Best Cloud GPU Providers of 2026 - Page 5

Cleura Cloud is an IaaS platform based in Europe, constructed on open standards and powered by OpenStack, which provides a secure, scalable, and programmable cloud infrastructure to assist teams in building, scaling, and managing digital services while maintaining complete control over their data and compliance standards. This platform facilitates the deployment of virtual machines with customizable compute profiles, manages container orchestration, offers block and object storage, and includes networking services, managed databases, and automation tools accessible through APIs, CLI, or a cloud management portal. Cleura prioritizes data sovereignty by operating exclusively within European data centers, thereby ensuring compliance with EU regulations and preventing unauthorized access under non-EU laws. It accommodates a variety of deployment models such as Public Cloud tailored for developers and small to medium businesses, Compliant Cloud designed for critical and regulated workloads with heightened security and availability zones, and Private Cloud for organizations requiring entirely isolated OpenStack environments. Additionally, Cleura Cloud's commitment to security and regulatory compliance makes it a compelling choice for businesses navigating the complexities of data management in today's digital landscape.

GreenNode is a powerful, self-service AI cloud platform designed for enterprises, which centralizes the entire lifecycle of AI and machine learning models—from inception to deployment—utilizing a scalable infrastructure powered by GPUs that caters to contemporary AI demands. It offers cloud-based notebook instances that facilitate coding, data visualization, and teamwork, while also accommodating model training and fine-tuning through versatile computing options, along with a comprehensive model registry for overseeing versions and performance metrics across different deployments. In addition, it boasts serverless AI model-as-a-service capabilities, featuring a library of over 20 pre-trained open-source models that assist in tasks such as text generation, embeddings, vision, and speech, all accessible via standard APIs that allow for rapid experimentation and seamless application integration without the need to develop model infrastructure from the ground up. Moreover, GreenNode enhances model inference with rapid GPU execution and ensures smooth compatibility with various tools and frameworks, thus optimizing performance while providing users with the flexibility and efficiency necessary for their AI initiatives. This platform not only streamlines the AI development process but also empowers teams to innovate and deploy sophisticated models quickly and effectively.

HPC-AI is a cutting-edge enterprise AI infrastructure and GPU cloud service crafted to enhance the training of deep learning models, facilitate inference, and manage extensive compute tasks with impressive performance and cost-effectiveness. The platform offers an AI-optimized stack that is pre-configured for swift deployment and real-time inference, adeptly handling demanding tasks that necessitate high IOPS, ultra-low latency, and significant throughput. It establishes a strong GPU cloud environment tailored for artificial intelligence, high-performance computing, and various compute-heavy applications, equipping teams with essential tools to execute complex workflows effectively. Central to the platform's offerings is its software, which prioritizes parallel and distributed training, inference, and the fine-tuning of expansive neural networks, aiding organizations in lowering infrastructure expenses while preserving high performance. Additionally, technologies like Colossal-AI contribute to its capabilities, drastically speeding up model training and enhancing overall productivity. This combination of features helps organizations remain competitive in the rapidly evolving landscape of artificial intelligence.

packet.ai is a cloud platform designed for GPU computing that enables developers and AI teams to swiftly access high-performance resources without the drawbacks associated with conventional cloud setups. It offers on-demand GPU instances featuring state-of-the-art NVIDIA technology that can be initiated within seconds and accessed via platforms like SSH, Jupyter, or VS Code, allowing users to efficiently begin training models, conducting inference, or testing AI applications. By adopting a novel strategy for GPU resource management, Packet.ai dynamically allocates resources in response to real-time workload requirements, which permits multiple compatible tasks to utilize the same hardware effectively while ensuring consistent performance. This innovative method leads to improved resource utilization and removes the necessity of paying for unused capacity, concentrating instead on the precise compute resources utilized. Additionally, Packet.ai includes an OpenAI-compatible API that supports language model inference, embeddings, fine-tuning, and more, thereby expanding the possibilities for AI development and experimentation. The platform's flexibility and efficiency make it a valuable tool for teams looking to optimize their AI workflows.

