Alternatives to Pacific
Compare Pacific alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Pacific in 2026. Compare features, ratings, user reviews, pricing, and more from Pacific competitors and alternatives in order to make an informed decision for your business.
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IONOS Cloud GPU Servers
IONOS
IONOS GPU Servers provide an accelerated computing infrastructure designed to handle workloads that require significantly more processing power than traditional CPU-based systems. It integrates enterprise-grade NVIDIA GPUs such as the H100, H200, and L40s, as well as specialized AI accelerators like Intel Gaudi, enabling massive parallel processing for compute-intensive applications. GPU-accelerated instances extend cloud infrastructure with dedicated graphics processors so virtual machines can perform complex calculations and data-heavy operations much faster than conventional servers. It is particularly suitable for artificial intelligence, deep learning, and data science tasks that involve training models on large datasets or performing high-speed inference operations. It also supports big data analytics, scientific simulations, and visualization workloads such as 3D rendering or modeling that require high computational throughput. -
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Compute with Hivenet
Hivenet
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 hivenet compute. -
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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. -
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OneSource Cloud
OneSource Cloud
OneSource Cloud designs, builds, and manages sovereign AI infrastructure for organizations in regulated industries that cannot run sensitive workloads on public cloud: healthcare and life sciences, financial services, government and defense, energy, legal, and research. We deliver dedicated GPU compute as a managed service. Scope covers cluster design, hardware procurement, data center colocation, deployment, and ongoing operations. Clusters use NVIDIA GPUs with InfiniBand interconnect for multi-node training and inference, backed by high-performance storage and private networking. Each customer gets an isolated, single-tenant environment, so data and models never share hardware with another tenant. Managed services include capacity planning, provisioning, workload scheduling, monitoring, patching, and support. Environments are configured to the customer's compliance requirements, including NIST 800-171 and data residency controls. We operate 20,000+ GPUs across 96+ DCs -
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GPUBank
GPU Compute
GPUBank is a cloud GPU rental platform for developers, machine-learning practitioners, and research teams that need accelerated compute for AI and other GPU workloads. Through its web console, customers can select NVIDIA or AMD GPU instances, choose a deployment region, and start preconfigured environments for tasks such as model training, inference, fine-tuning, image generation, and framework development. Available templates include PyTorch, vLLM, ComfyUI, and Ollama. The service provides an API, command-line interface, Python SDK, and Terraform provider for provisioning and usage management. GPU compute is priced by the second, with the selected instance's CPU, memory, local NVMe storage, public IPv4, and network traffic included in the hourly rate; persistent disks are billed separately. Customers can use on-demand, interruptible, or reserved capacity across listed data-center regions.Starting Price: $0.23/GPU/hour -
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CambridgeNexus
CambridgeNexus, Inc.
CambridgeNexus (CNEX) is a Boston-based AI Factory operator that owns bare-metal NVIDIA GB300 NVL72 racks and leases them whole, single tenant, from an allocation of 350+ racks across Tier III facilities in six US states and Taiwan, installed within 75 to 90 days of contract. Not a GPU marketplace and not a virtualized cloud. Customers lease full racks: bare metal, single tenant, no instances, no shared hardware. Seven operating layers run under one model: power, cooling, networking, compute, orchestration, compliance and customer workload planning. What a customer gets: - Full-rack NVIDIA GB300 NVL72 and NVIDIA Vera Rubin systems, from one rack upward - Lease terms from 6 months to 5+ years - Tier III facilities in USA and Taiwan - Contract to installation and acceptance in 75 to 90 days - 99.95% uptime SLA - SOC 2 Type I, GDPR and HIPAA; ISO 27001 and FedRAMP 20x in progress -
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Fluidstack
Fluidstack
