Best Infrastructure-as-a-Service (IaaS) Providers for PyTorch
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Compare the Top Infrastructure-as-a-Service (IaaS) Providers that integrate with PyTorch as of October 2025
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This a list of Infrastructure-as-a-Service (IaaS) providers that integrate with PyTorch. Use the filters on the left to add additional filters for products that have integrations with PyTorch. View the products that work with PyTorch in the table below.
What are Infrastructure-as-a-Service (IaaS) Providers for PyTorch?
Infrastructure-as-a-Service (IaaS) providers offer virtualized computing resources over the internet, allowing businesses to rent IT infrastructure such as servers, storage, and networking on-demand. IaaS platforms eliminate the need for companies to invest in and maintain physical hardware, offering scalability, flexibility, and cost-efficiency. Users can provision and manage virtual machines, storage, and other resources through web-based dashboards or APIs. IaaS is commonly used for hosting websites, running applications, and supporting data analytics or disaster recovery solutions. Major IaaS providers often offer advanced features like load balancing, security services, and automated backups. Compare and read user reviews of the best Infrastructure-as-a-Service (IaaS) providers for PyTorch currently available using the table below. This list is updated regularly.
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1
Google Cloud Platform
Google
Google Cloud Platform offers Infrastructure-as-a-Service (IaaS) with scalable compute, storage, and networking resources. Services like Google Compute Engine provide flexible virtual machine instances that can be customized to meet the specific needs of workloads. With GCP’s IaaS offerings, businesses can provision infrastructure on-demand and scale it dynamically. New customers receive $300 in free credits to run, test, and deploy workloads, allowing them to experiment with GCP’s IaaS solutions without any upfront investment. These resources are hosted on Google’s global infrastructure, ensuring high performance and low-latency access. GCP’s IaaS offerings are highly secure, with built-in encryption and identity management features to protect data and applications.Starting Price: Free ($300 in free credits) -
2
Amazon Web Services (AWS)
Amazon
Amazon Web Services (AWS) is the world’s most comprehensive cloud platform, trusted by millions of customers across industries. From startups to global enterprises and government agencies, AWS provides on-demand solutions for compute, storage, networking, AI, analytics, and more. The platform empowers organizations to innovate faster, reduce costs, and scale globally with unmatched flexibility and reliability. With services like Amazon EC2 for compute, Amazon S3 for storage, SageMaker for AI/ML, and CloudFront for content delivery, AWS covers nearly every business and technical need. Its global infrastructure spans 120 availability zones across 38 regions, ensuring resilience, compliance, and security. Backed by the largest community of customers, partners, and developers, AWS continues to lead the cloud industry in innovation and operational expertise. -
3
RunPod
RunPod
RunPod offers a cloud-based platform designed for running AI workloads, focusing on providing scalable, on-demand GPU resources to accelerate machine learning (ML) model training and inference. With its diverse selection of powerful GPUs like the NVIDIA A100, RTX 3090, and H100, RunPod supports a wide range of AI applications, from deep learning to data processing. The platform is designed to minimize startup time, providing near-instant access to GPU pods, and ensures scalability with autoscaling capabilities for real-time AI model deployment. RunPod also offers serverless functionality, job queuing, and real-time analytics, making it an ideal solution for businesses needing flexible, cost-effective GPU resources without the hassle of managing infrastructure.Starting Price: $0.40 per hour -
4
Microsoft Azure
Microsoft
Microsoft's Azure is a cloud computing platform that allows for rapid and secure application development, testing and management. Azure. Invent with purpose. Turn ideas into solutions with more than 100 services to build, deploy, and manage applications—in the cloud, on-premises, and at the edge—using the tools and frameworks of your choice. Continuous innovation from Microsoft supports your development today, and your product visions for tomorrow. With a commitment to open source, and support for all languages and frameworks, build how you want, and deploy where you want to. On-premises, in the cloud, and at the edge—we’ll meet you where you are. Integrate and manage your environments with services designed for hybrid cloud. Get security from the ground up, backed by a team of experts, and proactive compliance trusted by enterprises, governments, and startups. The cloud you can trust, with the numbers to prove it. -
5
Alibaba Cloud
Alibaba
As a business unit of Alibaba Group (NYSE: BABA), Alibaba Cloud provides a comprehensive suite of global cloud computing services to power both our international customers’ online businesses and Alibaba Group’s own e-commerce ecosystem. In January 2017, Alibaba Cloud became the official Cloud Services Partner of the International Olympic Committee. By harnessing, and improving on, the latest cloud technology and security systems, we tirelessly work towards our vision - to make it easier for you to do business anywhere, with anyone in the world. Alibaba Cloud provides cloud computing services for large and small businesses, individual developers, and the public sector in over 200 countries and regions. -
6
Amazon Elastic Inference
Amazon
Amazon Elastic Inference allows you to attach low-cost GPU-powered acceleration to Amazon EC2 and Sagemaker instances or Amazon ECS tasks, to reduce the cost of running deep learning inference by up to 75%. Amazon Elastic Inference supports TensorFlow, Apache MXNet, PyTorch and ONNX models. Inference is the process of making predictions using a trained model. In deep learning applications, inference accounts for up to 90% of total operational costs for two reasons. Firstly, standalone GPU instances are typically designed for model training - not for inference. While training jobs batch process hundreds of data samples in parallel, inference jobs usually process a single input in real time, and thus consume a small amount of GPU compute. This makes standalone GPU inference cost-inefficient. On the other hand, standalone CPU instances are not specialized for matrix operations, and thus are often too slow for deep learning inference. -
7
Database Mart
Database Mart
Database Mart offers a comprehensive suite of server hosting solutions tailored for diverse computing needs. Their VPS hosting provides isolated CPU, memory, and disk resources with full root or admin access, supporting various applications such as database hosting, mail servers, file sharing, SEO tools, and script testing. These VPS plans come with SSD storage, automated backups, and an intuitive control panel, making them ideal for individuals and small businesses seeking cost-effective solutions. For more demanding applications, Database Mart's dedicated servers offer exclusive resources, ensuring superior performance and security. These servers are customizable to support large software systems and high-traffic e-commerce platforms, providing reliability for critical operations. Their GPU servers feature high-performance NVIDIA GPUs, catering to high-performance computing and advanced AI workloads.
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