DeepInfra is a cloud-based AI inference platform designed to effortlessly execute a wide range of the latest machine learning models at scale, such as large language models, vision models, embeddings, and various forms of media generation including images and videos. The platform offers serverless inference via straightforward APIs, enabling developers to seamlessly incorporate production-ready AI models into their applications without the burden of managing GPU resources, auto-scaling, complex deployments, or model hosting logistics. Supporting OpenAI-compatible APIs allows for an easier transition from existing OpenAI-style integrations, while also providing access to an extensive library of both open-source and commercial models. With its Native API, users can access every type of model available on the platform, covering tasks such as image generation, speech recognition, object detection, token classification, fill-mask, image classification, zero-shot image classification, and text classification. DeepInfra is designed for optimal performance, ensuring scalable, low-latency inference powered by state-of-the-art GPU infrastructure, which ultimately enhances the efficiency of AI-driven applications. This focus on performance makes it an ideal choice for businesses looking to leverage advanced AI technologies.

Charg is a platform for managing the lifecycle of AI infrastructure, converting established enterprise-grade supercomputing systems into adaptable cloud environments for AI and high-performance computing. The public HPC cloud offered by Charg allows access to resources ranging from a single GPU to an extensive 60+ PFLOPS cluster, enabling teams to harness supercomputing capabilities without the need to own or maintain the physical hardware. It utilizes advanced CRAY supercomputers and the robust NVIDIA DGX architecture, which integrates clustered NVIDIA V100 GPUs with 200 GbE InfiniBand networking and extensive all-flash CEPH storage, ensuring low-latency and high-throughput performance. Charg is specifically designed to handle intensive AI tasks, scientific research, and engineering computations, facilitating activities such as model training, large-scale inference, simulations, intricate data analysis, finite element analysis, and computational fluid dynamics. With an API-driven infrastructure, Charg not only scales seamlessly with existing workflows but also offers on-demand capacity, free from operational limitations, making it an ideal choice for diverse computational needs. This flexibility ensures that organizations can dynamically adjust their resources to meet changing demands without any hassle.

hosted·ai is a comprehensive neocloud platform designed to transform servers and GPUs into a highly efficient and lucrative AI cloud infrastructure and service offering. This platform integrates GPU orchestration, monetization, and neocloud management, effectively software-defining GPU resources to facilitate genuine multi-tenancy, dynamic scheduling, capacity sharing, and customizable overcommitment. Its GPU pools are capable of accommodating both shared and dedicated scenarios, utilizing isolated workloads alongside adaptive scheduling and versatile allocation strategies aimed at maximizing utilization to nearly 100%, thereby allowing more clients to be served per GPU. The system is equipped to handle elastic GPU as a Service (GPUaaS), bare metal GPU servers, GPU-optimized virtual machines, AI as a service, model libraries, bring-your-own-model implementations, tokenized AI workloads, along with conventional CPU, storage, and networking solutions. Additionally, the GPU Mesh feature provides on-demand wholesale capacity, offering infrastructure owners an extra avenue to monetize idle resources while enhancing overall service availability. This innovative approach ensures that AI capabilities can be leveraged more effectively across various applications and industries.

Elice AI Cloud Runbox is a managed GPU cloud that utilizes container technology to facilitate rapid AI development, experimentation, and model training, eliminating the need for users to set up infrastructure from the ground up. It offers preconfigured execution environments that allow users to quickly activate high-performance GPU or NPU resources, enabling them to start executing code, training models, or testing workloads almost instantly. By supporting scalable AI research with parallel GPU capabilities, including H100 and B200 infrastructure, Runbox enables teams to accelerate their experiment cycles and break through the limitations of local or on-premises hardware. The platform’s preconfigured nature allows researchers and developers to concentrate on their projects rather than on managing operating systems, containers, drivers, or ensuring runtime compatibility. Additionally, direct access to object storage from any instance ensures that datasets remain accessible across various environments while minimizing data-transfer delays between experiments. This streamlined approach ultimately enhances productivity and fosters innovation in AI research and development.

