Best Cloud GPU Providers for Microsoft Azure

Compare the Top Cloud GPU Providers that integrate with Microsoft Azure as of October 2025

This a list of Cloud GPU providers that integrate with Microsoft Azure. Use the filters on the left to add additional filters for products that have integrations with Microsoft Azure. View the products that work with Microsoft Azure in the table below.

What are Cloud GPU Providers for Microsoft Azure?

Cloud GPU providers offer scalable, on-demand access to Graphics Processing Units (GPUs) over the internet, enabling users to perform computationally intensive tasks such as machine learning, deep learning, scientific simulations, and 3D rendering without the need for significant upfront hardware investments. These platforms provide flexibility in resource allocation, allowing users to select GPU types, configurations, and billing models that best suit their specific workloads. By leveraging cloud infrastructure, organizations can accelerate their AI and ML projects, ensuring high performance and reliability. Additionally, the global distribution of data centers ensures low-latency access to computing resources, enhancing the efficiency of real-time applications. The competitive landscape among providers has led to continuous improvements in service offerings, pricing, and support, catering to a wide range of industries and use cases. Compare and read user reviews of the best Cloud GPU providers for Microsoft Azure currently available using the table below. This list is updated regularly.

  • 1
    RunPod

    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
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  • 2
    Compute with Hivenet
    Compute with Hivenet is the world's first truly distributed cloud computing platform, providing reliable and affordable on-demand computing power from a certified network of contributors. Designed for AI model training, inference, and other compute-intensive tasks, it provides secure, scalable, and on-demand GPU resources at up to 70% cost savings compared to traditional cloud providers. Powered by RTX 4090 GPUs, Compute rivals top-tier platforms, offering affordable, transparent pricing with no hidden fees. Compute is part of the Hivenet ecosystem, a comprehensive suite of distributed cloud solutions that prioritizes sustainability, security, and affordability. Through Hivenet, users can leverage their underutilized hardware to contribute to a powerful, distributed cloud infrastructure.
    Starting Price: $0.10/hour
  • 3
    FluidStack

    FluidStack

    FluidStack

    Unlock 3-5x better prices than traditional clouds. FluidStack aggregates under-utilized GPUs from data centers around the world to deliver the industry’s best economics. Deploy 50,000+ high-performance servers in seconds via a single platform and API. Access large-scale A100 and H100 clusters with InfiniBand in days. Train, fine-tune, and deploy LLMs on thousands of affordable GPUs in minutes with FluidStack. FluidStack unites individual data centers to overcome monopolistic GPU cloud pricing. Compute 5x faster while making the cloud efficient. Instantly access 47,000+ unused servers with tier 4 uptime and security from one simple interface. Train larger models, deploy Kubernetes clusters, render quicker, and stream with no latency. Setup in one click with custom images and APIs to deploy in seconds. 24/7 direct support via Slack, emails, or calls, our engineers are an extension of your team.
    Starting Price: $1.49 per month
  • 4
    Moonglow

    Moonglow

    Moonglow

    Moonglow lets you run your local notebooks on a remote GPU as easily as changing your Python runtime. Avoid managing SSH keys, package installations, and other DevOps headaches. We have GPUs for every use case, A40s, A100s, H100s and more. Manage GPUs within your IDE.
  • 5
    AceCloud

    AceCloud

    AceCloud

    AceCloud is a comprehensive public cloud and cybersecurity platform designed to support businesses with scalable, secure, and high-performance infrastructure. Its public cloud services include compute options tailored for RAM-intensive, CPU-intensive, and spot instances, as well as cloud GPU offerings featuring NVIDIA A2, A30, A100, L4, L40S, RTX A6000, RTX 8000, and H100 GPUs. It provides Infrastructure as a Service (IaaS), enabling users to deploy virtual machines, storage, and networking resources on demand. Storage solutions encompass object storage, block storage, volume snapshots, and instance backups, ensuring data integrity and accessibility. AceCloud also offers managed Kubernetes services for container orchestration and supports private cloud deployments, including fully managed cloud, one-time deployment, hosted private cloud, and virtual private servers.
    Starting Price: $0.0073 per hour
  • 6
    Rafay

    Rafay

    Rafay

    Delight developers and operations teams with the self-service and automation they need, with the right mix of standardization and control that the business requires. Centrally specify and manage configurations (in Git) for clusters encompassing security policy and software add-ons such as service mesh, ingress controllers, monitoring, logging, and backup and restore solutions. Blueprints and add-on lifecycle management can easily be applied to greenfield and brownfield clusters centrally. Blueprints can also be shared across multiple teams for centralized governance of add-ons deployed across the fleet. For environments requiring agile development cycles, users can go from a Git push to an updated application on managed clusters in seconds — 100+ times a day. This is particularly suited for developer environments where updates are very frequent.
  • 7
    NVIDIA DGX Cloud
    NVIDIA DGX Cloud offers a fully managed, end-to-end AI platform that leverages the power of NVIDIA’s advanced hardware and cloud computing services. This platform allows businesses and organizations to scale AI workloads seamlessly, providing tools for machine learning, deep learning, and high-performance computing (HPC). DGX Cloud integrates seamlessly with leading cloud providers, delivering the performance and flexibility required to handle the most demanding AI applications. This service is ideal for businesses looking to enhance their AI capabilities without the need to manage physical infrastructure.
  • 8
    SQream

    SQream

    SQream

    ​SQream is a GPU-accelerated data analytics platform that enables organizations to process large, complex datasets with unprecedented speed and efficiency. By leveraging NVIDIA's GPU technology, SQream executes intricate SQL queries on vast datasets rapidly, transforming hours-long processes into minutes. It offers dynamic scalability, allowing businesses to seamlessly scale their data operations in line with growth, without disrupting analytics workflows. SQream's architecture supports deployments that provide flexibility to meet diverse infrastructure needs. Designed for industries such as telecom, manufacturing, finance, advertising, and retail, SQream empowers data teams to gain deep insights, foster data democratization, and drive innovation, all while significantly reducing costs. ​
  • 9
    NVIDIA Quadro Virtual Workstation
    NVIDIA Quadro Virtual Workstation delivers Quadro-level computing power directly from the cloud, allowing businesses to combine the performance of a high-end workstation with the flexibility of cloud computing. As workloads grow more compute-intensive and the need for mobility and collaboration increases, cloud-based workstations, alongside traditional on-premises infrastructure, offer companies the agility required to stay competitive. The NVIDIA virtual machine image (VMI) comes with the latest GPU virtualization software pre-installed, including updated Quadro drivers and ISV certifications. The virtualization software runs on select NVIDIA GPUs based on Pascal or Turing architectures, enabling faster rendering and simulation from anywhere. Key benefits include enhanced performance with RTX technology support, certified ISV reliability, IT agility through fast deployment of GPU-accelerated virtual workstations, scalability to match business needs, and more.
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