Quantum as a Service: An Overview

Why QaaS?

While quantum computing is no longer purely an academic endeavor, it remains far from being an end-user technology. The costs and scientific expertise required not only to design and build a full-scale quantum computer, but even to operate and maintain one, are enormous. As a result, only a handful of organizations worldwide have the resources to develop such systems. However, this does not mean that smaller companies or individual researchers are excluded from using quantum computing resources; access is made possible through Quantum-as-a-Service (QaaS) platforms.

These systems follow the model of other cloud paradigms, such as SaaS or PaaS: users no longer need to own or maintain hardware locally; instead, computation is performed and managed centrally by the provider and accessed remotely. In the context of quantum computing, this model serves as a critical stepping stone toward achieving practical quantum advantage across different industries.

Hybrid Quantum-Classical Computing

A defining trend in the QaaS market is the move toward hybrid systems in which quantum processors and classical accelerators (CPUs and GPUs) operate seamlessly within the same computational environment. Practical quantum applications almost always rely on significant classical pre- and post-processing. Accordingly, next-generation QaaS platforms must tightly integrate QPUs with classical high-performance computing (HPC) resources, enabling coherent hybrid workflows and minimizing latency.

QaaS in Practice

• Remote cloud-based access to real quantum processors (QPUs) from providers such as IBM, Amazon (Braket), Microsoft (Azure Quantum), and a growing set of emerging challengers.

• High-fidelity simulators, often accelerated by GPUs, are used to develop and test algorithms before deployment on hardware. At present, full-scale simulation remains feasible because current quantum computers support only a limited number of logical qubits. In the near future, however, such simulators will no longer be able to fully emulate hardware behavior, although they will remain valuable for small-scale testing and debugging.

• Comprehensive SDKs and APIs that allow developers to integrate quantum circuits into larger applications, with hybrid quantum–classical execution models increasingly becoming the standard interface.

Service Types

Hyperscalers

While dedicated quantum startups dominate parts of the ecosystem, hyperscale cloud providers play an increasingly important and distinct role. Companies such as Amazon, Google, and Microsoft integrate quantum resources directly into their broader cloud infrastructures.

Their strategy follows a cross-service model: rather than offering quantum hardware as an isolated endpoint, hyperscalers provide a unified cloud environment capable of executing complete workflows end-to-end. This approach is essential, as most quantum applications depend heavily on classical computation. By enabling seamless access to CPUs, GPUs, and QPUs within a single platform, hyperscalers allow quantum tools to be deployed without redesigning existing software stacks.

Specialized Quantum Software Services

Parallel to the hyperscalers are specialized providers, typically companies that develop physical quantum hardware and offer direct cloud access to their systems.

Unlike the broad, integrated environments of hyperscalers, their value proposition lies in deep specialization in a particular quantum computing modality (such as annealing, photonics, or trapped ions), combined with highly tailored development tools. These providers often maintain their own open-source software libraries or web-based IDEs designed to reflect the unique physics of their hardware. This results in a more direct service model, where users access quantum resources straight from the source.

Quantum Aggregators and Middleware Providers

A third service category consists of quantum aggregators and middleware providers. These companies typically do not build quantum hardware themselves. Instead, they focus on software platforms that abstract over multiple hardware backends and provide hardware-agnostic development environments.

Their primary value lies in portability and interoperability: developers can design algorithms once and execute them across different quantum modalities and providers without rewriting code. Some aggregators also offer integrated access to hardware through partnerships, while others remain purely software-focused. This layer is particularly important for enterprises aiming to remain flexible in a rapidly evolving hardware landscape.

Access and Pricing

Accessing such quantum clouds is often simpler than expected. For example, using AWS Braket, users only need a standard cloud account and can execute quantum programs through familiar Python-based workflows.

Pricing generally follows a pay-as-you-go model. Simulators are available free of charge for one hour per month and cost $0.075 per minute thereafter. Access to real quantum hardware is offered either via on-demand execution at approximately $0.30 per task or through reserved access costing $2,500–$7,000 per hour, depending on the hardware.

Companies Offering Quantum Services

Hyperscalers and Integrated Cloud Platforms

These companies leverage their massive existing cloud infrastructure to provide a unified environment for both classical and quantum workflows.

