D-Wave (QBTS): Commercializing Quantum Computing

Quantum computing is expected to revolutionize computational capacity, as this new form of computing differs radically from classical computing. Instead of processing binary outcomes (1 and 0), it can process  “quantum bits,” called qubits, where particle data is either 0 AND 1 at once, or 1, or 0.

This allows quantum computers to test massive numbers of possibilities at the same time, unlike regular computers that process tasks one step at a time. As a result, they can solve problems otherwise intractable with traditional binary, silicon-based computing.

However, creating the conditions where the qubits are stable enough to perform useful computation has been a real challenge.

One path is using superconducting materials (materials with no electrical resistance), but it only works at ultra-low temperatures. This is energy-consuming, expensive, and difficult to achieve.

Another option is to use so-called trapped-ion technology. Instead of superconducting chips, it uses individual charged atoms (ions) held in place by magnetic and electric fields in a vacuum chamber, controlled and measured using precise lasers.

In contrast to superconducting chips, this creates very stable systems, where quantum states last from seconds to minutes instead of microseconds. However, this is also a lot less powerful in terms of computational capacity, and networking quantum computers is a difficult task.

So far, most industry attention has focused on these two technologies, with tech giants like Google, IBM, and Microsoft (MSFT ) focusing on superconducting technology, and companies like Honeywell focusing on trapped-ion technology.

But a third path exists, which might be at the sweet spot between too low reliability and too slow calculations: quantum annealing.

One company in particular is the champion of this technology, and could become the leader in early applications of quantum computing in the real world: D-Wave

D-Wave Overview

D-Wave History

D-Wave was founded in 1999, much before any hype around quantum computing, when the Internet was still a new, booming technology. Its name refers to the earliest form of qubit the company used, D-Wave superconductors.

The company initially operated as an offshoot of the University of British Columbia, where it still has operations, alongside another site in Palo Alto, California, and soon a future new corporate headquarters and a key U.S. research and development (R&D) facility in Boca Raton, Florida.

In 2007, the company created the Orion Prototype, a prototype 16-qubit system which was the first public demonstration of a quantum processor.

The company made its first commercial sale in 2011, a 128-qubit processor sold to Lockheed Martin (LMT ). It later expanded its sales to NASA and Google, offering quantum computers with 500-2,000 qubits.

In 2020, the company shifted from selling only quantum computer hardware to also providing cloud access to quantum computing through its cloud-based Leap platform, alongside the Advantage system with 5,000 qubits.

This offer was focused on real-world optimization problems and industrial applications, instead of the more theoretical or experimental goals of most other quantum computing systems.

“This increase in qubit count and connectivity means that larger application problems can be solved directly on the quantum chip. Advantage QPUs can hold inputs that are on average 3 times larger than similarly-structured inputs held by 2000Q QPUs. Furthermore, application problems can be embedded more compactly onto Advantage QPUs (more compact embeddings are associated with better-quality solutions).”

These quantum computers were all based on quantum annealing, a method ideal for accumulating more qubits than trapped-ion computers and more reliable and easier to scale than superconducting quantum chips.

Since 2019, the company has also been expanding into gate-model processors, the “usual” superconducting quantum computing technology, complementary to the abilities of quantum annealing (see below for detailed explanations of both), leading the company to brand itself as “The World’s Only Dual-Platform Quantum Computing Company”.

Source: D-Wave

“While annealing quantum computing excels at optimization, materials simulation, and certain AI workloads, gate-model quantum computing is expected to advance applications such as quantum chemistry, molecular design, and next-generation energy storage.”

The company was publicly listed in 2022 via a SPAC merger on the New York Stock Exchange.

Lastly, D-Wave made a controversial “quantum supremacy” claim in 2025, declaring it was the first time anyone has successfully used quantum computing to solve a problem of scientific interest quicker than with classical computers.

“They studied a specific problem in which the temperature of the material starts at absolute zero, and quantum fluctuations let it transition from one state to another. They estimate that their machine achieved the result exponentially faster than any classical calculation.”

While some other scientists’ teams claim they could or have done similar with a classical computer, this was a good illustration that D-Wave quantum annealing technology is quickly becoming a viable competitor to existing supercomputers.

“These are results of 25 years of hardware development and research at D-Wave,”

Mohammad Amin – Senior physicist at D-Wave.

D-Wave By The Numbers

Despite the beginning of its commercial success and cloud computing offering, D-Wave should still be seen as a technology startup first, with a heavy focus on R&D, as it has only 385 employees, with roughly 20% to 25% of the total staff holding doctorates.

