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Nvidia, the chipmaker that dominates the artificial intelligence hardware market, has become the first company in history to surpass a $5 trillion market valuation. The company hit the milestone on Wednesday, 29 October, reaching it just 13 months after crossing $3 trillion. Nvidia’s stock has climbed more than 50% year-to-date, fuelled by surging demand for its graphics processing units (GPUs), which have become the essential hardware for training and running AI models.
The company commands an estimated 75% to 90% market share in the AI chip segment, making its processors the de facto infrastructure for everything from ChatGPT to autonomous vehicles. Nvidia expects to realise $500 billion in GPU sales through the end of 2026, compared to just over $100 billion in revenue during the first two quarters of 2025. Recent partnerships include deals with Uber to build self-driving cars, collaborations with Palantir and Oracle, and agreements with Nokia to help develop next-generation 6G cellular technology.
BTB So What?
On the surface, this is straightforward market dominance in a boom cycle. In reality, it’s about the consolidation of computational power into a single infrastructural chokepoint, and what that means when the architecture of intelligence itself runs through one company’s silicon. Nvidia isn’t only selling chips. It’s selling the substrate upon which the next generation of economic activity will run. The company’s valuation now roughly equals half the size of Europe’s benchmark Stoxx 600 equities index. When hyperscalers like Google, Microsoft, and OpenAI are racing to buy capacity, they’re not simply procuring hardware, they’re securing access to the means of cognitive production. Every AI laboratory, every enterprise scaling language models, every autonomous vehicle manufacturer requires Nvidia GPUs. This grants the company extraordinary leverage not just in pricing, but in shaping the development pathways of the technologies themselves.
The circular investment pattern compounds the risk. When Nvidia invests $100 billion in OpenAI, which then purchases billions in Nvidia chips, the velocity of money creates the appearance of organic demand. But if businesses can’t generate returns on AI investments that justify current spending, the flywheel reverses. The telecom crash analogy is apt: fibre-optic infrastructure built in the late 1990s took over a decade to be fully utilised because capacity outpaced actual demand. If AI infrastructure follows the same pattern, we’re not simply looking at a correction in Nvidia’s stock price, we’re looking at a revaluation of the entire AI sector’s growth assumptions.
There’s also a geopolitical dimension that’s underpriced. Nvidia’s chips are now strategic assets, subject to export controls and central to the tech rivalry between the US and China. The company’s $5 trillion valuation assumes relatively frictionless global market access. But if geopolitical tensions escalate, or if China accelerates development of domestic alternatives, Nvidia’s addressable market could contract suddenly.
The real story isn’t the number. It’s that a single company now represents the computational bottleneck for an entire technological epoch. And when infrastructure becomes this concentrated, the question isn’t whether it will face pressure, it’s what form that pressure takes, and whether the market’s assumptions about perpetual expansion can withstand a reality check on utilisation and returns.