Fluidstack is an AI infrastructure platform designed to provide high-performance compute resources for advanced workloads. It offers dedicated GPU clusters that are fully isolated and optimized for large-scale AI training and inference. The platform includes Atlas OS, a bare-metal operating system built to enable fast provisioning and efficient orchestration of AI infrastructure. Fluidstack also provides Lighthouse, a monitoring and optimization tool that ensures reliability and performance across workloads. Its infrastructure is designed for speed, scalability, and secure operations, with single-tenant environments by default. The platform supports enterprises, AI labs, and governments that require high-performance computing capabilities. Fluidstack emphasizes rapid deployment, enabling teams to access GPU resources quickly when needed. Overall, it delivers a powerful and secure solution for running AI workloads at scale. -
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WhiteFiber
WhiteFiber
WhiteFiber is a vertically integrated AI infrastructure platform offering high-performance GPU cloud and HPC colocation solutions tailored for AI/ML workloads. Its cloud platform is purpose-built for machine learning, large language models, and deep learning, featuring NVIDIA H200, B200, and GB200 GPUs, ultra-fast Ethernet and InfiniBand networking, and up to 3.2 Tb/s GPU fabric bandwidth. WhiteFiber's infrastructure supports seamless scaling from hundreds to tens of thousands of GPUs, with flexible deployment options including bare metal, containers, and virtualized environments. It ensures enterprise-grade support and SLAs, with proprietary cluster management, orchestration, and observability software. WhiteFiber's data centers provide AI and HPC-optimized colocation with high-density power, direct liquid cooling, and accelerated deployment timelines, along with cross-data center dark fiber connectivity for redundancy and scale. -
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IREN Cloud
IREN
IREN’s AI Cloud is a GPU-cloud platform built on NVIDIA reference architecture and non-blocking 3.2 TB/s InfiniBand networking, offering bare-metal GPU clusters designed for high-performance AI training and inference workloads. The service supports a range of NVIDIA GPU models with specifications such as large amounts of RAM, vCPUs, and NVMe storage. The cloud is fully integrated and vertically controlled by IREN, giving clients operational flexibility, reliability, and 24/7 in-house support. Users can monitor performance metrics, optimize GPU spend, and maintain secure, isolated environments with private networking and tenant separation. It allows deployment of users’ own data, models, frameworks (TensorFlow, PyTorch, JAX), and container technologies (Docker, Apptainer) with root access and no restrictions. It is optimized to scale for demanding applications, including fine-tuning large language models. -
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Axe Compute
Axe Compute
Axe Compute delivers enterprise bare-metal GPU infrastructure for AI and machine learning workloads with global reach, dedicated clusters, and predictable access. It gives teams dedicated GPU clusters delivered in approximately 48 hours across 200+ locations, with full choice across region, GPU type, fabric, interconnect, and topology. It is built to address the hidden cost of scaling AI: provisioning delays, limited cloud availability, quota rejections, rigid provider economics, data movement costs, and performance loss from virtualization. Axe provides 100% bare-metal access with zero virtualization overhead and no noisy neighbors, helping teams run LLM training, inference, diffusion, fine-tuning, enterprise deployment, and other AI workloads with more control. Its distributed GPU backbone supports low-latency placement near users and data, reducing the need to move data into centralized cloud regions. -
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Amazon EC2 Capacity Blocks for ML enable you to reserve accelerated compute instances in Amazon EC2 UltraClusters for your machine learning workloads. This service supports Amazon EC2 P5en, P5e, P5, and P4d instances, powered by NVIDIA H200, H100, and A100 Tensor Core GPUs, respectively, as well as Trn2 and Trn1 instances powered by AWS Trainium. You can reserve these instances for up to six months in cluster sizes ranging from one to 64 instances (512 GPUs or 1,024 Trainium chips), providing flexibility for various ML workloads. Reservations can be made up to eight weeks in advance. By colocating in Amazon EC2 UltraClusters, Capacity Blocks offer low-latency, high-throughput network connectivity, facilitating efficient distributed training. This setup ensures predictable access to high-performance computing resources, allowing you to plan ML development confidently, run experiments, build prototypes, and accommodate future surges in demand for ML applications.