The company holds as many as 290 granted US patents and a total of 800+ patents granted and pending globally. This puts D-Wave as #3 in terms of quantum patent portfolio globally, sitting just behind legacy giants IBM and Alphabet (GOOG ) (Google) in total patent publications.  Over 60% of D-Wave’s patents cover the core physics of quantum processors, chip fabrication, and advanced cryogenic infrastructure.

D-Wave counts more than 100 enterprise partners, with a focus on sectors like finance, industrial companies (chemicals, steel, construction, etc.), telecommunications, etc.

Source: D-Wave

Already, half of D-Wave’s customers are commercial enterprises, with 65% of revenue from commercial customers, and 45% of that revenue from Forbes Global 2000 customers. These collaborations with enterprise customers are not just academic, but are already used routinely for specific use cases.

For example, D-Wave tools are already used by AT&T (T ) to reduce the processing time for a network optimization workload from approximately one hour to less than 15 seconds. Another customer is using it to optimize scheduling:

“The auto-scheduler is saving both time and effort, trimming what was once an 80-hour task to just 15 hours each week, an 80%-time savings.”

Pattison Food Group

Or CaixaBank (48CA.DE ), a leading bank in Spain, used D-Wave to optimize the design of a portfolio for high-speed trading. What normally took the bank several hours of compute time was reduced to just minutes via quantum computing technology.

“The quantum hybrid applications have significantly decreased compute time to solve complex financial problems, improving investment portfolio optimization, increasing a bond portfolio internal rate of return (IRR), and minimizing the capital needed for hedging operations, as a result of their collaboration.”

The D-Wave Advantage2, released in 2025, is displaying 4,500+ active qubits. This is a slight decrease compared to Advantage1’s 5,000 qubits, marking a strategic trade-off made to significantly enhance the overall performance, quality, and fidelity of the processor.

One of the main changes is the switch from a 20-way qubit connectivity, up from the previous 15-way connectivity, which lets complex optimization problems be mapped more directly onto the chip. Another improvement in Advantage2 is that Quantum coherence times have doubled, and noise has been reduced by 75%, resulting overall in a 20x to 25,000x speedup on difficult optimization and materials science problems.

D-Wave is planning to launch the Advantage3, a system featuring 20,000 qubits by 2029, scaling further to 100,000 qubits by 2031.

Source: D-Wave

D-Wave’s Technologies

D-Wave’s Quantum Annealing Technology

The essential physics behind D-Wave technology is that quantum annealing processors naturally return low-energy solutions. So if you can model a real-life problem and frame it as an energy minimization problem, a quantum computer can spontaneously find the best option to reach a minimum energy state, which translates through the model into a direct answer to the kind of computation required, for example, by scheduling challenges or pathfinding questions (optimization problems).

Another category of problem that quantum annealing technology can solve is sampling problems. In this case, a general view of various low-energy conditions can help orient a machine learning model in the right direction.

“Sampling from many low-energy states and characterizing the shape of the energy landscape is useful for machine learning problems where you want to build a probabilistic model of reality.”

An advantage here is that probabilistic models explicitly handle uncertainty by accounting for gaps in knowledge and errors in data sources.

“For example, when training on the famous MNIST dataset of handwritten digits, such a model can generate images resembling handwritten digits that are consistent with the training set.”

In more detail, the way quantum annealing works is by coupling together individual qubits, so they can influence each other. For each additional qubit pair that is entangled, the capacity of the computer increases exponentially, while in classical computing adding more capacity only adds it, not multiplies it.

“Two qubits have four possible states over which to define an energy landscape; three qubits have eight. Each additional qubit doubles the number of states over which you can define the energy landscape”

This is why an increase in connectivity and stability of the qubits is as significant as the total count, as more stable qubits are usable for more calculations, and more connections increase the computing power exponentially.

Which is why D-Wave considers that quantum annealing is the perfect option for real-world applications:

• Annealing is more stable and reliable than other superconducting quantum computing methods, and easier to achieve, making it more scalable to thousands or tens of thousands of functional qubits.
• Annealing qubits are quicker than qubits from trapped-ion technology, allowing them to perform complex calculations more quickly, and making them competitive versus classical supercomputers.

Overall, this makes annealing more limited in terms of applications, mostly optimization and search problems, but also gives it an efficiency and an early mover advantage over more universal quantum computers.

D-Wave’s Gate-Model Technology

When describing “superconducting quantum computing” technology, what people usually mean is gate-model technology, where a controlled sequence of logic gates is used, in a way more similar to classical forms of computing.

This is inherently a more universal technology that can be applied to more problems than the limited set addressed by annealing technology. This is the favored approach by companies like IBM, Google, Rigetti, etc.

More recently, D-Wave accelerated its expansion into this field with the acquisition of Quantum Circuits Inc. (QCI) in an all-stock deal valued at up to $550M.

