Quantum computing is often seen as the future of computing, promising breakthroughs in everything from drug discovery to artificial intelligence. But there’s a big question that few people ask: how much energy does quantum computing use? And more importantly, how sustainable is it?
1. Quantum computers require cryogenic cooling, consuming up to 25 kW per dilution refrigerator.
Superconducting quantum computers, the most common type today, require extremely low temperatures—colder than outer space—to function. This is achieved using dilution refrigerators, which are complex machines that cool quantum processors to near absolute zero.
A single dilution refrigerator can consume up to 25 kW of power, which is a significant amount when considering energy efficiency. To put that into perspective, this is equivalent to running 25 high-powered air conditioners continuously.
Actionable Insight:
For quantum computing to be sustainable, cooling technology must become more energy-efficient. Researchers are working on new refrigeration techniques, such as cryogen-free cooling and alternative materials that require less extreme temperatures. Companies looking to use quantum computing should factor in the long-term energy costs of cooling.
2. A superconducting quantum processor operates at around 15 millikelvin, requiring substantial cooling energy.
The core of a superconducting quantum computer needs to be at about 15 millikelvin—a temperature so low that even the tiniest vibrations can generate heat and disrupt the system. Maintaining this extreme cold requires constant refrigeration.
This cooling process uses a cascade system, where several cooling stages progressively lower the temperature. Each of these steps demands energy, and inefficiencies at any stage result in higher power usage.
Actionable Insight:
More sustainable cooling methods could include new materials that remain superconducting at higher temperatures. Research into alternative qubit architectures, such as photonic or topological qubits, could eliminate the need for extreme cooling altogether.
3. A single dilution refrigerator can consume as much power as 10 average U.S. households.
The average U.S. household uses about 2-3 kW of power at any given time. That means one dilution refrigerator consumes as much power as 10 homes running continuously.
This raises concerns about the environmental impact of quantum computing. If quantum computers scale up significantly, their energy consumption could become a serious challenge.
Actionable Insight:
Businesses investing in quantum technology should factor in energy costs. Data centers using quantum computers must integrate renewable energy sources to minimize environmental impact.
4. Quantum processors themselves consume negligible power—on the order of milliwatts.
Despite the high energy cost of cooling, quantum processors themselves consume almost no power. A single qubit operates on just milliwatts of energy, far less than traditional transistors in a classical computer.
This suggests that if cooling efficiency improves, quantum computing could eventually be more energy-efficient than classical computing for complex problems.
Actionable Insight:
Optimization should focus on reducing supporting energy demands. Companies developing quantum computers should explore hybrid cooling solutions that minimize the power needed while maintaining qubit stability.
5. Control electronics for quantum computers use kilowatts of energy per system.
While qubits require very little power, the electronics that control them do not. These include microwave signal generators, error correction processors, and readout systems. Together, they consume several kilowatts per quantum computing system.
For large-scale quantum computers, this control infrastructure becomes a major bottleneck in energy efficiency.
Actionable Insight:
Developing low-power control electronics is critical. Researchers are exploring cryogenic electronics that work at low temperatures, reducing the need for high-powered classical controllers.
6. IBM’s 127-qubit Eagle processor requires around 10 kW just for control and readout electronics.
IBM’s 127-qubit Eagle processor is one of the most advanced quantum chips, but its support infrastructure requires 10 kW of power—just for control and readout.
This highlights a key issue: as quantum processors grow, the power required to manage them increases, potentially outweighing the efficiency gains of quantum computation.
Actionable Insight:
Efforts should focus on optimizing qubit connectivity and reducing error correction overhead. Smarter architectures that require fewer classical control components will lower energy demands.
7. Google’s Sycamore 53-qubit processor used around 26 kW for supporting infrastructure.
When Google achieved “quantum supremacy” with its 53-qubit Sycamore processor, the total energy consumption—including cooling and control systems—was approximately 26 kW.
This level of energy consumption is a concern because it suggests that even relatively small quantum computers consume as much power as multiple high-performance classical systems.
Actionable Insight:
Future quantum computing centers must integrate energy-efficient designs from the ground up. This includes better thermal management, optimized control electronics, and renewable energy integration.
8. Quantum computers require thousands of classical processors for error correction, adding to power usage.
Quantum computers are incredibly error-prone, meaning they rely on thousands of classical processors to perform error correction. These classical processors significantly increase the total power demand of a quantum system.
