Alternatives to Pacific

IONOS offers GPU Servers that deliver a high-performance computing framework aimed at managing tasks that demand significantly more power than standard CPU systems can provide. This infrastructure features top-tier NVIDIA GPUs, including the H100, H200, and L40s, in addition to specialized AI accelerators like Intel Gaudi, facilitating extensive parallel processing for demanding applications. By utilizing GPU-accelerated instances, the cloud infrastructure is enhanced with dedicated graphical processors, enabling virtual machines to execute intricate calculations and handle data-heavy tasks at a much faster rate compared to traditional servers. This solution is especially well-suited for fields such as artificial intelligence, deep learning, and data science, where training models on extensive datasets or executing rapid inference processes is necessary. Furthermore, it accommodates big data analytics, scientific simulations, and visualization tasks, including 3D rendering or modeling, that necessitate substantial computational capacity. As a result, organizations seeking to optimize their processing capabilities for complex workloads can greatly benefit from this advanced infrastructure.

Hivenet Compute gives you on-demand RTX 5090 and RTX Pro 6000 GPUs, plus vCPU instances, billed per second while they run. Hivenet owns and operates the infrastructure, with data centres in France, the UAE and the US, so EU teams can keep workloads and data in Europe. Use it for training and fine-tuning, inference, notebooks, rendering and batch jobs. Launch from ready-made templates in a few minutes, or automate everything through the public Compute API. If you'd rather not run the serving layer yourself, the Inference API gives you an OpenAI-compatible endpoint. Teams get organisations with role-based access, prepaid credits, and S3-compatible object storage alongside compute.

CambridgeNexus (CNEX), located in Boston, is an operator of AI Factory that provides exclusive leasing of bare-metal NVIDIA GB300 NVL72 racks, managing an inventory of over 350 racks housed in Tier III facilities across six US states and Taiwan, with installations typically completed within a timeframe of 75 to 90 days post-contract. Unlike traditional GPU marketplaces or virtualized cloud services, CNEX offers customers full racks that are bare metal, single tenant, and devoid of shared hardware or instances, underpinned by seven operational layers that encompass power, cooling, networking, compute, orchestration, compliance, and customer workload planning. Customers benefit from leasing complete systems, including NVIDIA GB300 NVL72 and NVIDIA Vera Rubin setups, with flexible lease agreements spanning from six months to over five years. The company guarantees a rapid turnaround from contract to installation, achieving a 99.95% uptime SLA, and adheres to stringent security and compliance standards, including SOC 2 Type I, GDPR, and HIPAA certifications, with ISO 27001 and FedRAMP statuses currently in progress. This unique approach not only ensures high reliability but also addresses the specific needs of businesses looking for dedicated AI computing resources.

OneSource Cloud specializes in the design, construction, and management of sovereign AI infrastructure tailored for organizations in regulated sectors that cannot utilize public cloud for sensitive operations, such as healthcare and life sciences, financial services, government and defense, energy, legal, and research sectors. Our services include the provision of dedicated GPU compute as a managed offering, encompassing cluster design, hardware acquisition, data center colocation, deployment, and ongoing maintenance. The clusters are equipped with NVIDIA GPUs connected via InfiniBand for efficient multi-node training and inference, complemented by high-performance storage solutions and dedicated private networking. Each client benefits from a unique, isolated environment that ensures their data and models do not share hardware with other users, safeguarding their confidentiality. Our managed services extend to capacity planning, provisioning, workload scheduling, system monitoring, patching, and customer support. Each environment is meticulously configured to meet the client’s compliance standards, including regulations such as NIST 800-171 and specific data residency requirements. Currently, we operate over 20,000 GPUs across more than 96 data centers, ensuring robust support for our clients' complex needs in an increasingly data-sensitive landscape. This extensive infrastructure positions us as a leader in providing secure AI solutions for organizations facing strict regulatory demands.

WhiteFiber operates as a comprehensive AI infrastructure platform that specializes in delivering high-performance GPU cloud services and HPC colocation solutions specifically designed for AI and machine learning applications. Their cloud services are meticulously engineered for tasks involving machine learning, expansive language models, and deep learning, equipped with advanced NVIDIA H200, B200, and GB200 GPUs alongside ultra-fast Ethernet and InfiniBand networking, achieving an impressive GPU fabric bandwidth of up to 3.2 Tb/s. Supporting a broad range of scaling capabilities from hundreds to tens of thousands of GPUs, WhiteFiber offers various deployment alternatives such as bare metal, containerized applications, and virtualized setups. The platform guarantees enterprise-level support and service level agreements (SLAs), incorporating unique cluster management, orchestration, and observability tools. Additionally, WhiteFiber’s data centers are strategically optimized for AI and HPC colocation, featuring high-density power, direct liquid cooling systems, and rapid deployment options, while also ensuring redundancy and scalability through cross-data center dark fiber connectivity. With a commitment to innovation and reliability, WhiteFiber stands out as a key player in the AI infrastructure ecosystem.