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Targon
Manifold Labs
Targon is a confidential compute cloud for scaling workloads with high-speed GPUs and CPUs for AI training and deployments. It provides secure GPUs on lightning-fast infrastructure, with an easy-to-use API, SDK, and CLI for managing workloads across rentals, serverless apps, persistent volumes, web endpoints, and LLM inference. Targon is built around confidential compute without compromise, using a decentralized compute network of trusted execution environments. Its Targon Virtual Machine keeps data confidential with hardware-backed protection powered by Intel TDX, while NVIDIA Confidential Computing and NVIDIA PCIe Confidentiality help protect data on untrusted hardware. Users can deploy confidential compute, connect to a GPU server with configured SSH keys, or use serverless containers that automatically scale up and down based on traffic. -
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Confidential AI
Confidential AI
Confidential AI provides private inference, private agents, confidential VMs and confidential computing infrastructure for AI labs, inference providers, routers, and organizations handling sensitive workloads. Its hosted inference service runs open-weight models in hardware-backed trusted execution environments (TEEs), including Intel TDX and AMD SEV-SNP confidential VMs with NVIDIA GPUs in confidential computing mode. Prompts, responses, and workload data are protected from infrastructure operators, and clients can verify attestation before sending sensitive input. Customers can use an OpenAI-compatible API to deploy inference endpoints and agent workloads, or license the confidential-computing stack for on-premises infrastructure, bare metal, and major clouds. Use cases include serving models while limiting operator access to prompts and model assets, and running sensitive AI workloads on dedicated confidential compute.Starting Price: $0.30 per 1M input tokens -
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Sesterce
Sesterce
Sesterce Cloud offers the seamless and simplest way to launch a GPU Cloud instance, in bare-metal or virtualized mode. Our platform is tailored to allow early-stage teams to collaborate, for training or deploying AI solutions through a large range of NVIDIA and AMD products and optimized pricing, in over 50 regions worldwide. We also offer packaged, turnkey AI solutions for companies that want to rapidly deploy tools to automate their processes, or develop new sources of growth. All with integrated customer support, 99.9% uptime, unlimited storage capacity.Starting Price: $0.30/GPU/hr -
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packet.ai
packet.ai
packet.ai is a GPU cloud platform built to give developers and AI teams fast access to high-performance computing without the complexity and inefficiencies of traditional cloud infrastructure. It provides on-demand GPU instances, including modern NVIDIA hardware, that can be launched in seconds and accessed through tools like SSH, Jupyter, or VS Code, enabling users to quickly start training models, running inference, or experimenting with AI workloads. It introduces a different approach to GPU usage by dynamically allocating resources based on real-time workload demands, rather than treating a GPU as a fixed unit, allowing multiple compatible workloads to share hardware efficiently while maintaining predictable performance. This results in higher utilization and eliminates the need to pay for idle capacity, focusing instead on the exact compute resources consumed. packet.ai also offers an OpenAI-compatible API for language model inference, embeddings, and fine-tuning, etc.Starting Price: $0.39/hour -
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Lium
lium.io
Agent-first GPU cloud. Rent NVIDIA GPUs via web, CLI, SDK, or API. Providers earn 95% rental revenue + bonuses. lium.io connects developers, research teams and AI agents with independent GPU providers. Rent a single GPU or a full 8-GPU node for training, fine-tuning, inference and batch jobs, with SSH and Jupyter access. Deploy through the web, CLI, Python SDK, API or MCP integration. Billing is per second, with usage-based marketplace prices and no minimum commitment. View live rates and availability on the live pricing page; prices change with supply. Choose Secure or Spot GPU capacity to fit your workload. New accounts can receive $5 of credit after passing signup checks. Have idle GPUs? Set your own rental prices and list capacity in the provider portal. Documentation and developer guides are available.Starting Price: $0.40 per GPU per hour -
