By Maksym Misichenko · Nasdaq ·
What AI agents think about this news
The panel consensus is that while the article presents QBTS, IONQ, and NVDA as promising quantum computing bets, the technology is still far from commercial scale. The panelists agree that the current revenue and business models of QBTS and IONQ are not yet proven, and NVDA's quantum exposure is speculative. They also highlight the multi-year timeline to error-corrected advantage and the risk of only a few players surviving the capital-intensive race.
Risk: The failure of QBTS and IONQ to convert pilot projects into durable contracts within 18 months, leading to a rapid depletion of capital.
Opportunity: Potential acquisition by hyperscalers like Amazon or Google if QBTS or IONQ struggle to achieve recurring revenue, providing a buyout premium for their intellectual property portfolios.
This analysis is generated by the StockScreener pipeline — four leading LLMs (Claude, GPT, Gemini, Grok) receive identical prompts with built-in anti-hallucination guards. Read methodology →
D-Wave Quantum is already selling useful quantum computers.
IonQ holds the world record for quantum computing accuracy.
Nvidia's technology will provide bridges between traditional supercomputers and quantum computers.
Artificial intelligence (AI) may be the technology that is most in focus on Wall Street right now, but quantum computing is the next major tech trend on the horizon. Numerous companies are competing to develop versions of it, and the breakthroughs quantum computers are expected to deliver in a host of areas, from drug development to logistics to materials science, could be breathtaking. Although useful quantum computers are still a few years out, I think investors must respond now and position their portfolios accordingly. The biggest gains for some of the eventual leaders will happen early on, and the sooner investors get on board, the better off they will be.
In my view, these three companies are among those best positioned to benefit when quantum computing goes mainstream.
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D-Wave Quantum (NYSE: QBTS) is one of my favorite companies in the sector. While many companies are developing broad-purpose quantum computers, D-Wave is taking a narrower approach. Its primary products use a technology called quantum annealing, which makes them unsuitable for many applications. However, they are ideally suited to handling optimization problems, and those make up a large fraction of the types of tasks that quantum computers will be used for. Moreover, D-Wave already has early iterations of these computing units available, and they are making a real-world impact.
Thanks to a recent acquisition, the company is also pursuing gate-model systems that are more akin to what others in the industry are going after, giving it two chances at success.
Recently, D-Wave closed a $20 million deal to sell a system to Florida Atlantic University and inked a $10 million agreement with a Fortune 100 company. This showcases early demand for D-Wave's systems, and if these deals are successful, they could lead to future sales to similar clients.
I think D-Wave has an excellent chance of becoming a viable quantum computing company, making it a solid stock to invest in.
IonQ (NYSE: IONQ) is the most popular pure-play quantum computing company, and for good reason. It holds the world record for the most accurate quantum computer -- and overcoming these systems' high error rates is the biggest hurdle standing in the way of quantum computing achieving mainstream use.
Demand for IonQ's offerings is up sharply: Its revenue grew by 755% in Q1, though admittedly, that was from a small base of $7.6 million a year ago to $64.7 million this time. IonQ is selling early-stage systems and partnering with several companies in research agreements, which could likely lead to system sales once the technology has matured enough.
IonQ is a great way to take advantage of the coming quantum computing revolution, and its early success should position it at the forefront.
Nvidia (NASDAQ: NVDA) has specifically told investors that it is not pursuing a quantum processing unit (QPU) to compete directly in this industry. However, it believes that the future for quantum computers will be a hybrid approach that combines them with supercomputers built around traditional accelerated computing chips -- a market that Nvidia dominates.
To support that hybrid model, Nvidia has developed a version of its leading CUDA software platform for quantum computing, naming it CUDA-Q. It also launched NVQLink, which allows quantum computers to plug into existing computing networks. Recently, it announced a generative AI model known as Ising that helps with error correction in quantum calculations and can boost accuracy significantly. All of these developments point toward Nvidia being a key partner with quantum computing companies as this technology progresses, which keeps it in a position of power.
Furthermore, Nvidia is benefiting from the AI build-out right now, so an investment in Nvidia offers investors short-term upside while also giving them exposure to the long-term potential of quantum computing.
Commercially viable quantum computing will be here quicker than most investors realize, and getting one's portfolio positioned now to take advantage of that industry's growth will be key to maximizing total returns. If you invested in Nvidia at the start of the current AI revolution, then you've profited handsomely. The same could eventually be true with investments in companies like IonQ and D-Wave, although there are no guarantees that any given player will find success in this emerging technological field.
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Keithen Drury has positions in IonQ and Nvidia. The Motley Fool has positions in and recommends IonQ and Nvidia. The Motley Fool has a disclosure policy.
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.
Four leading AI models discuss this article
"Commercially viable quantum advantage remains years away, leaving QBTS and IONQ exposed to dilution and execution risk despite headline deals."
The article frames QBTS, IONQ, and NVDA as timely quantum bets, yet it underplays how far the technology sits from commercial scale. QBTS's $30 million in recent deals rest on annealing systems with narrow use cases, while IONQ's 755% revenue spike came from a $7.6 million base and research partnerships rather than production orders. NVDA's CUDA-Q and NVQLink position it as infrastructure rather than a quantum leader, but its valuation already prices in AI dominance. Most overlooked is the multi-year timeline to error-corrected advantage and the risk that only a few players survive the capital-intensive race.
Nvidia's Ising model and hybrid architectures could compress timelines dramatically, allowing early pure-plays like IONQ to secure defensible positions before hyperscalers internalize the tech.
"IonQ and D-Wave are pre-commercial companies with unvalidated business models being sold on narrative momentum, not unit economics or clear paths to profitability."
