Even as global markets reel from geopolitical tensions and a fresh wave of volatility, a handful of quantum technology companies are pushing ahead with public listings this year.

They are determined to tap fresh capital and accelerate the long-promised shift from laboratory curiosity to real-world applications, according to a CNBC report.

The latest example came Friday when Toronto-based Xanadu Quantum Technologies, a pioneer in photonic quantum computing and a partner of chipmaker Nvidia, began trading on both the Nasdaq and Toronto Stock Exchange following a merger with blank-check company Crane Harbor Acquisition Corp. Shares opened rocky but rallied to close up about 15 percent in New York trading at around $11.50, though they gave back some ground in after-hours action.

Xanadu’s debut followed closely on the heels of Singapore’s Horizon Quantum Computing, which started trading on Nasdaq under ticker HQ after merging with dMY Squared Technology Group and raising roughly $120 million. Earlier in February, neutral-atom specialist Infleqtion became the first company focused on that approach to list publicly via a SPAC deal with Churchill Capital, pulling in more than $550 million.

These moves echo the path blazed by IonQ back in 2021, when dMY Technology Group took the pure-play quantum computing firm public. SPACs, shell companies that raise money through an IPO and then merge with a private target, have emerged as the favored shortcut for quantum startups seeking faster access to public markets with lighter regulatory hurdles than a traditional IPO.

Markets remain jittery over the ongoing U.S.-Israeli conflict with Iran, oil price spikes, and broader economic uncertainty — precisely the sort of environment that usually punishes speculative, long-horizon bets like quantum computing. Xanadu’s shares slipped more than 10 percent after hours Friday, Horizon Quantum has shed around 18 percent since its debut, and Infleqtion’s stock has plunged over 30 percent since mid-February.

Yet company executives argue the window is actually ideal. “It’s an interesting time to be entering the public markets, of course, with everything happening in the world,” Horizon Quantum founder and CEO Dr. Joe Fitzsimons told CNBC. “But for quantum computing, it’s actually a very ideal time to be coming out. We’re really starting to hit something of an inflection point.”

That inflection stems from a string of tangible scientific advances over the past 18–24 months. Researchers have demonstrated meaningful progress in quantum error correction — the critical technique for protecting fragile quantum information from noise and decoherence. Milestones include higher qubit counts, longer coherence times, and early signs that logical qubits (error-protected units of quantum information) can outperform raw physical ones in real computations.

Industry observers point to demonstrations of up to dozens of logical qubits with error rates low enough to show “beyond break-even” performance. Bain & Company partner Velu Sinha noted that practical quantum advantage, where quantum machines solve useful problems faster or better than classical supercomputers, could emerge around 100 logical qubits by 2028–2029.

Commercially transformative applications in drug discovery, materials science, logistics optimization, or financial modeling will likely require 1,000 to 10,000 logical qubits, a threshold many expect in the mid-2030s.

“The narrative has shifted from science project to commercial trajectory,” Sinha said. “Quantum is one of a small number of technology categories investors view as structurally inevitable.”

At full maturity, the addressable market could reach $100–250 billion, giving patient capital reason to look past near-term volatility.

Early revenue pathways are already appearing. Horizon Quantum has concentrated on software tools that bridge classical and quantum systems, allowing developers to prepare code that can run on future hardware while generating income today. The company plans to expand its research team and roll out an early version of its platform to select users later this year.

Xanadu, which uses photons (particles of light) for its qubits, has developed cloud-based platforms where developers can experiment with quantum algorithms on existing hardware. The firm has set an ambitious goal of helping deliver one of the world’s first practical quantum data centers by 2030 and boasts strong engagement from partners in automotive, aerospace, and finance.

Infleqtion’s CEO Matthew Kinsella emphasized that neutral-atom technology is moving from pure scientific progress toward commercial relevance, particularly in quantum sensing and networking alongside computing.

“Going public gives us the capital to accelerate commercialization and invest behind the markets where we already see customer demand,” he said. “We think commercialization will happen in stages.”

Governments have long bankrolled the heavy lifting in quantum R&D, with the U.S., China, and the European Union each committing billions to secure strategic edges in computing power and cybersecurity. National labs and universities remain central. But the current wave of listings signals a clear pivot: private companies are now chasing market traction, even if widespread consumer-facing quantum devices remain decades away.

As Counterpoint Research director Marc Einstein put it, quantum computers could one day perform trillions of operations instantaneously, revolutionizing fields from cryptography to complex simulations. Large organizations are far more likely to own or access the hardware as a service in the coming years than individuals will ever have desktop quantum machines.

For now, these newly public quantum firms must prove they can convert scientific momentum into sustainable revenue while navigating the unforgiving realities of public markets. The road from lab breakthrough to broad commercialization is still long and capital-intensive. But with error correction improving, qubit scales rising, and real customer interest emerging in optimization and simulation, the sector’s leaders are betting that going public is the best way to fund the next leg of the journey.

Space-compute startup Starcloud has vaulted into unicorn territory, securing a $1.1 billion valuation in one of the fastest climbs from Y Combinator demo day to billion-dollar status.

