Is NVIDIA the Best Quantum Computing Stock in 2026?

Investors might not be aware of how important it is to build Quantum alongside Generative AI, particularly for several of the members of the “Magnificent Seven”. Google (Alphabet), Amazon, and Microsoft have produced proprietary quantum processors called Willow, Ocelot and Majorana respectively. The Quantum AI Team's work at Google on Willow produced superior results in comparison to prior participants who had been utilizing error correction to improve their circuit performance. Google also posted an outstanding randomized circuit sampling (RCS) benchmark which helped to jumpstart a stock rally. However, the researchers have emphasized that the achievements remain just the first step in developing the technology.

The practical timeline for this eventuality is therefore important, as many in the field do not believe that true, practical quantum advantages over classical computation will be available before 2030; a significant number believe it will take until the mid-2040's before we will see significant quantum advances.

Today, quantum computing is still primarily an experimentally-oriented endeavor at the enterprise level, and the majority of companies are still heavily involved in the research and development stage. Specifically, IonQ and Rigetti are both developing gate-based systems that utilize trapped ions and superconductors, whereas D-Wave's quantum annealing system focuses on optimization issues.

Ultimately, these companies are engaged in some of the most difficult physical challenges associated with qubit development and utilization, and thus all work done is foundational to future commercial deployment of quantum computers.

In 2026, Nvidia has established a clear quantum computing strategy that will serve as the "universal bridge" between classical supercomputing technology and quantum hardware. Instead of focusing on developing a proprietary Quantum Processor Unit (QPU), Nvidia focuses on producing the necessary software and hardware "glue" that allows quantum-classical computer hybridization to function effectively.

Nvidia’s primary quantum computing business areas and products are CUDA-Q, cuQuantum, NVQLink, DGX Quantum and NVAQC.

1. CUDA-Q (Software Platform)

CUDA-Q is an open-source, QPU-agnostic platform that serves as the "operating system" for hybrid computing. It allows developers to write code in a single environment (C++ or Python) that runs across CPUs, GPUs, and QPUs. As of 2026, it integrates with approximately 75% of the world’s publicly available quantum processors, including those from IonQ, Rigetti, and IQM. It automates the distribution of tasks, sending heavy mathematical simulations to GPUs and specific quantum tasks to QPUs.

2. cuQuantum (Simulation SDK)

Researchers will simulate the expected behaviour of quantum circuits with Nvidia GPUs while quantum hardware has yet to be developed on a large scale. With the cuQuantum framework, researchers can simulate quantum circuits thousands of times faster than traditional CPU techniques by using Nvidia GPU-accelerated libraries (e.g., cuStateVec and cuTensorNet). The most recent version (v25.11) released of the cuQuantum software includes new features such as the ability to simulate the propagation of random Pauli operators on quantum circuits and stabilisers, both of which play a major role in the development of QEC and in designing larger, more robust quantum computing systems.

3. NVQLink (Hardware Interconnect)

Announced in late 2025, NVQLink is a high-speed hardware architecture designed to solve the "latency bottleneck" in quantum computing. It provides a direct, low-latency (<4 microseconds) link between the GPU and the Quantum System Controller. This speed is vital for quantum error correction, where classical GPUs must process error data and send corrections back to the quantum processor before the "qubits" lose their quantum state (decoherence).

4. DGX Quantum (Hybrid System Architecture)

Nvidia partners with companies like Quantum Machines to build the DGX Quantum, a physical hardware system. It is used by global research centers (like the Israeli Quantum Computing Center and various U.S. National Labs) as a "workbench" to develop the first generation of utility-scale quantum applications in fields like drug discovery and materials science.

5. NVAQC (Research & Ecosystem)

The NVIDIA Accelerated Quantum Computing Research Center serves as a hub for ecosystem development. Nvidia uses its venture capital arm to invest in leading quantum startups (such as Quantinuum, QuEra, and PsiQuantum) to ensure that their next-generation hardware is natively compatible with Nvidia's stack.

In contrast to others in the industry, NVIDIA has carved out an entirely different path through the QPU landscape. Instead of attempting to develop the best QPUs possible, NVIDIA is focusing on building a complete ecosystem of Quantum Computing and accelerated (also called classical) computing solutions, which it will connect together through Middleware, by integrating both the software and hardware components for Hybrid systems.

The CUDA-Q solution allows Application Developers to create Applications which work on CPUs, GPUs and QPUs without having to develop their entire stack over again. Additionally, NVQLink provides Low Latency / High Bandwidth connectivity between QPUs and GPUs through a high-speed data path through which data will flow at lightning speed allowing for seamless communication.