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GPU.ai
GPU.ai
GPU.ai is a cloud platform specialized in GPU infrastructure tailored to AI workloads. It offers two main products: GPU Instance, letting users launch compute instances with recent NVIDIA GPUs (for tasks like training, fine-tuning, and inference), and model inference, where you upload your pre-built models and GPU.ai handles deployment. The hardware options include H200s and A100s. It also supports custom requests via sales, with fast responses (within ~15 minutes) for more specialized GPU or workflow needs.Starting Price: $2.29 per hour -
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AIC Cloud
AIC Cloud
AIC Cloud is a global cloud hosting platform serving developers, startups, and small businesses across Asia, Africa, Europe, and North America. Linux VPS from $1.19/month on NVMe SSD with full root access, bare-metal dedicated servers from $22/month, NVIDIA cloud GPU instances (RTX 3090, RTX 4090, A100) billed per minute from $0.14/hour, business email with custom domains, and one-click app deployment. What separates AIC Cloud: flat monthly pricing - the rate you sign up at is the rate you pay every month, per-minute GPU billing with no hourly minimums, real-human WhatsApp and email support, multi-region datacenters across Asia Pacific, Europe, and North America with anti-DDoS protection on every plan, and multiple payment methods including UPI, international cards, and net banking. Built by Applied Intelligence Corporation, a bootstrapped technology company - operating since 2024.Starting Price: $1/month -
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Charg
Charg
Charg is an AI infrastructure lifecycle platform that transforms proven enterprise-grade supercomputing systems into scalable AI and high-performance computing cloud environments. Its public HPC cloud provides access to anything from a single GPU to a full 60+ PFLOPS cluster, giving teams supercomputing power without owning or managing the underlying hardware. It redeploys hyperscaler-class CRAY supercomputers and mature NVIDIA DGX architecture, combining clustered NVIDIA V100 GPUs with 200 GbE InfiniBand networking and petabytes of high-density all-flash CEPH storage for low-latency, high-throughput performance. Charg is built for demanding AI, scientific research, and engineering workloads, including model training, scaled inference, simulations, advanced data analysis, finite element analysis, and computational fluid dynamics. Its API-driven infrastructure scales with existing workflows and supports on-demand capacity without the operational restrictions.Starting Price: $0.99 per hour -
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Oracle Cloud Infrastructure provides fast, flexible, and affordable compute capacity to fit any workload need from performant bare metal servers and VMs to lightweight containers. OCI Compute provides uniquely flexible VM and bare metal instances for optimal price-performance. Select exactly the number of cores and the memory your applications need. Delivering high performance for enterprise workloads. Simplify application development with serverless computing. Your choice of technologies includes Kubernetes and containers. NVIDIA GPUs for machine learning, scientific visualization, and other graphics processing. Capabilities such as RDMA, high-performance storage, and network traffic isolation. Oracle Cloud Infrastructure consistently delivers better price performance than other cloud providers. Virtual machine-based (VM) shapes offer customizable core and memory combinations. Customers can optimize costs by choosing a specific number of cores.Starting Price: $0.007 per hour
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NVIDIA Confidential Computing secures data in use, protecting AI models and workloads as they execute, by leveraging hardware-based trusted execution environments built into NVIDIA Hopper and Blackwell architectures and supported platforms. It enables enterprises to deploy AI training and inference, whether on-premises, in the cloud, or at the edge, with no changes to model code, while ensuring the confidentiality and integrity of both data and models. Key features include zero-trust isolation of workloads from the host OS or hypervisor, device attestation to verify that only legitimate NVIDIA hardware is running the code, and full compatibility with shared or remote infrastructure for ISVs, enterprises, and multi-tenant environments. By safeguarding proprietary AI models, inputs, weights, and inference activities, NVIDIA Confidential Computing enables high-performance AI without compromising security or performance.