Nextify serves as a cloud infrastructure platform designed for the provisioning and oversight of various virtual machines, including confidential-computing VMs, GPU instances, and associated networking and storage solutions. The platform features both shared and dedicated vCPU offerings powered by AMD EPYC processors, alongside AMD SEV-SNP secure VMs that provide encrypted guest memory, a virtual TPM, and remote attestation capabilities. Additionally, it supports GPU VMs equipped with AMD Radeon AI PRO R9700 graphics cards, enabling high-performance computing tasks. Customers are granted the ability to attach NVMe-backed block storage, generate snapshots, and set up S3-compatible object storage buckets, as well as utilize public IPv4 addresses, firewalls, private networks, VPN gateways, and load balancers. Resource management can be executed via a web portal or through a REST API and command-line interface, with the API facilitating automation through scripts, CI pipelines, and Terraform configurations. Furthermore, compute instances are charged on an hourly basis, capped at a specified monthly limit, and are suitable for a variety of use cases such as web services, development and testing environments, databases, build jobs, GPU inference, fine-tuning, and rendering tasks. This flexibility makes Nextify a comprehensive solution for businesses looking to efficiently manage their cloud infrastructure needs.

GPUBank serves as a cloud-based platform where developers, machine-learning experts, and research groups can rent GPU resources to enhance their AI and GPU-intensive workloads. Users can easily navigate the web console to select either NVIDIA or AMD GPU instances, pick a deployment location, and initiate pre-configured setups for a variety of purposes, including model training, inference, fine-tuning, image generation, and framework development. The platform offers a range of templates, such as PyTorch, vLLM, ComfyUI, and Ollama, catering to diverse project needs. Additionally, GPUBank provides an API, a command-line interface, a Python SDK, and a Terraform provider to facilitate easy provisioning and management of usage. Pricing for GPU compute is calculated per second and encompasses the costs for the chosen instance's CPU, memory, local NVMe storage, public IPv4, and network traffic as part of the hourly rate; however, persistent disks incur additional charges. Customers have the flexibility to opt for on-demand, interruptible, or reserved capacity across various data center locations, ensuring they can tailor their resources to fit specific project requirements effectively. This versatility makes GPUBank an appealing choice for those looking to optimize their computational needs in a cost-effective manner.

NVIDIA Run:ai is a cutting-edge platform that streamlines AI workload orchestration and GPU resource management to accelerate AI development and deployment at scale. It dynamically pools GPU resources across hybrid clouds, private data centers, and public clouds to optimize compute efficiency and workload capacity. The solution offers unified AI infrastructure management with centralized control and policy-driven governance, enabling enterprises to maximize GPU utilization while reducing operational costs. Designed with an API-first architecture, Run:ai integrates seamlessly with popular AI frameworks and tools, providing flexible deployment options from on-premises to multi-cloud environments. Its open-source KAI Scheduler offers developers simple and flexible Kubernetes scheduling capabilities. Customers benefit from accelerated AI training and inference with reduced bottlenecks, leading to faster innovation cycles. Run:ai is trusted by organizations seeking to scale AI initiatives efficiently while maintaining full visibility and control. This platform empowers teams to transform resource management into a strategic advantage with zero manual effort.