The bridging strategy is a prudent hedge for Nvidia because it prepares the company for winners regardless of which quantum processor design or qubit architecture becomes the standard format. In addition, Nvidia's bridging approach aligns well with the various tools it offers to support the entire ecosystem, one being cuQuantum, which is a software development kit to help engineers develop quantum workflows, through using GPGPU accelerated computing. It enables engineers to use a known software development framework for constructing the next generation quantum systems they will use.

Additionally, in March 2023, Nvidia unveiled DGX Quantum, which combines cutting-edge generation NVIDIA GPUs with Quantum Machines' quantum hardware, and aims to give research scientists access to tools leveraging the power of quantum computing. With DGX Quantum, Nvidia is poised for tangible innovation, helping develop fuel-efficient jet aircraft engines and streamlining drug and health related product development.

By taking a wider angle of view on the situation, we can see that there are macro support systems for this view. The performance of Nvidia will largely depend on what the big-tech companies spend money on with regards to AI; and that they will continue to accelerate their spending on capital expenditures (CapEx). Currently, the slope of the CapEx lines shows that the hyperscaled data centers (notably to build Out) and the procurement of networking and chips are high priorities.

Hyperscalers are projected, according to Goldman Sachs, to spend subsequently nearly $500 billion on AI infrastructures by 2026, and that according to McKinsey, the AI infrastructure market size could reach approximately $7 trillion by the end of the decade; therefore, this is very positive news for Nvidia in the near term.

More importantly, framing AI infrastructure provides a secular multi-year cycle for growth for Nvidia. As quantum computing takes hold as a more significant contributor to the overall AI conversation over the next number of years, there will continue to be outsized demand for Nvidia products. CUDA-Q and NVQLink are not yet substantial relative to the company's core compute and networking areas, but the pursuit of quantum will become increasingly relevant as we progress through the AI infrastructure era.

What do you think about the current price of NVDA stocks as of Jan 21? At this point, NVDA stocks are being traded at a forward PE ratio (Price to Earning ratio) of 24, making it appear very attractive based on its existing growth profile and Wall Street's forecasts.

Additionally, I believe that Quantum Computing is another strong pillar within NVDA's larger strategy of long-term growth as AI technologies continue to proliferate throughout the business world. Those individuals considering whether to purchase NVDA stocks over the next couple of years should take note of the potential for future expansion of its valuation and see NVDA as a viable long-term hold for an investor.

Quantum computing utilizes the principles of quantum mechanics, including superposition, which describes the lack of a definitive state of an object at a sub-atomic level. This leads to the potential for considerable increases in performance, relative to traditional computing methods, in certain types of computation. However, the technology is still largely under development as of 2025. Improvements to the speed and cost of building quantum systems, as well as the emergence of cloud-based solutions that allow academics and software developers to work with quantum systems, have increased the number of people who can access quantum systems.

Google showcased, through their Project "Willow", that the performance of Error Correction Algorithms will continue to be improved until all current Algorithms have been replaced with Algorithms using quantum-based Systems and Algorithms derived from quantum-based Systems will be seamlessly integrated into current Quantum Computing Platforms. Therefore, it is no surprise that the RCS Benchmark Scores achieved by Google’s Willow represent the highest quality of all projects that have previously been tested within this area, but this is still only a beginning on the path of the development of Quantum Systems to be utilized for practical purposes.

While the future of quantum computing is uncertain, it makes sense to have a diversified portfolio, because pure play is in high risk.

Additionally, while software has been growing significantly in the industry, there are also companies that are dedicated to creating integrated hardware and software; these companies will continue to be important players in the quantum computing landscape. Similarly, to gain additional exposure to the quantum computing market, there is a quantum exchange-traded fund (ETF) called Defiance Quantum. Because it may take a long time for a quantum competitive advantage to be achieved, some experts believe that there will not be widespread quantum advantage until 2030, while others expect it to take until the mid-2040s.

As such, it can be beneficial to have your investment capital distributed among several companies, some of which are already generating cash flow and others that are risky pure plays. A diversified approach that includes both types of companies is a great way for investors to get started in quantum computing.

Is Nvidia the most attractive quantum computing investment in 2026? For many investors, the answer will likely be yes. Nvidia is not building a quantum processing unit (QPU), but rather creating the necessary infrastructure for quantum and classical computing to work together with products such as CUDA-Q, NVQLink, cuQuantum and DGX Quantum. As an early-stage company focused on the AI infrastructure space, Nvidia will likely benefit from increased spending on this segment as well as offering a way to invest in quantum companies without the risk associated with a pure quantum play.

Therefore, an investor can hold Nvidia stock while also investing in select quantum businesses or an ETF. If you are considering a single stock as the foundation of your quantum investment strategy in 2026, Nvidia will likely be the best combination of size, strategy, and longevity of any publicly traded company. Additionally, if the price of Nvidia stock is being primarily driven by its core AI business and not accounting for its role as a bridge to quantum computing, this could provide long-term shareholders with a potentially advantageous investment position relative to other quantum investments.