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.

IREN’s AI Cloud is a cutting-edge GPU cloud infrastructure that utilizes NVIDIA's reference architecture along with a high-speed, non-blocking InfiniBand network capable of 3.2 TB/s, specifically engineered for demanding AI training and inference tasks through its bare-metal GPU clusters. This platform accommodates a variety of NVIDIA GPU models, providing ample RAM, vCPUs, and NVMe storage to meet diverse computational needs. Fully managed and vertically integrated by IREN, the service ensures clients benefit from operational flexibility, robust reliability, and comprehensive 24/7 in-house support. Users gain access to performance metrics monitoring, enabling them to optimize their GPU expenditures while maintaining secure and isolated environments through private networking and tenant separation. The platform empowers users to deploy their own data, models, and frameworks such as TensorFlow, PyTorch, and JAX, alongside container technologies like Docker and Apptainer, all while granting root access without any limitations. Additionally, it is finely tuned to accommodate the scaling requirements of complex applications, including the fine-tuning of extensive language models, ensuring efficient resource utilization and exceptional performance for sophisticated AI projects.

Axe Compute offers enterprise-level bare-metal GPU infrastructure tailored for AI and machine learning applications, featuring extensive global accessibility, dedicated clusters, and reliable access. Within around 48 hours, teams can receive dedicated GPU clusters at over 200 locations, allowing for complete flexibility in selecting region, GPU type, fabric, interconnect, and topology. This solution is specifically designed to tackle the often-overlooked challenges associated with scaling AI, including delays in provisioning, limited availability in the cloud, quota restrictions, inflexible provider economics, costs linked to data movement, and performance degradation due to virtualization. By providing 100% bare-metal access without any virtualization overhead or disruptive neighbors, Axe enables teams to effectively conduct LLM training, inference, diffusion, fine-tuning, enterprise deployment, and various other AI-related tasks with enhanced control. Additionally, its distributed GPU infrastructure ensures low-latency placement close to users and data, minimizing the necessity to transfer data to centralized cloud regions, thereby streamlining operations for teams working on complex AI projects.

Targon offers a secure cloud computing environment designed for efficiently scaling AI workloads with high-speed GPUs and CPUs suitable for training and deployment purposes. With a user-friendly API, SDK, and CLI, it simplifies the management of various workloads, including rentals, serverless applications, persistent volumes, web endpoints, and inference of large language models. At its core, Targon leverages confidential computing principles without compromise, utilizing a decentralized network of trusted execution environments to enhance security. The Targon Virtual Machine maintains data confidentiality through hardware-backed protection powered by Intel TDX, while NVIDIA's Confidential Computing and PCIe Confidentiality technologies safeguard data even on untrusted hardware. Users can choose to deploy confidential compute environments, establish connections to GPU servers with configured SSH keys, or leverage serverless containers that intelligently auto-scale in response to user traffic demands. This flexibility allows organizations to tailor their computing resources to meet fluctuating needs while ensuring stringent security measures are upheld.

Amazon EC2 Capacity Blocks for Machine Learning allow users to secure accelerated computing instances within Amazon EC2 UltraClusters specifically for their machine learning tasks. This service encompasses a variety of instance types, including Amazon EC2 P5en, P5e, P5, and P4d, which utilize NVIDIA H200, H100, and A100 Tensor Core GPUs, along with Trn2 and Trn1 instances that leverage AWS Trainium. Users can reserve these instances for periods of up to six months, with cluster sizes ranging from a single instance to 64 instances, translating to a maximum of 512 GPUs or 1,024 Trainium chips, thus providing ample flexibility to accommodate diverse machine learning workloads. Additionally, reservations can be arranged as much as eight weeks ahead of time. By operating within Amazon EC2 UltraClusters, Capacity Blocks facilitate low-latency and high-throughput network connectivity, which is essential for efficient distributed training processes. This configuration guarantees reliable access to high-performance computing resources, empowering you to confidently plan your machine learning projects, conduct experiments, develop prototypes, and effectively handle anticipated increases in demand for machine learning applications. Furthermore, this strategic approach not only enhances productivity but also optimizes resource utilization for varying project scales.

lium.io gives developers, researchers and AI agents on-demand access to NVIDIA GPU capacity from independent providers. Rent a single GPU or a full 8-GPU node for training, fine-tuning, inference and batch workloads, with SSH and Jupyter access. Use the web, CLI, Python SDK, API or MCP integration to deploy. Per-second billing and usage-based marketplace rates make short jobs practical, without a minimum commitment. Secure and Spot options let you choose capacity for your workload. Live prices and availability are published on the marketplace. New accounts can receive $5 of credit after signup checks. GPU providers set their own rental prices and earn 95% of rental revenue plus bonuses. List capacity in the provider portal; developer guides are in the documentation.