Oracle Cloud Infrastructure not only accommodates traditional workloads but also provides advanced cloud development tools for modern needs. It is designed with the capability to identify and counteract contemporary threats, empowering innovation at a faster pace. By merging affordability with exceptional performance, it effectively reduces total cost of ownership. As a Generation 2 enterprise cloud, Oracle Cloud boasts impressive compute and networking capabilities while offering an extensive range of infrastructure and platform cloud services. Specifically engineered to fulfill the requirements of mission-critical applications, Oracle Cloud seamlessly supports all legacy workloads, allowing businesses to transition from their past while crafting their future. Notably, our Generation 2 Cloud is uniquely equipped to operate Oracle Autonomous Database, recognized as the industry's first and only self-driving database. Furthermore, Oracle Cloud encompasses a wide-ranging portfolio of cloud computing solutions, spanning application development, business analytics, data management, integration, security, artificial intelligence, and blockchain technology, ensuring that businesses have all the tools they need to thrive in a digital landscape. This comprehensive approach positions Oracle Cloud as a leader in the evolving cloud marketplace.

Transition your essential business operations and critical workloads to the Azure infrastructure to enhance your operational effectiveness. You can operate SQL Server, SAP, Oracle® applications, and high-performance computing on Azure Virtual Machines. Opt for your preferred Linux distribution or Windows Server for your virtual instances. Configure virtual machines equipped with as much as 416 vCPUs and 12 TB of memory to meet your needs. Enjoy impressive performance with up to 3.7 million local storage IOPS for each VM. Leverage advanced connectivity options, including up to 30 Gbps Ethernet and the cloud’s pioneering 200 Gbps InfiniBand deployment. Choose from a variety of processors, including AMD, Ampere (Arm-based), or Intel, based on your specific requirements. Safeguard sensitive information by encrypting data, securing VMs against cyber threats, managing network traffic securely, and ensuring adherence to regulatory standards. Utilize Virtual Machine Scale Sets to create applications that can easily scale. Optimize your cloud expenditure with Azure Spot Virtual Machines and reserved instances to maximize cost-effectiveness. Establish your private cloud environment using Azure Dedicated Host, and ensure that mission-critical applications operate reliably on Azure to bolster overall resiliency. This strategic move not only enhances performance but also positions your business for future growth and innovation.

With just a click, you can access your own high-performance PC from any device, at any place, and at any time. Experience seamless performance with capabilities of up to 96 cores running at 2.8 GHz, an impressive 1360 GB of RAM, and 16 NVIDIA A100 80 GB graphics cards. You have the flexibility to expand both your storage and specifications as necessary. We streamline the process, allowing you to concentrate on what truly matters—your creative projects. Choose from various plans based on whether you intend to utilize the Cloud PC alone or as part of a team. Customize your hardware configuration to suit your specific needs and seamlessly operate your Cloud Desktop through your web browser or desktop application, no matter where you are located. Renderro Cloud Storage provides a centralized hub for all your high-quality designs and resources, ensuring that they are easily accessible whenever you need them. This scalable storage solution means you won't be constrained by project file sizes, and you can adjust your storage capacity whenever required. Furthermore, Cloud Drives can be shared across multiple Cloud Desktops, allowing for effortless transitions between machines without the hassle of transferring files repeatedly, thereby enhancing your productivity and workflow.

Infomaniak is a major European cloud player and the largest developer of web technologies in Switzerland. Infomaniak, a Swiss cloud player, is fully responsible for all aspects of its value chain. This includes the design and production of data centers and products as well as the orchestration and management of cloud infrastructures. This independence allows it to guarantee the security and confidentiality of the data of more then one million users from more than 208 countries. Infomaniak is located in Geneva and Winterthur at the heart of Europe and offers all the solutions companies need to increase their online visibility and sustain their development.