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Mistral Compute
Mistral
Mistral Compute is a purpose-built AI infrastructure platform that delivers a private, integrated stack, GPUs, orchestration, APIs, products, and services, in any form factor, from bare-metal servers to fully managed PaaS. Designed to democratize frontier AI beyond a handful of providers, it empowers sovereigns, enterprises, and research institutions to architect, own, and optimize their entire AI environment, training, and serving any workload on tens of thousands of NVIDIA-powered GPUs using reference architectures managed by experts in high-performance computing. With support for region- and domain-specific efforts, defense technology, pharmaceutical discovery, financial markets, and more, it offers four years of operational lessons, built-in sustainability through decarbonized energy, and full compliance with stringent European data-sovereignty regulations. -
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NVIDIA DGX Cloud Lepton
NVIDIA
NVIDIA DGX Cloud Lepton is an AI platform that connects developers to a global network of GPU compute across multiple cloud providers through a single platform. It offers a unified experience to discover and utilize GPU resources, along with integrated AI services to streamline the deployment lifecycle across multiple clouds. Developers can start building with instant access to NVIDIA’s accelerated APIs, including serverless endpoints, prebuilt NVIDIA Blueprints, and GPU-backed compute. When it’s time to scale, DGX Cloud Lepton powers seamless customization and deployment across a global network of GPU cloud providers. It enables frictionless deployment across any GPU cloud, allowing AI applications to be deployed across multi-cloud and hybrid environments with minimal operational burden, leveraging integrated services for inference, testing, and training workloads. -
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Impossible Cloud
Impossible Cloud
Impossible Cloud is an enterprise cloud platform that delivers high-performance object storage, dedicated bare metal GPU servers, and managed AI infrastructure for data-intensive workloads. Its S3-compatible object storage provides scalable cloud storage with enterprise security, high availability, and transparent pricing that eliminates egress fees and vendor lock-in. The platform also offers dedicated bare metal GPU servers that provide direct hardware access without virtualization, enabling maximum performance for AI training and inference workloads. Managed AI services include LLM inference, model deployment, Kubernetes, and high-performance computing to simplify AI infrastructure management. Impossible Cloud emphasizes enterprise-grade security through ISO 27001, SOC 2, GDPR compliance, encryption, and customer-controlled access to data.Starting Price: $7.99 per month -
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Massed Compute
Massed Compute
Massed Compute offers high-performance GPU computing solutions tailored for AI, machine learning, scientific simulations, and data analytics. As an NVIDIA Preferred Partner, it provides access to a comprehensive catalog of enterprise-grade NVIDIA GPUs, including A100, H100, L40, and A6000, ensuring optimal performance for various workloads. Users can choose between bare metal servers for maximum control and performance or on-demand compute instances for flexibility and scalability. Massed Compute's Inventory API allows seamless integration of GPU resources into existing business platforms, enabling provisioning, rebooting, and management of instances with ease. Massed Compute's infrastructure is housed in Tier III data centers, offering consistent uptime, advanced redundancy, and efficient cooling systems. With SOC 2 Type II compliance, the platform ensures high standards of security and data protection.Starting Price: $21.60 per hour -
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Core Scientific
Core Scientific
Core Scientific delivers purpose-built high-density colocation infrastructure and intelligent software solutions designed for demanding compute workloads such as AI, machine learning, high-performance computing, and digital asset mining. It features ready-to-scale high-density compute environments with contracted power capacity of over 1.3 GW, faster deployment timelines, and optimized cooling and power systems tailored for intensive workloads. Core Scientific’s digital mining offering incorporates proprietary software for fleet management capable of handling up to one million miners, real-time thermal monitoring, and hash-price economics analysis to optimize profitability. In its colocation and AI-focused infrastructure business, Core Scientific combines high-density racks (50–200 kW+ per rack) and enterprise-grade infrastructure to support AI model training/inference, cloud workloads, financial services analytics, government mission-critical systems, and healthcare research. -
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Cantech
Cantech
