Nvidia Becomes First Company to Reach $4 Trillion Valuation
By Tom Kagy | 09 Jul, 2025
The surge in AI investments by tech giants around the world has turned Nvidia into the decade's indispensable chipmaker.
Nvidia has invested heavily in robotics as part of its "physical AI" push.
On Wednesday Nvidia shares rose 2.5% to hit a record high, pushing the company's valuation past the $4 trillion mark ahead of Microsoft, which has been its nearest rival since Trump began his tariff offensive against the international business order.
Until Trump came on the scene to disrupt global supply chains, Apple had been widely seen as the company most likely to hit the $4 trillion mark. But Trump's massive tariffs on imports from China cut Apple profits as it scrambled to shift much of its iPhone assembly to India and Vietnam.
Nvidia's main products are its various GPU, graphic processor chipsets that combine massively parallel processing with high-bandwidth memory chips from Samsung. These GPUs can process large quantities of data at unmatched speeds, making them indispensable for large-language AI models that now power virtually every type of generative AI applications.
Nvidia's advantage as the foundational supplier of AI ambitions also owes to its vast libraries of instructions for AI processing, like its CUDA-X and NVIDIA NPP Libraries which allow direct access to GPU's virtual instruction set necessary for executing compute kernels. These libraries make it extremely inefficient and uncompetitive for AI models to be built without relying heavily on Nvidia GPUs, ensuring Nvidia's supremacy in AI processing for the forseeable future.
To help ensure a prominent place in the dawning age of quantum computing, founder and CEO Jensen Huang is in talks to buy leading quantum computing startup PsiQuantum. Huang has also been aggressive with developing libraries to facilitate the integration of quantum processing to accelerate AI computation.
Nvidia's advantage as the foundational supplier of AI ambitions also owes to its vast libraries of instructions for AI processing, like its CUDA-X and NVIDIA NPP Libraries which allow direct access to GPU's virtual instruction set necessary for executing compute kernels.
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