Back in California's gold rush in the mid-1800s, thousands of individuals flocked to the region hoping to find gold and strike it rich. However, the easy money was instead made by the suppliers who sold tools to the gold prospectors.
Today, the term "pick-and-shovel investing" honors that legacy. Oftentimes, providers of ancillary products and services achieve greater success than pure-play companies do.
Could this be the case with Nvidia (NVDA 2.13%) in the quantum computing market? Maybe so.
Image source: Nvidia.
Simulation paves the way for reality
Several companies are racing to develop large-scale quantum computers that can be utilized in a wide range of practical applications. They include tech giants such as Google Quantum AI parent Alphabet (GOOG 2.49%) (GOOGL 2.30%), Amazon (AMZN 3.89%), and Microsoft (MSFT 2.44%) as well as rising stars like D-Wave Quantum (QBTS 5.12%) and IonQ (IONQ 7.83%). However, Nvidia isn't in this group.
That doesn't mean that Nvidia doesn't have a vested interest in quantum computing, though. And the chipmaker doesn't have to wait for quantum computing to fulfill its potential to make money, either.
Researchers must develop simulations of quantum systems to design and test algorithms and circuits. However, access to quantum processing units (QPUs) today is limited and expensive. Nvidia recognized this challenge and offers a solution: Use its graphics processing units (GPUs) on classical computers for quantum simulation.
Nvidia Quantum Cloud supports quantum simulation using the company's GPUs and its CUDA-Q quantum computing platform. Roughly 75% of organizations deploying QPUs use CUDA-Q.
Three of the four largest cloud service providers have integrated Nvidia Quantum Cloud into their platforms: Microsoft Azure, Google Cloud, and Oracle (ORCL 2.05%) Cloud Infrastructure. The notable exception is Amazon Web Services (AWS). However, AWS allows QPU developers to use Nvidia's CUDA-Q.
Nvidia's bridge to the future
Nvidia's quantum opportunities aren't limited to simulation. The likelihood is that most practical quantum computers will be hybrid systems that connect QPUs with classical supercomputers for the foreseeable future.
The problem is that qubits (the basic units of information in quantum computers) are notoriously unwieldy, at least for now. Because they're prone to errors, complex calibration processes and control algorithms are required to keep them on track. Nvidia is addressing this challenge in two ways.
NASDAQ: NVDA
Key Data Points
First, the company's GPUs are ideally suited for powering the supercomputers needed in hybrid quantum-classical systems. Second, Nvidia has developed a low-latency, high-throughput bridge between QPUs and its GPUs called NVQLink.
Nvidia found and CEO Jensen Huang describes NVQLink as "the Rosetta Stone connecting quantum and classical supercomputers." He recently predicted, "In the near future, every Nvidia GPU scientific supercomputer will be hybrid, tightly coupled with quantum processors to expand what is possible with computing."
A familiar path
Making money as a pick-and-shovel play in quantum computing should be relatively straightforward for Nvidia. The company has successfully navigated a similar path in artificial intelligence (AI).
OpenAI, Google, and others have developed powerful large language models (LLMs). Many of these companies are also pioneering agentic AI and working on artificial general intelligence (AGI) and AI superintelligence (ASI). Nvidia opted not to compete on their turf. Instead, it's supporting them with the chips and software tools that make their jobs easier.
In many respects, Nvidia's strategy in quantum computing mirrors the approach it has taken with AI. With the company generating revenue of $57 billion in the third quarter of 2025 and projecting revenue of $65 billion next quarter, Nvidia's AI strategy is paying off handsomely. I think supplying the picks and shovels for the quantum computing gold rush will prove to be a winning approach over the long run, too.
