GPU as a Service Market

The global GPU as a Service market is expected to be valued at USD 8.21 billion in 2025 and is projected to reach USD 26.62 billion by 2030 and grow at a CAGR of 26.5% from 2025 to 2030. The increasing use of high-performance computing (HPC) for scientific research, engineering simulations, and financial modeling is fueling the GPUaaS market. GPUs excel at parallel processing, making them ideal for complex simulations in fields like aerospace, pharmaceuticals, and climate modeling. For example, IBM Cloud and Oracle Cloud offer GPUaaS solutions tailored for HPC workloads. By providing researchers with remote access to advanced GPU resources, these services accelerate innovation, reduce time-to-insight, and optimize research budgets.

Amazon web Servies, Inc. (US), Microsoft (US), Google (US), Oracle (US), IBM (US), Coreweave (US), Alibaba Cloud, Lambda (US), Tencent Cloud (China), Jarvislabs.ai (India) are the major players in the GPU as a Dervice market. Market participants have become more varied with their offerings, expanding their global reach through strategic growth approaches like launching new products, collaborations, establishing alliances, and forging partnerships.

For instance, in February 2025, Google (US) introduced the preview of A4X VMs, powered by NVIDIA GB200 NVL72, a system featuring 72 NVIDIA Blackwell GPUs and 36 Arm-based NVIDIA Grace CPUs connected via fifth-gen NVLink. Designed for next-gen AI reasoning models, A4X VMs offer the performance and efficiency needed to handle massive datasets, long context windows, and complex problem-solving.

In March 2024, Amazon Web Services, Inc. and NVIDIA Corporation partnered to offer  NVIDIA Grace Blackwell GPU-based Amazon EC2 instances and NVIDIA DGX Cloud. This partnership enhances real-time inference capabilities for multi-trillion parameter LLMs, enabling faster, more scalable, and cost-efficient AI model deployment compared to previous-generation NVIDIA GPUs on EC2.

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Major GPU as a Service Companies Include:

• Amazon web Servies, Inc. (US)
• Microsoft (US)
• Google (US)
• Oracle (US)
• IBM (US)
• Coreweave (US)
• Alibaba Cloud, Lambda (US)
• Tencent Cloud (China)
• Jarvislabs.ai (India)

AMAZON WEB SERVICES, INC.:

Amazon Web Services, Inc. (AWS), a company that is owned by Amazon.com, is the global leader in cloud computing service providing a full range of cloud-based solutions in computing, storage, networking, artificial intelligence (AI), machine learning (ML), and analytics. AWS provides computing, storage solutions, databases, networking, machine learning, analytics, and security services to businesses, governments, and individuals. AWS offers GPU-powered cloud instances that speed up AI/ML workloads, deep learning, and graphics-intensive workloads. AWS offers Amazon EC2 GPU instances, including G4, P4, and P5, which are designed for AI inference, deep learning training, and HPC. These instances use NVIDIA GPUs, such as T4, A100, H100, and the new Blackwell B100 GPUs, enabling customers to process large-scale AI and ML workloads efficiently. To enable businesses building generative AI models, AWS offers Amazon SageMaker, a managed ML service that streamlines the development of building, training, and deploying AI models with GPU support

MICROSOFT:

Microsoft develops and sells a large variety of software, hardware, cloud services and Al-based solutions. Its key products are the Windows operating system, the Microsoft Office software suite, and enterprise offerings like Microsoft Azure, Dynamics 365, and Microsoft 365. Microsoft has established itself as a market leader in cloud computing, artificial intelligence, and enterprise IT services via its Azure cloud platform, which offers scalable, secure, and high-performance solutions for companies and developers globally. It boasts a large customer base in various sectors including government, finance, retail, and healthcare, applying Al and machine learning to support digital transformation in industries.

Microsoft is a major player in the GPU as a Service (GPUaaS) market, primarily through its Microsoft Azure cloud platform, which offers GPU-powered virtual machines (VMs) designed for Al, deep learning, graphics rendering, and high-performance computing (HPC). Azure provides a variety of NVIDIA GPU-based instances, including A100, H100, V100, and RTX-series GPUs, enabling enterprises to accelerate workloads related to Al model training, scientific simulations, gaming, and data analytics. Microsoft Azure's ND- and NC-series virtual machines are specifically designed for Al and HPC workloads, delivering high throughput and scalability for enterprises requiring GPU acceleration. Additionally, Microsoft has developed Azure Machine Learning, which integrates GPUaaS capabilities to allow organizations to build, train, and deploy machine learning models efficiently in the cloud. With its investments in Al, quantum computing, and custom Al accelerators, Microsoft is continuously enhancing its GPUaaS offerings to meet the growing demand for cloud-based GPU resources.

Company Ranking

The GPU as a Service market is consolidated, with the top five players: Amazon Web Services (AWS), Microsoft, Google, IBM, and Oracle Corporation collectively hold around 54-62% of the total market share. These giants use their massive cloud infrastructure, AI, and worldwide presence to capture the majority of the market. AWS dominates the market with its strong ecosystem of machine learning and AI services, providing scalable GPU instances on Amazon EC2. Microsoft Azure comes in second, offering specialized AI and HPC workloads based on NVIDIA GPUs, addressing enterprises that need hybrid and multi-cloud solutions. Google Cloud has solidified its position with TensorFlow processing units (TPUs) and high-end AI services, especially in data analytics and machine learning-based applications. IBM's AI-based solutions, such as Watson AI services, also add to its strong market presence. Oracle Corporation has also enhanced its cloud infrastructure with high-performance GPU offerings for enterprise customers across industries such as finance, healthcare, and automotive. The leadership of these players is further reinforced by strategic collaborations with AI startups, ongoing innovation in GPU technology and investments in data center growth. With increasing demand for AI workloads, these leaders are likely to continue their dominance, fueling innovation and market growth in the GPUaaS market.

Related Reports:

GPU as a Service Market by Service Model (IaaS, PaaS), GPU Type (High-end GPUs, Mid-range GPUs, Low-end GPUs), Deployment (Public Cloud, Private Cloud, Hybrid Cloud), Enterprise Type (Large Enterprises, SMEs) - Global Forecast to 2030

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