Traditional GPU infrastructure requires significant investment in physical hardware leading to high upfront costs due to ongoing maintenance, upgrades and electricity. With GPUaaS, companies can eliminate the need for upfront hardware investments and convert GPU usage into an operational expense, paying only for what they use. Continue reading as we explore what GPU-as-a-Service means, its key benefits and why Hyperstack can be your preferred GPUaaS provider.
GPU-as-a-Service (GPUaaS) allows users to deploy GPU resources in the cloud rather than owning and maintaining them on-site. By using a GPU cloud service, companies can run compute-heavy tasks like AI training, machine learning, deep learning, data analytics, and HPC applications without any upfront GPU investment.
GPUaaS transforms infrastructure from capital to operational expense, providing on-demand GPU services with scalable, usage-based billing. This makes it easier for teams to innovate faster, without the burden of managing physical GPU infrastructure.
On-premises GPU infrastructure offers full control, predictable performance, and lower latency, suitable for organisations with steady, long-term GPU needs. But this comes at a high cost due to hardware, maintenance, upgrades, and energy usage.
On the other hand, GPU-as-a-Service eliminates capital expenses by offering on-demand access to powerful GPU platforms. With flexible pricing and GPU cloud service models, organisations can easily scale workloads up or down as needed.
In 2023, the global GPU-as-a-service market was valued at $3.23 billion and is expected to increase from $4.31 billion in 2024 to $49.84 billion by 2032 [source]. This massive growth is driven by the following factors:
Growing Demand for AI, Machine Learning and LLM
Rising popularity of cloud gaming
Growth in Data Analytics and Real-Time Processing Workloads
Infrastructure and Operational Cost Savings
Here’s why more businesses are switching to GPU cloud platforms like Hyperstack for their compute-intensive workloads:
Despite the advantages, there are challenges associated with using GPU as a service:
Some of the popular cloud GPU providers could be Hyperstack, NexGen Cloud’s GPUaaS platform, lets you deploy workloads on NVIDIA GPU infrastructure, paying only for usage. Here's why it's ideal:
Explore the Hyperstack GPU Cloud Platform
Ready to try one of the most scalable GPU cloud services available? Take a quick tour of Hyperstack and explore our high-performance GPU platform for your AI, ML, and data workloads.
As AI adoption grows, organisations need GPU solutions that scale. GPU-as-a-Service offers flexible, secure, and powerful infrastructure for enterprise workloads—without upfront investment. With Hyperstack’s sustainable GPU cloud platform, you get performance, flexibility, and eco-conscious GPU services. Whether you’re a startup or enterprise, our platform is built for your next big idea.
Sign Up Now to Get started with Hyperstack.
GPUaaS lets users access GPU infrastructure in the cloud, removing the need for in-house hardware and offering scalable GPU services.
The key benefits of using GPUaas include scalability, flexible payment models, enhanced data security, and faster time-to-market for AI and ML applications.
Yes, Hyperstack allows seamless scaling of GPU resources to meet changing workload demands, ensuring optimal performance.
Hyperstack is a GPUaaS provider with usage-based billing. You only pay for what you use—no hidden fees.
Yes, Hyperstack supports LLM training and inference via its high-performance GPU cloud platform optimised for AI.
Sign up for a Hyperstack account by visiting https://console.hyperstack.cloud/. After registration, sign in, activate your account and add credit to deploy your virtual machine on Hyperstack. Learn more about getting started in our documentation here.