The company’s Series A round, led by Benchmark and EQT Ventures, raised $170 million and brought total funding to $200 million, according to the company and investors. The fundraise comes just 17 months after its YC debut, underscoring the surging investor appetite for infrastructure plays tied to the artificial intelligence boom.

The enthusiasm has remarkably been sustained by a bold thesis to move power-hungry AI data centers off Earth and into orbit.

As hyperscalers race to build capacity for generative AI workloads, terrestrial data center expansion is increasingly constrained by power shortages, land scarcity, water use concerns, and regulatory bottlenecks. Starcloud is pitching orbit as a solution, where near-continuous solar power and the vacuum of space could, in theory, transform the economics of compute.

The company has already moved beyond concept.

In November 2025, Starcloud launched its first satellite carrying an Nvidia H100 GPU, becoming one of the first companies to deploy a state-of-the-art terrestrial AI chip in orbit. The satellite was used to perform inference and early AI model training tasks in space, a milestone that helped validate the technical premise behind orbital computing.

“An H100 is probably not the best chip for space, to be honest, but the reason we did it is we wanted to prove that we could run state of the art terrestrial chips in space,” he told TechCrunch.

Later this year, Starcloud plans to launch a second, more advanced spacecraft equipped with multiple GPUs, including an Nvidia Blackwell chip, an Amazon Web Services server blade, and even a bitcoin-mining computer.

That second mission is designed less as a demonstration and more as an engineering testbed, particularly for thermal management and power systems. Cooling remains one of the most difficult problems in orbital computing because high-performance chips generate significant heat and cannot rely on conventional air-based cooling systems.

Chief executive Philip Johnston says the next-generation spacecraft will carry what is expected to be the largest deployable radiator yet flown on a privately owned satellite, a critical step in making space-based computing viable at scale.

The longer-term ambition is far larger.

Starcloud is developing Starcloud 3, a three-ton, 200-kilowatt orbital data center spacecraft intended for deployment via SpaceX’s Starship system. The design is meant to fit the launch company’s “pez dispenser” deployment architecture originally built for Starlink satellites.

If launch costs fall to roughly $500 per kilogram, Johnston believes the platform could deliver electricity costs near five cents per kilowatt-hour, placing it in direct competition with land-based data centers.

That assumption, however, rests heavily on Starship becoming commercially operational by 2028 or 2029. This is where the investment case becomes more speculative.

Starship has yet to begin routine commercial flights, and many analysts believe the high-frequency launch cadence required to make orbital data centers economically viable may not emerge until the 2030s. Until then, the cost of lofting powerful compute hardware into orbit remains a significant barrier.

Johnston acknowledges as much, saying the company will continue deploying smaller systems on SpaceX’s Falcon 9 if Starship timelines slip.

“If it ends up being delayed, we’ll just carry on launching the smaller versions on Falcon 9,” Johnston said. “We’re not going to be competitive on energy costs until Starship is flying frequently.”

The economics also highlight how early this market remains. While Starcloud’s ambitions include an 88,000-satellite compute constellation, the entire global installed base of advanced GPUs in orbit is still measured in the dozens. By contrast, Nvidia is estimated to have shipped nearly four million advanced GPUs to terrestrial hyperscalers in 2025 alone.

The gap is even starker in power terms.

SpaceX’s Starlink constellation, currently the world’s largest satellite network with roughly 10,000 spacecraft, is estimated to generate around 200 megawatts of energy. On Earth, more than 25 gigawatts of data-center capacity are under construction in the United States alone.

This makes Starcloud less a direct competitor to terrestrial hyperscalers today and more a strategic infrastructure bet on where AI computing may go next.

Its near-term business model reflects that reality.

Rather than immediately replacing ground-based cloud services, the company is focused first on selling processing power to other spacecraft operators. One example already in use is the processing of Earth observation data from Capella Space’s radar satellites.

In the longer term, Starcloud hopes to position itself as an energy and compute infrastructure provider to hyperscalers seeking overflow or distributed AI workloads.

Competition is intensifying.

Alongside Starcloud, companies such as Aethero, Aetherflux, and Google’s Project Suncatcher are exploring adjacent orbital infrastructure models. Meanwhile, SpaceX itself has reportedly sought regulatory approval for a million-satellite distributed compute network, potentially making it the most formidable rival in the field.

That looming presence is the elephant in the room.

Still, Johnston argues the two companies are addressing different markets, with SpaceX likely prioritizing internal workloads tied to xAI’s Grok and Tesla systems, while Starcloud positions itself as an independent infrastructure player.

“They are building for a slightly different use case than us,” he told TechCrunch. “They’re mainly planning on serving Grok and Tesla workloads. It may be at some point that they offer a third party cloud service, but what I think they are unlikely to do is what we’re doing [as] an energy and infrastructure player.”

Investors are betting that if launch costs collapse and orbital compute becomes technically scalable, Starcloud could sit at the intersection of two of the decade’s biggest themes, space infrastructure and AI.