Error correction remains one of the biggest hurdles to scalable quantum computing.
Actionable Insight:
Research is moving toward more efficient error correction codes that require fewer classical resources. Advancements in quantum error correction could drastically reduce the energy footprint.
9. Classical supercomputers used to simulate quantum circuits can consume several megawatts of power.
Simulating a quantum computer using a classical system is extremely energy-intensive. Some supercomputers consume over 5 MW just to run quantum simulations.
This highlights why quantum computers could be more energy-efficient for certain calculations—if their overhead energy costs can be reduced.
Actionable Insight:
Investment should prioritize applications where quantum computing is significantly more efficient than classical alternatives, reducing overall energy use.
10. The Frontier supercomputer, used for quantum simulations, consumes around 21 MW.
Frontier, one of the world’s fastest supercomputers, consumes a staggering 21 MW of power. It is often used to model quantum systems.
If quantum computers can achieve practical error correction, they could surpass supercomputers while using far less energy.
Actionable Insight:
The transition to practical quantum computing should prioritize replacing energy-hungry classical simulations with quantum alternatives where appropriate.
11. Quantum annealers (e.g., D-Wave) operate at substantially lower energy than gate-based quantum computers.
Not all quantum computers consume the same amount of energy. Quantum annealers, like those built by D-Wave, operate at much lower power levels compared to gate-based quantum computers like IBM’s or Google’s.
Unlike gate-based quantum computers, which require extensive control electronics and high-power cryogenic systems, quantum annealers function at higher temperatures and use significantly less supporting infrastructure. This makes them more energy-efficient for certain types of problems, particularly optimization tasks.
Actionable Insight:
For businesses exploring quantum computing, quantum annealers can be a cost-effective and sustainable starting point. They consume less energy and are already being used in industries like logistics, finance, and pharmaceuticals. If energy efficiency is a concern, annealers might be a better choice than fully error-corrected quantum computers.
12. A D-Wave Advantage system uses around 25 kW, including cooling.
D-Wave’s latest quantum annealer, the Advantage system, runs on just 25 kW of power—including refrigeration. This is comparable to a single dilution refrigerator used in gate-based quantum computers, meaning that the total energy demand of an annealer is significantly lower than a general-purpose quantum processor.
This difference is because annealers do not need complex microwave control electronics and operate at slightly higher temperatures, reducing cooling needs.
Actionable Insight:
If sustainability is a key concern, businesses should consider quantum annealers for specific applications instead of more power-hungry universal quantum computers. While they are not as versatile, they are already providing practical advantages in real-world problem-solving.
13. Classical data centers consume about 200 terawatt-hours per year, much higher than today’s quantum systems.
Data centers worldwide consume approximately 200 terawatt-hours (TWh) per year—about 1% of global electricity use. By comparison, today’s quantum computers consume only a fraction of that.
This might make quantum computing seem energy-efficient, but the comparison isn’t straightforward. Quantum computers are still in their infancy, and as they scale up, their energy demands could increase rapidly.
Actionable Insight:
The real energy benefit of quantum computing will come from its ability to solve problems faster than classical computers. If a quantum computer can perform a task in minutes that would take a data center weeks, the overall energy savings could be significant.
14. Error correction in fault-tolerant quantum computing could increase power consumption 10x.
One of the biggest challenges in quantum computing is error correction. Unlike classical computers, quantum computers are extremely fragile, and even minor disturbances can cause computation errors.
To fix this, quantum computers use error correction codes—which require many more physical qubits to create a single logical qubit. This process increases computational overhead and power consumption by a factor of 10 or more.
Actionable Insight:
The future of sustainable quantum computing depends on developing better error correction techniques that require fewer redundant qubits. Businesses should track advances in quantum error correction before making long-term energy investment decisions.
15. Quantum systems need hours or even days to stabilize after cooling, adding energy overhead.
A quantum computer doesn’t just turn on instantly like a classical one. Once a dilution refrigerator is started, it can take hours to days for the system to reach operational temperatures. This waiting period wastes energy before computation even begins.
Moreover, the system needs to be kept cold even when not in use, leading to continuous energy consumption.
Actionable Insight:
Future improvements in fast-start cooling technology and more efficient idle-state refrigeration could drastically reduce this overhead. Until then, quantum computing should be scheduled for batch processing to minimize wasted cooling energy.