From an investor’s point of view, this can be a little confusing:

• On one hand, this turns D-Wave from a “one trick pony” into both a company with existing applications and customers, and a generalist quantum computing company with a larger addressable market in the long run.
• On the other hand, this somewhat proves that annealing alone might be too limited, and puts into question whether D-Wave can compete directly with giants like IBM or Google.

So the question is not so much if a gate-based model will be useful for D-Wave, but if it will bring it a competitive advantage.

One positive aspect is that the experience and patents in cryogenic technology used for annealing transfer well to gate-model chips, reducing the required investment. Notably, D-Wave’s on-chip cryogenic control reduces the massive bundle of wiring inside a quantum fridge, and could prove a unique competitive advantage from a decade of having to deal with the industry’s largest quantum computers by qubit count.

“Building systems with tens of thousands of superconducting qubits forced D-Wave to solve the wiring bottleneck before anyone else needed to. Now that gate-model systems are approaching scales where wiring becomes the limiting factor, D-Wave has a technology that competitors must develop from scratch or license.

Sal Magnone”

Another positive is that Leap Quantum Cloud is already familiar to D-Wave customers, which often use it daily, and they can slowly, over time, switch to gate-model tech for other applications and as the technology matures. Getting started with annealing is also easier for customers, as it uses Python tools like the D-Wave Ocean SDK, instead of complex circuit assembly (e.g., Qiskit).

Another potential key technology advantage is dual-rail qubits that handle error detection natively at the chip level, also obtained in the Quantum Circuits Inc. acquisition. The idea is that instead of building massive systems and correcting errors later via software, dual-rail qubits ensure that errors raise a physical flag the moment they happen.

Source: D-Wave

As error reduction and correction are a major bottleneck in quantum technology, this could be very important for the future of the company and the quick scaling of its computer models.

“As part of D-Wave’s broader dual-platform strategy, gate-model technology will complement our production-ready annealing systems. This will expand the range of computationally complex problems organizations can explore as quantum computing matures, including areas such as quantum chemistry, materials science, and AI.”

Dr. Alan Baratz – CEO of D-Wave

Still, D-Wave’s gate model is, for now, quite smaller than its competitors’. It currently only produces a 17-qubit system. It aims to produce a 49-qubit system in 2027, and 181 qubits in 2028. At that rate, the company expects that the parallel reduction in error can create the first fault-tolerant algorithm in 2030 and the first real-world applications by 2032.

Source: D-Wave

D-Wave’s Tech Applications

As mentioned, one key application of D-Wave quantum annealing computing is in scheduling, either production or delivery and logistics. As supply chains become increasingly complex, handling thousands of parts or parcels and optimizing ordering, transport, and delivery can become an unsolvable problem with traditional methods. And considering factors like vehicle capacity, time constraints, ever-changing traffic conditions, and sustainability practices adds further complexity.

Another form of scheduling that can be solved more efficiently with quantum annealing is workforce scheduling. This can let companies handle employee scheduling more efficiently while taking into account factors like shift preferences, changing regulations, and sick leave.

Lastly, another application is resource management, with the term “resource” taken with a wide meaning: materials, funds, and personnel. The same method is, for example, applied by telecom companies for bandwidth resources on mobile networks during periods of heavy use.

“It resolves resource conflicts by managing competing demands across departments, balances workloads to prevent bottlenecks, and aligns assets with critical projects for stronger impact. This approach can reduce waste, elevate productivity, and help achieve a sustainable competitive advantage.”

Source: D-Wave

D-Wave’s Investor Takeaway

Investors in D-Wave should be aware that quantum computing is an emergent and very competitive field.

Virtually every quantum company will see itself as having picked the right technological path, either because it is more reliable (ion-trapped), more market-ready (annealing), or has greater potential for scalability (superconducting).

Still, having its quantum annealing computers being deployed at increasing scale to already solve real-life problems in biotech, telecom, or banking is an impressive feat, and D-Wave might be a surprise winner in the field, while discussions are often focused on other companies using different quantum computing technologies.

It is also possible that D-Wave’s unique experience in building large, multi-thousand-qubit commercial quantum computers will pay off in other ways with “usual” superconducting designs.

Notably, it gave the company unique patents in cryogenic control and made it able to handle error detection natively at the chip level, something that none of the bigger players can do with their own version of gate-model technology.

At the end of 2024, the company looked like it was in trouble and might run out of money before it achieved commercialization at scale. With an ongoing flow of new deals with major enterprises for annealing quantum computing (including through the cloud), and unique IP in gate-model technology, the situation of the company seems very different today.

At the same time, with revenues of only $1.9M in Q2 2026, most of the current multi-billion dollar valuation is supported by the company’s potential, and diversifying risk across multiple quantum computing technologies may be the most prudent approach in a field that is evolving very quickly.

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