Confidential AI offers a secure platform for private AI inference, agent environments, and confidential computing solutions tailored for AI laboratories, inference service providers, routers, and organizations that manage sensitive data. Its hosted inference service operates open-weight models within hardware-backed trusted execution environments (TEEs), utilizing technologies such as Intel TDX and AMD SEV-SNP confidential virtual machines, paired with NVIDIA GPUs in a confidential computing configuration. The system ensures that prompts, responses, and workload information remain safeguarded from infrastructure operators, allowing clients to authenticate attestation prior to submitting sensitive information. Users have the flexibility to implement an OpenAI-compatible API to establish inference endpoints and agent workloads, or alternatively, they can acquire the confidential-computing stack for deployment on their own premises, bare metal servers, or across major cloud platforms. This service is particularly beneficial for scenarios that involve serving models while restricting operator access to prompts and model assets, as well as executing sensitive AI workloads in a dedicated confidential computing environment. Additionally, the emphasis on robust security measures fosters trust in the processing of sensitive data, enabling clients to focus on innovation without compromising privacy.

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.

Sesterce is a leading provider of cloud-based GPU services for AI and machine learning, designed to power the most demanding applications across industries. From AI-driven drug discovery to fraud detection in finance, Sesterce’s platform offers both virtualized and dedicated GPU clusters, making it easy to scale AI projects. With dynamic storage, real-time data processing, and advanced pipeline acceleration, Sesterce is perfect for organizations looking to optimize ML workflows. Its pricing model and infrastructure support make it an ideal solution for businesses seeking performance at scale.

AIC Cloud is an international cloud hosting service catering to developers, startups, and small enterprises throughout Asia, Africa, Europe, and North America. They offer Linux VPS plans starting at just $1.19 per month featuring NVMe SSD and complete root access, as well as dedicated bare-metal servers beginning at $22 per month, and NVIDIA cloud GPU instances (including RTX 3090, RTX 4090, and A100) charged by the minute with rates starting at $0.14 per hour. Additionally, users can benefit from business email services with custom domains and the convenience of one-click app deployment. What distinguishes AIC Cloud is its straightforward flat-rate monthly pricing, ensuring that the rate you initially choose remains the same every month; per-minute GPU billing without any hourly minimums; and accessible customer support through real humans via WhatsApp and email. The platform also features multiple data center locations across Asia Pacific, Europe, and North America, each equipped with anti-DDoS protection on all plans, while providing various payment options such as UPI, international cards, and net banking. Founded in 2024, AIC Cloud is a product of Applied Intelligence Corporation, a self-sustaining technology firm that prioritizes user needs in its offerings. Its commitment to customer satisfaction and innovative pricing structures make it a compelling choice for those seeking reliable cloud hosting solutions.

GPU.ai is a cloud service designed specifically for GPU infrastructure aimed at artificial intelligence tasks. The platform provides two primary offerings: the GPU Instance, which allows users to initiate compute instances equipped with the latest NVIDIA GPUs for various functions such as training, fine-tuning, and inference, and a model inference service where users can upload their pre-trained models, with GPU.ai managing the deployment process. Among the available hardware options are the H200s and A100s, catering to different performance requirements. Additionally, GPU.ai accommodates custom requests through its sales team, ensuring quick responses—typically within about 15 minutes—for those with specific GPU or workflow needs, making it a versatile choice for developers and researchers alike. This flexibility enhances user experience by enabling tailored solutions that align with individual project demands.

Oracle Cloud Infrastructure (OCI) offers a range of compute options that are not only speedy and flexible but also cost-effective, catering to various workload requirements, including robust bare metal servers, virtual machines, and efficient containers. OCI Compute stands out by providing exceptionally adaptable VM and bare metal instances that ensure optimal price-performance ratios. Users can tailor the exact number of cores and memory to align with their applications' specific demands, which translates into high performance for enterprise-level tasks. Additionally, the platform simplifies the application development process through serverless computing, allowing users to leverage technologies such as Kubernetes and containerization. For those engaged in machine learning, scientific visualization, or other graphic-intensive tasks, OCI offers NVIDIA GPUs designed for performance. It also includes advanced capabilities like RDMA, high-performance storage options, and network traffic isolation to enhance overall efficiency. With a consistent track record of delivering superior price-performance compared to other cloud services, OCI's virtual machine shapes provide customizable combinations of cores and memory. This flexibility allows customers to further optimize their costs by selecting the precise number of cores needed for their workloads, ensuring they only pay for what they use. Ultimately, OCI empowers organizations to scale and innovate without compromising on performance or budget.