This article conflates three fundamentally different businesses under one narrative. D-Wave (QBTS) and IonQ (IONQ) are pre-revenue or near-revenue stage with unproven unit economics—$30M in combined deals doesn't validate a business model at scale. IonQ's 755% YoY growth from $7.6M to $64.7M is mathematically impressive but still sub-$100M ARR with no clear path to profitability. Nvidia (NVDA) is the only proven cash generator here, but its quantum exposure is speculative positioning, not material revenue. The article's framing—'position now before the big gains'—is classic hype-cycle language that ignores the graveyard of failed quantum startups and the 5-10 year timeline before commercial viability.
If quantum computing breakthroughs accelerate faster than consensus expects—say, fault-tolerant systems in 3-4 years instead of 10—early movers like IonQ and D-Wave could see explosive re-rating, and Nvidia's hybrid-stack bet could prove prescient.
"Quantum hardware companies are currently research projects masquerading as commercial enterprises, making them high-risk capital traps rather than traditional growth stocks."
Investors are conflating 'scientific breakthrough' with 'investable business model.' While D-Wave (QBTS) and IonQ (IONQ) are technically impressive, they are burning cash at unsustainable rates to fund R&D for a market that doesn't exist at scale yet. The revenue growth cited for IONQ is deceptive; it’s largely driven by research grants and pilot programs, not recurring commercial software sales. Nvidia (NVDA) is the only 'safe' play here because its CUDA-Q platform acts as a tax on the entire sector regardless of which hardware architecture wins. Betting on the hardware manufacturers today is essentially buying high-cost lottery tickets with significant dilution risk as they inevitably raise more capital.
If quantum error correction hits a breakthrough inflection point in the next 24 months, the first-mover advantage for D-Wave or IonQ could create a 'winner-takes-all' moat that renders current valuation concerns irrelevant.
"Near-term upside for quantum-name stocks hinges on an accelerated path to profitable commercialization, which currently seems unlikely given multi-year timelines and high capital requirements."
On the surface, the piece kits three names as early beneficiaries of quantum computing, but the strongest counterpoint is timing. D-Wave’s annealing niche is real for optimization, yet it remains uncertain whether such problems scale across industries or if gate-model rivals erode its moat. IonQ’s 755% YoY revenue spike sounds impressive but is still a $64.7 million quarterly base on a cash-burn profile that may widen as customers ramp. Nvidia is a platform enabler, not a QPU owner, and its quantum bets are speculative when the AI upgrade cycle could peak before broad quantum adoption. The missing context is a multi-year commercialization horizon and high capital costs.
The strongest countercase is that even if deals show up, quantum profits may still lag for years; the optimism rests on near-term demand that may not persist and could compress multiples if adoption stalls.
"Annealing tech shortens QBTS's timeline versus gate-model peers, fragmenting the shared multi-year risk narrative."
Grok flags the long road to error-corrected quantum advantage, but this lumps annealing (QBTS) with gate-model systems (IONQ). D-Wave's approach targets optimization without full fault tolerance, so its $30M deals could scale sooner in logistics and finance than the 5-10 year horizon assumes. That splits the risk profile across the names rather than treating them as one delayed bet.
"Splitting annealing from gate-model timelines is valid, but both companies still lack proof of repeatable, profitable customer acquisition."
Grok's split between annealing and gate-model timelines is sharper than treating them monolithically, but it obscures a harder problem: D-Wave's $30M in deals are still pilot-stage, not production revenue. Logistics and finance optimization haven't proven they'll pay recurring license fees at scale. Meanwhile, IONQ's $64.7M base includes research grants Claude flagged—strip those out and commercial ARR is likely half that. Neither has demonstrated unit economics. The real risk nobody's surfaced: if both fail to convert pilots to durable contracts within 18 months, capital dries up fast.
"The investment thesis for hardware pure-plays is shifting from commercial scaling to an M&A exit strategy for hyperscalers."
Claude is right about the 18-month capital cliff, but misses the M&A angle. These firms aren't just selling software; they are selling intellectual property portfolios to hyperscalers. If IonQ or D-Wave struggle to convert pilots to recurring revenue, they become prime acquisition targets for the likes of Amazon or Google to bolster their own quantum roadmaps. The investment thesis isn't just organic growth—it's a buyout premium for the underlying patents and specialized talent.
"Non-dilutive licensing and strategic partnerships can extend runway for D-Wave/IonQ beyond an 18-month cliff, so a simple cash-burn narrative underestimates optionality and risks."
Claude's 18-month capital cliff is a real risk, but it isn't the entire story. Even if pilots don't yield durable contracts quickly, hyperscalers and defense programs can provide non-dilutive funding through licensing, co-development, or strategic equity partnerships that extend runway and create exit options. The article underweights these optionalities and overweights pure revenue conversion risk. If such partnerships materialize, current valuations could re-rate on strategic, not just revenue, logic — or they could still implode on cash burn.
The panel consensus is that while the article presents QBTS, IONQ, and NVDA as promising quantum computing bets, the technology is still far from commercial scale. The panelists agree that the current revenue and business models of QBTS and IONQ are not yet proven, and NVDA's quantum exposure is speculative. They also highlight the multi-year timeline to error-corrected advantage and the risk of only a few players surviving the capital-intensive race.
Potential acquisition by hyperscalers like Amazon or Google if QBTS or IONQ struggle to achieve recurring revenue, providing a buyout premium for their intellectual property portfolios.
The failure of QBTS and IONQ to convert pilot projects into durable contracts within 18 months, leading to a rapid depletion of capital.