about $500 billion. That figure would place the firm among the most valuable technology companies worldwide, highlighting investor belief in its dominance in generative AI.

Growth around OpenAI has been strengthened by its deepening ties with chipmaker Nvidia. Earlier this month, Nvidia announced it would commit as much as $100 billion to support the firm, supplying high-performance data-centre chips to bolster training and inference at scale. This shows the growing demand for AI hardware but also the interdependence between model developers and infrastructure providers.

For competitors such as Anthropic and Google DeepMind, the challenge is increasing. OpenAI’s integration into Microsoft Copilot is spreading across industries from healthcare to finance, giving it a commercial reach that few competitors can match. 

Its spending levels are also setting new benchmarks for research intensity, with consequences for talent competition, regulation, and industry standards.