What many investors might not fully realize is that several members of the “Magnificent Seven” are also exploring quantum computing technology alongside their existing generative AI efforts. While Alphabet<\/a>, Amazon, and Microsoft have received some notoriety around their custom quantum processors, I think there’s a more lucrative opportunity hiding in plain sight.<\/p>\n I’ll detail how Nvidia (NVDA<\/a> +1.02%) is quietly building a full-spectrum quantum computing suite, and explain why this could be a major catalyst for the company as the artificial intelligence (AI) infrastructure era begins.<\/p>\n Image source: Nvidia.<\/p>\n Nvidia is laying the foundation between quantum and accelerated computing<\/p>\n At the moment, quantum computing is an exploratory pursuit. While some businesses are assessing how the technology may be integrated within their existing AI framework, quantum technology has little use at the enterprise level today.<\/p>\n Against this backdrop, pure-play developers are primarily focused on research and development right now. IonQ and Rigetti specialize in gate-based approaches leveraging trapped ions<\/a> and superconducting techniques<\/a>. D-Wave, for its part, is more niche — focusing on quantum annealing<\/a> processes for optimization tasks.<\/p>\n The main takeaway is that quantum pure plays are currently engaged with the actual physics behind the creation and configuration of quantum bits — known as qubits<\/a> — within new computing architectures.<\/p>\n As mentioned, the big three cloud providers have each designed their own quantum processors — dubbed Willow<\/a> (Alphabet), Ocelot<\/a> (Amazon), and Majorana<\/a> (Microsoft). While quantum computing is not a meaningful contributor to their respective businesses at this time, it’s clear that big tech is fascinated by how this emerging technology may eventually impact the broader AI opportunity.<\/p>\n Nvidia’s approach is entirely different from that of its megacap counterparts, as well as the pure plays. Instead of building its own quantum computers, Nvidia is seeking to become a bridge between the software and hardware investments necessary to build these systems.<\/p>\n Nvidia offers a software platform called CUDA-Q<\/a>, within which developers can write applications that work across a network of CPUs, GPUs, and QPUs (quantum processing units). On the hardware side, Nvidia has built a high-speed interconnect called NVQLink<\/a>. NVQLink represents a pathway for QPUs and GPUs to seamlessly communicate without straining latency and bandwidth.<\/p>\n Essentially, Nvidia’s decision to provide a software and hardware ecosystem allows programmers to easily test their AI workloads across a hybrid quantum-classical computing environment. This is a particularly smart move because it positions Nvidia to be a beneficiary regardless of which quantum processor designs or qubit architecture emerges as the market standard down the road.<\/p>\n Today’s Change<\/p>\n (1.02%) $1.92<\/p>\n Current Price<\/p>\n $190.53<\/p>\n Key Data Points<\/p>\n Market Cap<\/p>\n $4.6T<\/p>\n Day’s Range<\/p>\n $188.00 – $192.69<\/p>\n 52wk Range<\/p>\n $86.62 – $212.19<\/p>\n Volume<\/p>\n 140M<\/p>\n Avg Vol<\/p>\n 189M<\/p>\n Gross Margin<\/p>\n 70.05%<\/p>\n Dividend Yield<\/p>\n 0.02%<\/p>\n Will 2026 be a big year for Nvidia?<\/p>\n Nvidia’s growth trajectory is directly tied to the budgets of big tech. As the slope of the lines in the chart illustrate, AI hyperscalers<\/a> are accelerating their capital expenditures<\/a> (capex) — suggesting that data center buildouts, networking equipment, and chip procurement remain high priorities.<\/p>\n GOOGL Capital Expenditures (TTM)<\/a> data by YCharts<\/a><\/p>\n Research from Goldman Sachs suggests that the hyperscalers alone will contribute nearly half a trillion dollars to AI infrastructure<\/a> in 2026. While this is great news for Nvidia in the short term, AI infrastructure is expected to become a nearly $7 trillion opportunity<\/a> by the end of the decade, according to management consulting firm McKinsey & Company.<\/p>\n I bring this up to drive home a couple of key ideas. First, Nvidia appears well-positioned to benefit from rising data center spend going into next year. More importantly, however, AI infrastructure is shaping up to be a longer-term secular opportunity.<\/p>\n Given these dynamics, Nvidia could continue receiving outsized demand for its products as quantum computing becomes a more meaningful contributor to the broader AI narrative over the next several years. So while CUDA-Q and NVQLink may not yet be major contributors to Nvidia’s business today relative to its core compute and networking services, I’m encouraged by the company’s pursuit of quantum computing and see these products eventually becoming an important storyline in its evolution throughout the AI infrastructure chapter.<\/p>\n Is Nvidia stock still a good buy?<\/p>\n As of this writing (Dec. 22), Nvidia trades at a forward price-to-earnings<\/a> (P\/E) multiple of just 24. Considering Nvidia’s current growth in combination with Wall Street’s outlook, the stock is valued quite reasonably.<\/p>\n<\/p>\n
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