16. The energy cost per quantum operation is much lower than classical bits but offset by infrastructure needs.
At an individual level, a quantum operation (gate) consumes far less energy than a classical transistor operation. However, this advantage is currently overshadowed by the enormous energy cost of cooling, control electronics, and error correction.
If these supporting systems become more efficient, quantum computers could leap ahead of classical computers in energy efficiency.
Actionable Insight:
Quantum hardware companies should focus on reducing infrastructure energy costs rather than just improving computation speed. Businesses adopting quantum technology should prioritize energy-efficient setups.
17. The heat generated by control electronics limits the scalability of superconducting qubits.
The more qubits you add, the more control electronics you need. These electronics generate heat, which is a major problem in a system that needs to stay near absolute zero.
This creates a paradox: to scale up quantum computers, more heat needs to be managed, but cooling capacity is already a bottleneck.
Actionable Insight:
One solution being explored is cryogenic classical processors, which operate at lower temperatures and generate less heat. Investing in hybrid cooling solutions can help mitigate this challenge.
18. Photonic quantum computing may significantly reduce cooling energy needs.
Photonic quantum computers use light instead of superconducting circuits. This means they don’t require extreme cooling and could be far more energy-efficient.
Companies like PsiQuantum are working on scalable photonic quantum computers that could revolutionize energy consumption in quantum computing.
Actionable Insight:
Investors and businesses looking into quantum computing should keep an eye on photonic-based systems as a more sustainable alternative to superconducting qubits.
19. Neutral atom quantum computers operate at room temperature, reducing energy use.
Another promising approach is neutral atom quantum computing, where individual atoms are manipulated using lasers. These systems work at room temperature, eliminating the need for extreme cooling.
Companies like ColdQuanta are developing neutral atom quantum computers that could operate with far less energy than traditional superconducting systems.
Actionable Insight:
If you’re considering adopting quantum computing, explore room-temperature quantum technologies as they could offer lower long-term operational costs.
20. Trapped ion quantum systems have higher per-qubit power requirements due to laser cooling.
Trapped ion quantum computers use lasers to manipulate qubits. While they don’t require dilution refrigerators, they consume more power per qubit due to the energy-intensive laser systems.
However, they are more stable and require less error correction, which may make them more energy-efficient overall in the long run.
Actionable Insight:
For companies looking at quantum computing solutions, trapped ion systems may be a good choice for applications where error correction overhead is a concern.
21. IBM’s roadmap aims to improve energy efficiency per qubit with modular architectures.
IBM, one of the leading players in quantum computing, has a clear roadmap for making quantum computing more energy-efficient. Their focus is on modular architectures, where multiple quantum processors are connected together to form a larger, more powerful system.
Why does this matter? Today, quantum processors require massive amounts of cooling and classical control systems to function. By designing modular architectures, IBM aims to reduce redundant energy use, making it possible to scale quantum computers without an exponential increase in power consumption.
Actionable Insight:
Businesses interested in quantum computing should pay attention to IBM’s developments in modular architectures. As they refine this approach, quantum computing could become far less energy-intensive while delivering greater computational power.
22. Google’s roadmap includes reducing cooling power needs by 50% through better refrigeration.
Google’s quantum research team is also working hard to reduce energy consumption. One of their primary goals is to cut cooling power requirements by 50% using advanced refrigeration techniques.
One of their strategies is to develop more efficient cryogenic cooling systems that use less energy while maintaining the ultra-low temperatures needed for superconducting qubits.
Google is also exploring ways to minimize the heat output of control electronics, which would further reduce the need for excessive cooling.
Actionable Insight:
If Google successfully achieves this 50% reduction, it will be a major breakthrough in quantum computing sustainability. Companies looking to adopt quantum computing should stay updated on these advancements, as they could lead to lower operating costs in the near future.
23. Quantum computing energy use scales super-linearly with qubit count.
A big challenge with quantum computing is that energy consumption does not scale linearly with the number of qubits—it scales super-linearly. This means that doubling the number of qubits could more than double the energy consumption.
This happens because:
- More qubits require more control electronics, which generates additional heat.
- Error correction becomes more complex, requiring additional classical processors to manage it.
- Cooling requirements increase due to the added computational load.
Actionable Insight:
To prevent energy costs from spiraling out of control, companies and researchers need to focus on more energy-efficient qubit architectures, better error correction techniques, and low-power classical processors for control systems.
24. The energy efficiency of quantum computing improves when problem complexity justifies the cost.
Quantum computers aren’t designed to replace all classical computers. Instead, they shine in solving highly complex problems that would take classical supercomputers an impractical amount of time and energy.