• Amazon adopted an aggregated approach with AWS Bracket. Rather than a single hardware solution, it provides a single portal to access hardware from multiple third-party providers: IonQ, Rigetti, AQT, IQM, and QuEra. The quantum hardware, as well as a selection of simulators, are integrated into the existing cloud service, allowing for fast and easy integration and hybrid computation.

• IBM was one of the first companies to claim quantum supremacy and is a prominent player in the QaaS market. The IBM Quantum Platform lets researchers and developers access the company’s quantum hardware and services through a unified gateway. It is also important to mention Qiskit (Quantum Information Software Kit), an open-source, Python-based quantum computing framework developed by IBM, through which developers can run code on quantum computers and simulators—another critical component of the QaaS ecosystem.

• Google is another major player with its Quantum AI Lab. The lab was founded over a decade ago and has since contributed significantly to research in the field, including the company’s recent announcement, claiming to have proven quantum supremacy. Its platform provides researchers with access to processors and simulators.

Specialized Full-Stack Providers

Alongside the hyperscalers, many smaller players also offer hardware access. These companies, some of which are mentioned below, specialize in providing cloud access to their own unique hardware, instead of or alongside selling physical devices. They often offer unique modalities and full-stack development tools.

• D-Wave is one of the oldest players in the QC market, focusing on quantum annealing (a limited modality with no gates), mainly useful for optimization and logistics tasks. Their cloud service includes its own developer tools, OCEAN, as well as a web-based IDE.

• Quantinuum is a full-stack quantum company offering cloud access to software tools, while also providing quantum hardware as a service through Helios.

• Xanadu offers cloud access to several photonic quantum computers and maintains popular open-source software libraries like PennyLane for quantum machine learning and Strawberry Fields for designing photonic quantum circuits.

• Alpine Quantum Technologies demonstrates the unique scalability of trapped-ion quantum computers that operate at room temperature in a normal office environment.

Quantum Aggregators

Lastly, certain smaller companies adopted a middleman approach. These companies do not develop their own hardware, but rather focus solely on software services. Some of them also offer integrated hardware access, while others only provide a hardware-agnostic framework for quantum software.

• QCWare provides quantum machine learning and quantum chemistry algorithms, with access to multiple hardware backends through its Forge platform.

• Terra Quantum combines hardware-agnostic hybrid quantum algorithms with its own cloud infrastructure, focusing on industry applications and quantum-secure communication such as QKD.

• Scaleway offers a cloud ecosystem bridging classical simulators and quantum hardware, providing GPU-powered emulators (“digital twins”) and access to multiple hardware providers.

“The Catch” - Quantum Hardware Availability

The core promise of Quantum-as-a-Service is remote access to real quantum hardware. In practice, however, this promise is only partially fulfilled today. Unlike classical cloud computing, where hardware is abundant, reliable, and instantly available, quantum hardware remains scarce and difficult to operate at scale.

Access to quantum processors is often limited by queue times, maintenance periods, and unpredictable availability, as quantum devices require frequent calibration and operate only during specific time windows, which makes the shared, on-demand cloud model far more challenging than in classical computing. As a result, users cannot reliably expect immediate execution or consistent performance when submitting jobs to real quantum hardware.

In contrast, cloud-based quantum software and simulators behave much more like traditional cloud services. They run on classical infrastructure, have negligible waiting times, and are consistently available. Because current quantum computers are still small, error-prone, and can often be simulated efficiently, most practical development today happens on simulators rather than on hardware.

Consequently, today’s QaaS platforms often emphasize software development and hybrid workflows, with real hardware access treated as a limited and carefully scheduled resource. While this limits immediate practical gains, it allows the industry to prepare for future quantum systems as hardware reliability and availability improve.

Expected Progress Vectors in the Near Future

As quantum computing continues to evolve, we can expect several near-term progress vectors: expanded enterprise SLAs with stronger reliability guarantees, deeper integration with classical cloud workflows such as Kubernetes, Jupyter, and microservices, verticalized solutions for domains like chemistry, optimization, and cryptography, stronger standards and interoperability across hardware providers, and improved testing and benchmarking frameworks to guide hardware selection.

Quantum-as-a-Service (QaaS) is a critical component in enabling the broader usefulness of quantum computers, as it provides easy and accessible entry to the technology for researchers, developers, and enterprises, lowering barriers and accelerating practical applications.

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Itamar Fink is a Research Intern at Qbeat Ventures and a Master’s student in Computer Science at LMU Munich, focusing on quantum technologies and their emerging applications.