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.

Mistral Compute is a specialized AI infrastructure platform that provides a comprehensive, private stack including GPUs, orchestration, APIs, products, and services, available in various configurations from bare-metal servers to fully managed PaaS solutions. Its mission is to broaden access to advanced AI technologies beyond just a few providers, enabling governments, businesses, and research organizations to design, control, and enhance their complete AI landscape while training and running diverse workloads on an extensive array of NVIDIA-powered GPUs, all backed by reference architectures crafted by experts in high-performance computing. This platform caters to specific regional and sectoral needs, such as defense technology, pharmaceutical research, and financial services, and incorporates four years of operational insights along with a commitment to sustainability through decarbonized energy sources, ensuring adherence to strict European data-sovereignty laws. Additionally, Mistral Compute’s design not only prioritizes performance but also fosters innovation by allowing users to scale and customize their AI applications as their requirements evolve.

NVIDIA Confidential Computing safeguards data while it is actively being processed, ensuring the protection of AI models and workloads during execution by utilizing hardware-based trusted execution environments integrated within the NVIDIA Hopper and Blackwell architectures, as well as compatible platforms. This innovative solution allows businesses to implement AI training and inference seamlessly, whether on-site, in the cloud, or at edge locations, without requiring modifications to the model code, all while maintaining the confidentiality and integrity of both their data and models. Among its notable features are the zero-trust isolation that keeps workloads separate from the host operating system or hypervisor, device attestation that confirms only authorized NVIDIA hardware is executing the code, and comprehensive compatibility with shared or remote infrastructures, catering to ISVs, enterprises, and multi-tenant setups. By protecting sensitive AI models, inputs, weights, and inference processes, NVIDIA Confidential Computing facilitates the execution of high-performance AI applications without sacrificing security or efficiency. This capability empowers organizations to innovate confidently, knowing their proprietary information remains secure throughout the entire operational lifecycle.

NVIDIA DGX Cloud Lepton is an advanced AI platform that facilitates connections for developers to a worldwide network of GPU computing resources across various cloud providers, all through a singular interface. It provides a cohesive experience for discovering and leveraging GPU capabilities, complemented by integrated AI services that enhance the deployment lifecycle across multiple cloud environments. With immediate access to NVIDIA's accelerated APIs, developers can begin their projects using serverless endpoints and prebuilt NVIDIA Blueprints, along with GPU-enabled computing. When scaling becomes necessary, DGX Cloud Lepton ensures smooth customization and deployment through its expansive global network of GPU cloud providers. Furthermore, it allows for effortless deployment across any GPU cloud, enabling AI applications to operate within multi-cloud and hybrid settings while minimizing operational complexities, and it leverages integrated services designed for inference, testing, and training workloads. This versatility ultimately empowers developers to focus on innovation without worrying about the underlying infrastructure.

Impossible Cloud is a cloud infrastructure platform built to support enterprise storage, artificial intelligence, and high-performance computing workloads through a unified set of cloud services. The platform combines S3-compatible object storage, dedicated bare metal GPU servers, and managed AI services that allow organizations to build, deploy, and scale modern applications. Its object storage service provides high availability, enterprise-grade durability, transparent pricing, and compatibility with existing S3-based workflows while eliminating egress fees and long-term lock-in. Dedicated bare metal GPU servers give customers exclusive access to physical hardware without virtualization layers, maximizing performance for machine learning, AI inference, and GPU-intensive applications. Managed AI services support large language model deployment, Kubernetes orchestration, and HPC environments while reducing infrastructure management complexity. Impossible Cloud is designed for organizations with strict security and compliance requirements by offering encryption, role-based access control, multi-factor authentication, and certifications including ISO 27001 and SOC 2. Customers can choose deployment regions in Europe or the United States while maintaining data governance aligned with regulatory requirements such as GDPR. A partner ecosystem, enterprise support, and broad integration capabilities make the platform suitable for managed service providers, enterprises, and technology partners. Impossible Cloud delivers scalable cloud infrastructure that combines enterprise storage, AI computing, and transparent pricing without sacrificing performance or data sovereignty.