Rafay helps enterprises, neoclouds, telcos, sovereign AI clouds, and service providers transform GPU and CPU infrastructure into secure, self-service platforms for AI innovation, consumption, and monetization. The Rafay Platform sits between accelerated infrastructure and the teams or customers consuming it, helping organizations move from raw compute to production-ready AI platforms faster. With Rafay, platform teams can orchestrate, govern, and automate infrastructure across data centers, cloud, hybrid, and air-gapped or sovereign environments. Teams can deliver self-service access to GPU resources, Kubernetes clusters, virtual machines, SLURM environments, AI workbenches, inference services, and application catalogs while maintaining control through policies, access controls, quotas, audit trails, and usage visibility. Rafay supports multiple teams, tenants, customers, and business units on shared infrastructure. Secure multi-tenancy, cost visibility, chargeback, and lifecycle automation help maximize GPU utilization while giving developers and data scientists fast access to the environments they need. For neoclouds, GPU cloud providers, telcos, and service providers, Rafay helps turn infrastructure investments into differentiated services. Providers can package compute and AI capabilities into consumable SKUs, deliver self-service GPU and AI platforms, and monetize usage through consumption-based models. Rafay unifies orchestration, governance, consumption, and monetization so organizations can accelerate AI adoption and turn infrastructure into a launchpad for innovation.

CoreWeave stands out as a cloud infrastructure service that focuses on GPU-centric computing solutions specifically designed for artificial intelligence applications. Their platform delivers scalable, high-performance GPU clusters that enhance both training and inference processes for AI models, catering to sectors such as machine learning, visual effects, and high-performance computing. In addition to robust GPU capabilities, CoreWeave offers adaptable storage, networking, and managed services that empower AI-focused enterprises, emphasizing reliability, cost-effectiveness, and top-tier security measures. This versatile platform is widely adopted by AI research facilities, labs, and commercial entities aiming to expedite their advancements in artificial intelligence technology. By providing an infrastructure that meets the specific demands of AI workloads, CoreWeave plays a crucial role in driving innovation across various industries.

The NVIDIA DGX Cloud provides an AI infrastructure as a service that simplifies the deployment of large-scale AI models and accelerates innovation. By offering a comprehensive suite of tools for machine learning, deep learning, and HPC, this platform enables organizations to run their AI workloads efficiently on the cloud. With seamless integration into major cloud services, it offers the scalability, performance, and flexibility necessary for tackling complex AI challenges, all while eliminating the need for managing on-premise hardware.

We have listened to customer feedback and have reduced the prices for both our bare metal and virtual server offerings while maintaining the same level of power and flexibility. A graphics processing unit (GPU) serves as an additional layer of computational ability that complements the central processing unit (CPU). By selecting IBM Cloud® for your GPU needs, you gain access to one of the most adaptable server selection frameworks in the market, effortless integration with your existing IBM Cloud infrastructure, APIs, and applications, along with a globally distributed network of data centers. When it comes to performance, IBM Cloud Bare Metal Servers equipped with GPUs outperform AWS servers on five distinct TensorFlow machine learning models. We provide both bare metal GPUs and virtual server GPUs, whereas Google Cloud exclusively offers virtual server instances. In a similar vein, Alibaba Cloud restricts its GPU offerings to virtual machines only, highlighting the unique advantages of our versatile options. Additionally, our bare metal GPUs are designed to deliver superior performance for demanding workloads, ensuring you have the necessary resources to drive innovation.

Genesis Cloud is designed to support a wide range of applications, whether you are developing machine learning models or performing advanced data analytics. In just minutes, you can set up a virtual machine with either GPU or CPU capabilities, and with various configurations available, you’re sure to find a solution that fits your project's scale, from initial deployment to large-scale operations. You can also create storage volumes that automatically grow in response to your data needs; these are secured by a reliable storage cluster and encrypted to protect against unauthorized access or data loss. Our data centers utilize a state-of-the-art non-blocking leaf-spine architecture featuring 100G switches, ensuring that each server has multiple 25G uplinks, while every account operates within its own isolated virtual network for enhanced security and privacy. Additionally, our cloud services utilize renewable energy, making it not only environmentally friendly but also the most cost-effective option available in the marketplace. This commitment to sustainability and affordability sets Genesis Cloud apart as a leader in cloud infrastructure solutions.