For example, if a quantum computer can solve a problem in minutes that would take a classical system months, then its energy consumption is justified. However, if the problem can be solved classically with reasonable efficiency, then using a quantum computer may not be sustainable.
Actionable Insight:
Businesses should carefully evaluate which problems are best suited for quantum computing. If a task can be done efficiently with a classical system, it’s likely the more energy-efficient choice.
25. Superconducting qubit-based quantum computers require helium-3, a rare and energy-intensive resource.
One lesser-known challenge in quantum computing is the reliance on helium-3, a rare isotope used in dilution refrigerators. Helium-3 is extremely scarce, and its extraction process is energy-intensive.
As quantum computers scale, the demand for helium-3 will increase, potentially creating a supply-chain issue and further sustainability concerns.
Actionable Insight:
To make quantum computing more sustainable, researchers are looking into alternative cooling methods that don’t rely on helium-3. Companies investing in quantum technology should monitor these developments and seek helium-free quantum systems in the future.
26. Future cryogenic solutions may use liquid nitrogen cooling, reducing power needs.
A promising alternative to helium-3 cooling is liquid nitrogen-based cooling. Liquid nitrogen is much cheaper and more abundant than helium-3, and it can still reach low enough temperatures for some quantum applications.
Some researchers are exploring high-temperature superconductors that would allow quantum computers to operate at liquid nitrogen temperatures instead of requiring expensive helium-3 cooling.
Actionable Insight:
As liquid nitrogen-based cooling technology advances, it could drastically cut quantum computing’s environmental footprint. Businesses investing in quantum hardware should explore solutions that leverage this cooling method.
27. Quantum supremacy experiments used millions of times more energy than classical alternatives.
When Google demonstrated quantum supremacy in 2019 with its Sycamore processor, the experiment used an enormous amount of energy. In fact, it took millions of times more energy than running the same problem on a classical computer.
This experiment was designed to showcase a theoretical advantage, not an energy-efficient application. But it highlights an important issue—just because a quantum computer can outperform a classical one doesn’t mean it’s the greener option yet.
Actionable Insight:
The goal should not just be quantum supremacy but quantum advantage—where quantum computers solve real-world problems efficiently. Until then, businesses should be cautious about assuming quantum computing is always the more sustainable choice.
28. Quantum computing energy efficiency depends on algorithm suitability for quantum speedup.
Quantum computers aren’t universally faster than classical ones. Some algorithms see exponential speedup, while others do not perform any better than classical methods.
For example, Shor’s algorithm for factoring large numbers is highly efficient on a quantum computer, but many everyday computing tasks don’t benefit from quantum processing. If a problem doesn’t offer a significant speedup, then using a quantum computer wastes energy.
Actionable Insight:
Before adopting quantum computing, businesses should evaluate whether their use case is genuinely better suited for a quantum approach. If not, they might be better off sticking with classical computing for energy efficiency.
29. Government-funded quantum computing projects increasingly focus on sustainability.
Governments worldwide are investing heavily in quantum computing, and many of these projects are prioritizing energy-efficient designs.
For example, the U.S. Department of Energy is funding research into low-power quantum computing architectures, and Europe’s Quantum Flagship program is exploring sustainable quantum computing methods.
Actionable Insight:
Companies interested in sustainable quantum computing should explore government grants and partnerships that focus on energy-efficient solutions. Governments are eager to support projects that reduce the environmental impact of quantum technology.
30. Advances in room-temperature quantum computing could reduce total energy use by over 90%.
One of the most exciting areas of quantum research is room-temperature quantum computing. If successful, these systems would eliminate the need for massive cooling systems, potentially reducing energy use by over 90%.
Several companies, including Atom Computing and Microsoft, are working on room-temperature qubit technologies that could make quantum computing significantly more sustainable.
Actionable Insight:
Businesses looking to invest in quantum computing should keep an eye on room-temperature quantum technologies. If successful, they could revolutionize quantum computing sustainability, making it as energy-efficient as—or even more efficient than—classical computing.
wrapping it up
Quantum computing is at an exciting crossroads. It holds the potential to revolutionize fields like cryptography, materials science, drug discovery, and artificial intelligence. However, the energy challenge cannot be ignored.
While quantum processors themselves are incredibly efficient, the supporting infrastructure—cooling systems, control electronics, and error correction—creates significant energy overhead.