Massed Compute provides advanced GPU computing solutions designed specifically for AI, machine learning, scientific simulations, and data analytics needs. As an esteemed NVIDIA Preferred Partner, it offers a wide range of enterprise-grade NVIDIA GPUs, such as the A100, H100, L40, and A6000, to guarantee peak performance across diverse workloads. Clients have the option to select bare metal servers for enhanced control and performance or opt for on-demand compute instances, which provide flexibility and scalability according to their requirements. Additionally, Massed Compute features an Inventory API that facilitates the smooth integration of GPU resources into existing business workflows, simplifying the processes of provisioning, rebooting, and managing instances. The company's infrastructure is located in Tier III data centers, which ensures high availability, robust redundancy measures, and effective cooling systems. Furthermore, with SOC 2 Type II compliance, the platform upholds stringent standards for security and data protection, making it a reliable choice for organizations. In an era where computational power is crucial, Massed Compute stands out as a trusted partner for businesses aiming to harness the full potential of GPU technology.

Core Scientific provides specialized, high-density colocation infrastructure along with advanced software solutions tailored for demanding computational tasks like AI, machine learning, high-performance computing, and digital asset mining. The company offers scalable high-density computing environments with a power capacity exceeding 1.3 GW, ensuring quicker deployment times and enhanced cooling and power systems specifically designed for intensive workloads. Its digital mining services include proprietary fleet management software that can oversee up to one million miners, along with features for real-time thermal monitoring and hash-price economic analysis to maximize profitability. Additionally, Core Scientific integrates high-density racks (ranging from 50 to over 200 kW per rack) with robust enterprise-grade infrastructure, supporting a diverse range of applications including AI model training and inference, cloud computing, financial services analytics, critical government systems, and healthcare research initiatives. This comprehensive approach allows Core Scientific to meet the diverse needs of its clients while maintaining a focus on efficiency and performance.

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.

Cantech VPS Hosting offers a virtual private server solution tailored for businesses, developers, agencies, and website owners who require greater control and dedicated computing resources compared to traditional shared hosting options. Their plans feature isolated virtual machines that come with allocated CPU, memory, SSD storage, bandwidth, and a dedicated IP address for enhanced performance. Clients have the flexibility to choose between Linux or Windows server setups, granting them root access via SSH or RDP, and they can install various applications, frameworks, and scripts for diverse purposes such as websites, e-commerce platforms, development, testing, and other workloads. Additionally, Cantech provides optional managed support for initial setup and ongoing maintenance, while self-managed plans empower customers to take full control over their servers. As needs evolve, users can easily upgrade their resources, and they benefit from daily backups along with server control panel options for streamlined management. Monthly VPS plans are available with data center locations in India and select international regions, ensuring global access and reliability for users worldwide. This comprehensive service is designed to meet the demands of modern digital operations, making it an ideal choice for those seeking tailored server solutions.

TensorHost delivers GPU computing resources through its own infrastructure, avoiding reliance on third-party providers. Clients indicate their workload specifications, GPU needs, quantity, and preferred timing; service details and location are verified before a final agreement on allocation is reached. This service enables access to NVIDIA GPU capacity for AI applications and other highly demanding computational tasks. TensorHost maintains the foundational infrastructure, allowing clients to utilize the allocated compute for their specific applications and operations. It caters primarily to developers, AI teams, and businesses seeking GPU resources without the burden of buying and managing their own GPU servers. Users are charged based on their actual usage, with the capacity and pricing determined based on the requested resources. This model allows for flexibility and scalability in meeting the diverse computing demands of clients in a rapidly evolving technological landscape.

VMoHost is a global hosting provider offering high-performance dedicated servers, GPU servers, and professional colocation services for businesses that require reliable infrastructure. The company operates across more than 250 data centers worldwide, enabling customers to deploy servers in multiple continents including North America, Europe, Asia, Africa, South America, and Australia. Its dedicated servers are designed to deliver powerful computing performance while allowing full control over hardware configurations and software environments. Customers can customize CPU, RAM, storage options such as NVMe or SSD drives, and network bandwidth to match the demands of their projects. VMoHost uses trusted enterprise-grade hardware from brands like Supermicro, Dell, HP, and IBM to ensure consistent performance and long-term stability. The platform also offers specialized GPU servers powered by NVIDIA and AMD graphics cards for resource-intensive workloads such as AI training, video rendering, gaming, and data processing. With fast deployment times of 24 to 48 hours, businesses can quickly scale their hosting infrastructure without delays. VMoHost provides advanced networking with high-speed connectivity and low latency through multiple Tier 1 network providers. Its services also include strong security measures, DDoS protection options, and reliable data center infrastructure with redundant power and cooling systems. Combined with 24/7 expert technical support, VMoHost offers a scalable and cost-effective hosting environment for modern digital operations.