Vast.ai offers the lowest-cost cloud GPU rentals. Save up to 5-6 times on GPU computation with a simple interface. Rent on-demand for convenience and consistency in pricing. You can save up to 50% more by using spot auction pricing for interruptible instances. Vast offers a variety of providers with different levels of security, from hobbyists to Tier-4 data centres. Vast.ai can help you find the right price for the level of reliability and security you need. Use our command-line interface to search for offers in the marketplace using scriptable filters and sorting options. Launch instances directly from the CLI, and automate your deployment. Use interruptible instances to save an additional 50% or even more. The highest bidding instance runs; other conflicting instances will be stopped.

Fluidstack is a high-performance AI infrastructure platform built to deliver scalable and secure compute resources for demanding workloads. It provides dedicated GPU clusters that are fully isolated, ensuring consistent performance without shared resource interference. The platform includes Atlas OS, a bare-metal operating system designed for fast provisioning, orchestration, and full control of infrastructure. Fluidstack also offers Lighthouse, a system that monitors, optimizes, and automatically resolves performance issues in real time. Its infrastructure is engineered for speed and reliability, enabling rapid deployment of GPU resources. The platform supports large-scale AI training, inference, and other compute-intensive applications. Fluidstack is designed for enterprises, AI research labs, and government organizations that require advanced computing capabilities. It provides strong security features, including compliance with standards like GDPR, SOC 2, and ISO certifications. The platform offers human support with fast response times to ensure operational stability. Fluidstack enables teams to scale infrastructure efficiently as their needs grow. Overall, it provides a robust and flexible solution for AI-driven computing at scale.

Our advanced storage systems are capable of efficiently managing millions of small, random files to support GPU-based training servers, significantly speeding up the overall training process. We provide high-bandwidth, low-latency network solutions that facilitate seamless connections between distributed training servers while enabling smooth data transfer from storage to servers. Unlike other cloud providers that impose additional fees for data retrieval, which can quickly accumulate, we strive to be an integral part of your team. Collaborating with you, we assist in establishing scheduling services, advise on best practices, and deliver exceptional support tailored to your needs. Recognizing that workflows differ across organizations, Cirrascale is committed to ensuring that you receive the most suitable solutions to achieve optimal results. Uniquely, we are the only provider that collaborates closely with you to customize your cloud instances, enhancing performance, eliminating bottlenecks, and streamlining your workflow. Additionally, our cloud-based solutions are designed to accelerate your training, simulation, and re-simulation processes, yielding faster outcomes. By prioritizing your unique requirements, Cirrascale empowers you to maximize your efficiency and effectiveness in cloud operations.

Every product we offer includes bandwidth and is typically priced 70 to 90% lower than similar options available in the market. Our solutions are crafted by a dedicated team based entirely in the United States. The servers are managed by independent hosts utilizing our proprietary hypervisor software. We provide a cloud solution that is flexible, resilient, scalable, and secure, perfectly suited for burstable workloads. Our pricing can be as much as 70% lower than traditional cloud providers. For continuous workloads, such as ML inference, we offer low-cost secure servers available on a monthly basis or for extended terms. A key priority for us is ensuring seamless integration with our customers' existing technology stacks. We pride ourselves on our thorough documentation and maintenance, ensuring everything functions smoothly and effectively. Additionally, our commitment to customer support further enhances the overall user experience.

Novita AI is a comprehensive cloud platform designed for AI developers, startups, and enterprises that need reliable access to models, agents, and GPU infrastructure. The platform offers serverless access to more than 200 AI models through a unified API, secure sandbox environments for running autonomous agents, and dedicated or serverless GPU resources for inference, training, and deployment workloads. Built specifically for AI applications, Novita AI provides production-grade reliability, predictable performance, and seamless scalability without the operational burden of managing complex infrastructure. Developers can build, test, and deploy AI-powered products while benefiting from centralized management, flexible pricing, and enterprise-ready support.