Lambda is building the cloud designed for superintelligence by delivering integrated AI factories that combine dense power, liquid cooling, and next-generation NVIDIA compute into turnkey systems. Its platform supports everything from rapid prototyping on single GPU instances to running massive distributed training jobs across full GB300 NVL72 superclusters. With 1-Click Clusters™, teams can instantly deploy optimized B200 and H100 clusters prepared for production-grade AI workloads. Lambda’s shared-nothing, single-tenant security model ensures that sensitive data and models remain isolated at the hardware level. SOC 2 Type II certification and caged-cluster options make it suitable for mission-critical use cases in enterprise, government, and research. NVIDIA’s latest chips—including the GB300, HGX B300, HGX B200, and H200—give organizations unprecedented computational throughput. Lambda’s infrastructure is built to scale with ambition, capable of supporting workloads ranging from inference to full-scale training of foundation models. For AI teams racing toward the next frontier, Lambda provides the power, security, and reliability needed to push boundaries.

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.

Radiant is an advanced AI infrastructure platform that delivers a complete, vertically integrated solution for AI development and deployment. It unifies software, compute, energy, and capital into a single platform, enabling organizations to build and scale AI workloads efficiently. The platform offers a robust AI Cloud powered by NVIDIA GPUs, along with MLOps capabilities such as model training, inference, and lifecycle management. Its lightweight and scalable architecture supports high-performance computing environments with automated resource management and secure multi-tenancy. Radiant also leverages a global powered-land portfolio, providing access to large-scale energy resources for cost-efficient operations. With backing from Brookfield, it offers strong financial support for large infrastructure projects. The platform is designed to deliver consistent performance, scalability, and operational independence. Overall, Radiant enables enterprises and governments to deploy AI infrastructure with speed and efficiency.

NetMind.AI is an innovative decentralized computing platform and AI ecosystem aimed at enhancing global AI development. It capitalizes on the untapped GPU resources available around the globe, making AI computing power affordable and accessible for individuals, businesses, and organizations of varying scales. The platform offers diverse services like GPU rentals, serverless inference, and a comprehensive AI ecosystem that includes data processing, model training, inference, and agent development. Users can take advantage of competitively priced GPU rentals and effortlessly deploy their models using on-demand serverless inference, along with accessing a broad range of open-source AI model APIs that deliver high-throughput and low-latency performance. Additionally, NetMind.AI allows contributors to integrate their idle GPUs into the network, earning NetMind Tokens (NMT) as a form of reward. These tokens are essential for facilitating transactions within the platform, enabling users to pay for various services, including training, fine-tuning, inference, and GPU rentals. Ultimately, NetMind.AI aims to democratize access to AI resources, fostering a vibrant community of contributors and users alike.

NVIDIA Brev is designed to streamline AI and ML development by delivering ready-to-use GPU environments hosted on popular cloud platforms. With Launchables, users can rapidly deploy preconfigured compute instances tailored to their project’s needs, including GPU capacity, container images, and essential files like notebooks or GitHub repositories. These Launchables can be customized, named, and generated with just a few clicks, then easily shared across social networks or directly with collaborators. The platform includes a variety of prebuilt Launchables that incorporate NVIDIA’s latest AI frameworks, microservices, and Blueprints, allowing developers to get started without delay. NVIDIA Brev also offers a virtual GPU sandbox, making it simple to set up CUDA-enabled environments, run Python scripts, and work within Jupyter notebooks right from a browser. Developers can monitor Launchable usage metrics and leverage CLI tools for fast code editing and SSH access. This flexible, easy-to-use platform accelerates the entire AI development lifecycle from experimentation to deployment. It empowers teams and startups to innovate faster by removing traditional infrastructure barriers.

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.

The Cloud GPU Service is a flexible computing solution that offers robust GPU processing capabilities, ideal for high-performance parallel computing tasks. Positioned as a vital resource within the IaaS framework, it supplies significant computational power for various demanding applications such as deep learning training, scientific simulations, graphic rendering, and both video encoding and decoding tasks. Enhance your operational efficiency and market standing through the advantages of advanced parallel computing power. Quickly establish your deployment environment with automatically installed GPU drivers, CUDA, and cuDNN, along with preconfigured driver images. Additionally, speed up both distributed training and inference processes by leveraging TACO Kit, an all-in-one computing acceleration engine available from Tencent Cloud, which simplifies the implementation of high-performance computing solutions. This ensures your business can adapt swiftly to evolving technological demands while optimizing resource utilization.

Selecting the appropriate GPUs and deployment strategies can be quite intricate. Whether you are leaning towards on-site installations or utilizing cloud services, Arc Compute offers specialized insights to optimize your infrastructure planning while enhancing performance. At Arc Compute, our process begins with a thorough assessment of your unique AI or HPC goals. Following this, our experts design tailored GPU infrastructure solutions, accommodating everything from temporary rentals for peak usage to permanent clusters for continuous training demands. We conduct comprehensive consultations to determine the most effective GPU configurations and deployment models, which may include cloud, on-premises, or hybrid options. Our services include prompt sourcing and delivery of NVIDIA GPU servers, along with the management of all vendor relationships. We also provide seamless installation and continuous support to maintain the optimal functioning of your GPU infrastructure. With our collaborative and consultative approach, we ensure that you achieve the ideal combination of performance, cost-effectiveness, and scalability. This commitment to understanding each client's unique needs sets us apart in the industry.

OpenGPU Network serves as a decentralized platform for GPU computing, linking individuals in need of robust processing power with a diverse array of independent GPU suppliers around the world. This innovative system facilitates various demanding tasks such as AI inference, machine learning training, and rendering by harnessing distributed resources rather than relying on traditional centralized cloud services. It functions as an intelligent routing mechanism that dynamically pairs workloads with the available GPU resources globally, enabling immediate task execution without the hassle of infrastructure management or limitations related to regions, queues, or provisioning delays. By consolidating resources from data centers, cloud providers, and personal machines, OpenGPU tackles the increasing disparity between the soaring demand for GPUs and the scattered, underused supply. The platform operates on a blockchain framework, which not only manages task coordination and result verification but also ensures that rewards are fairly distributed, fostering a trustless environment for users. In doing so, OpenGPU not only enhances accessibility to GPU computing but also promotes efficient utilization of computational resources on a global scale.

A colocation data center serves as a dedicated physical location that provides the essential infrastructure, including power, cooling, and security, for businesses to house their computing equipment and servers. This facility can accommodate a range of setups, from individual cabinets to larger cages or fully private suites. Typically, colocation providers rent out this space to a diverse array of clients, such as network operators, cloud service providers, and various enterprises. These clients benefit from the ability to interconnect and collaborate within the same colocation data center, fostering a cooperative business environment. This approach enables organizations to streamline their IT functions and develop a more efficient system, ultimately leading to cost savings. Additionally, colocation facilities are designed to support your growth over time, whether you are beginning with a modest setup and planning to expand, entering new markets, requiring customized solutions, or seeking cloud connectivity. Our commitment is to provide tailored solutions that address a broad spectrum of evolving business requirements.

FPT Cloud represents an advanced cloud computing and AI solution designed to enhance innovation through a comprehensive and modular suite of more than 80 services, encompassing areas such as computing, storage, databases, networking, security, AI development, backup, disaster recovery, and data analytics, all adhering to global standards. Among its features are scalable virtual servers that provide auto-scaling capabilities and boast a 99.99% uptime guarantee; GPU-optimized infrastructure specifically designed for AI and machine learning tasks; the FPT AI Factory, which offers a complete AI lifecycle suite enhanced by NVIDIA supercomputing technology, including infrastructure, model pre-training, fine-tuning, and AI notebooks; high-performance object and block storage options that are S3-compatible and encrypted; a Kubernetes Engine that facilitates managed container orchestration with portability across different cloud environments; as well as managed database solutions that support both SQL and NoSQL systems. Additionally, it incorporates sophisticated security measures with next-generation firewalls and web application firewalls, alongside centralized monitoring and activity logging features, ensuring a holistic approach to cloud services. This multifaceted platform is designed to meet the diverse needs of modern enterprises, making it a key player in the evolving landscape of cloud technology.

Core42 provides sovereign AI and cloud solutions designed to empower individuals, organizations, and countries to harness the full capabilities of AI through a secure, scalable, and high-performance infrastructure. Their AI Cloud serves as a comprehensive platform that supports the entire intelligence lifecycle, encompassing everything from data movement and training to optimization, fine-tuning, deployment, governance, and production inference. By offering access to top-tier accelerators, integrated tools, orchestration, high-performance storage, and expert assistance, it enables AI developers to train, fine-tune, and deploy agentic and inference workloads more efficiently. The Core42 AI Cloud also facilitates GenAI services, model hosting and inference, AI operations, and infrastructure as a service, which empowers teams to confidently and swiftly build and scale next-generation AI applications. Additionally, Core42's GenAI services foster rapid innovation by providing agents, retrieval-augmented generation, guardrails, and fine-tuning capabilities, ensuring that users can stay ahead in the evolving AI landscape. This comprehensive approach not only enhances productivity but also drives significant advancements in AI technology.

Amazon EC2 G4 instances are specifically designed to enhance the performance of machine learning inference and applications that require high graphics capabilities. Users can select between NVIDIA T4 GPUs (G4dn) and AMD Radeon Pro V520 GPUs (G4ad) according to their requirements. The G4dn instances combine NVIDIA T4 GPUs with bespoke Intel Cascade Lake CPUs, ensuring an optimal mix of computational power, memory, and networking bandwidth. These instances are well-suited for tasks such as deploying machine learning models, video transcoding, game streaming, and rendering graphics. On the other hand, G4ad instances, equipped with AMD Radeon Pro V520 GPUs and 2nd-generation AMD EPYC processors, offer a budget-friendly option for handling graphics-intensive workloads. Both instance types utilize Amazon Elastic Inference, which permits users to add economical GPU-powered inference acceleration to Amazon EC2, thereby lowering costs associated with deep learning inference. They come in a range of sizes tailored to meet diverse performance demands and seamlessly integrate with various AWS services, including Amazon SageMaker, Amazon ECS, and Amazon EKS. Additionally, this versatility makes G4 instances an attractive choice for organizations looking to leverage cloud-based machine learning and graphics processing capabilities.

Voltage Park stands as a pioneer in GPU cloud infrastructure, delivering both on-demand and reserved access to cutting-edge NVIDIA HGX H100 GPUs, which are integrated within Dell PowerEdge XE9680 servers that boast 1TB of RAM and v52 CPUs. Their infrastructure is supported by six Tier 3+ data centers strategically located throughout the U.S., providing unwavering availability and reliability through redundant power, cooling, network, fire suppression, and security systems. A sophisticated 3200 Gbps InfiniBand network ensures swift communication and minimal latency between GPUs and workloads, enhancing overall performance. Voltage Park prioritizes top-notch security and compliance, employing Palo Alto firewalls alongside stringent measures such as encryption, access controls, monitoring, disaster recovery strategies, penetration testing, and periodic audits. With an impressive inventory of 24,000 NVIDIA H100 Tensor Core GPUs at their disposal, Voltage Park facilitates a scalable computing environment, allowing clients to access anywhere from 64 to 8,176 GPUs as needed, thereby accommodating a wide range of workloads and applications. Their commitment to innovation and customer satisfaction positions Voltage Park as a leading choice for businesses seeking advanced GPU solutions.

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.

TensorWave is a cloud platform designed for AI and high-performance computing (HPC), exclusively utilizing AMD Instinct Series GPUs to ensure optimal performance. It features a high-bandwidth and memory-optimized infrastructure that seamlessly scales to accommodate even the most rigorous training or inference tasks. Users can access AMD’s leading GPUs in mere seconds, including advanced models like the MI300X and MI325X, renowned for their exceptional memory capacity and bandwidth, boasting up to 256GB of HBM3E and supporting speeds of 6.0TB/s. Additionally, TensorWave's architecture is equipped with UEC-ready functionalities that enhance the next generation of Ethernet for AI and HPC networking, as well as direct liquid cooling systems that significantly reduce total cost of ownership, achieving energy cost savings of up to 51% in data centers. The platform also incorporates high-speed network storage, which provides transformative performance, security, and scalability for AI workflows. Furthermore, it ensures seamless integration with a variety of tools and platforms, accommodating various models and libraries to enhance user experience. TensorWave stands out for its commitment to performance and efficiency in the evolving landscape of AI technology.

The NVIDIA Quadro Virtual Workstation provides cloud-based access to Quadro-level computational capabilities, enabling organizations to merge the efficiency of a top-tier workstation with the advantages of cloud technology. As the demand for more intensive computing tasks rises alongside the necessity for mobility and teamwork, companies can leverage cloud workstations in conjunction with conventional on-site setups to maintain a competitive edge. Included with the NVIDIA virtual machine image (VMI) is the latest GPU virtualization software, which comes pre-loaded with updated Quadro drivers and ISV certifications. This software operates on select NVIDIA GPUs utilizing Pascal or Turing architectures, allowing for accelerated rendering and simulation from virtually any location. Among the primary advantages offered are improved performance thanks to RTX technology, dependable ISV certification, enhanced IT flexibility through rapid deployment of GPU-powered virtual workstations, and the ability to scale in accordance with evolving business demands. Additionally, organizations can seamlessly integrate this technology into their existing workflows, further enhancing productivity and collaboration across teams.