Cantech Networks Private Limited has been delivering IT infrastructure and hosting solutions since 2009, supporting startups and enterprises across India and international markets. Its services include dedicated servers, bare metal servers, VPS hosting, cloud infrastructure, NVIDIA GPU servers, and managed IT services. With Tier-certified data centers in India and a presence across 10+ global locations, Cantech focuses on dependable performance, backed by 99.97% uptime and 24/7 technical support. The company has deployed over 3,000 servers and hosts more than 60,000 websites, earning a 4.7+ rating on Trustpilot for its reliability and service quality. From scalable cloud infrastructure and GPU hosting to AWS and Azure managed services and colocation, Cantech helps businesses build and expand their IT infrastructure with transparent pricing and carrier-neutral connectivity.Starting Price: ₹659/month -
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NVIDIA Run:ai
NVIDIA
NVIDIA Run:ai is an enterprise platform designed to optimize AI workloads and orchestrate GPU resources efficiently. It dynamically allocates and manages GPU compute across hybrid, multi-cloud, and on-premises environments, maximizing utilization and scaling AI training and inference. The platform offers centralized AI infrastructure management, enabling seamless resource pooling and workload distribution. Built with an API-first approach, Run:ai integrates with major AI frameworks and machine learning tools to support flexible deployment anywhere. It also features a powerful policy engine for strategic resource governance, reducing manual intervention. With proven results like 10x GPU availability and 5x utilization, NVIDIA Run:ai accelerates AI development cycles and boosts ROI. -
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VMoHost
VMoHost
VMoHost is a dedicated server and colocation provider based in the United States that offers high-performance hosting infrastructure for businesses and individuals. The platform specializes in bare-metal dedicated servers, GPU servers, and global colocation services designed to deliver reliability and scalability. With deployment available within 24–48 hours, customers can quickly launch powerful servers in over 250 data center locations worldwide. VMoHost provides flexible server configurations that allow users to customize RAM, storage, bandwidth, and hardware to meet specific application requirements. Its infrastructure is powered by trusted hardware brands such as Dell, HP, Supermicro, IBM, and Toshiba, ensuring strong performance and stability. The company also offers advanced GPU servers equipped with leading NVIDIA and AMD graphics cards to support demanding workloads like AI, rendering, gaming, and big data analysis.Starting Price: $39/month -
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Rafay
Rafay
Founded in 2017, Rafay transforms compute infrastructure into AI platforms, self-service cloud environments, and revenue-generating services — for enterprises, neoclouds, and sovereign AI clouds. From the moment hardware is racked — GPUs, VMs, bare metal, or any compute type — Rafay makes it immediately productive. Enterprises get developer self-service, AI workload delivery, and governance at scale. Cloud providers and sovereign clouds get the complete platform to launch AI services and monetize compute investment, including Token Factory for token-metered AI delivery and SLURM-as-a-Service for elastic HPC. Rafay is the only NVIDIA-certified reference architecture for GPU infrastructure delivery. GigaOm Leader and Outperformer, Kubernetes and AI Infrastructure Management, 2025. -
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Lambda
Lambda.ai
Lambda provides high-performance supercomputing infrastructure built specifically for training and deploying advanced AI systems at massive scale. Its Superintelligence Cloud integrates high-density power, liquid cooling, and state-of-the-art NVIDIA GPUs to deliver peak performance for demanding AI workloads. Teams can spin up individual GPU instances, deploy production-ready clusters, or operate full superclusters designed for secure, single-tenant use. Lambda’s architecture emphasizes security and reliability with shared-nothing designs, hardware-level isolation, and SOC 2 Type II compliance. Developers gain access to the world’s most advanced GPUs, including NVIDIA GB300 NVL72, HGX B300, HGX B200, and H200 systems. Whether testing prototypes or training frontier-scale models, Lambda offers the compute foundation required for superintelligence-level performance. -
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TensorHost
GPU Server Hosts
TensorHost provides GPU compute directly from infrastructure it owns and operates, rather than brokering capacity from third-party hosts. Customers request the workload, GPU requirements, quantity, and timing; service specifications and location are confirmed before an allocation is agreed. The service makes NVIDIA GPU capacity available for AI and other GPU-intensive computing workloads. TensorHost operates the underlying infrastructure, while customers use the provisioned compute for their own applications and workloads. It is intended for developers, AI teams, and organizations that need hosted GPU resources without purchasing and maintaining the underlying GPU servers. Compute is billed according to usage, with capacity and pricing arranged for the requested allocation.Starting Price: $0.50/GPU-hour -
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Radiant
Radiant
Radiant is a fully integrated AI infrastructure platform designed to deliver end-to-end capabilities for building and scaling AI systems. It combines compute, software, energy, and capital into a unified ecosystem, enabling organizations to move from concept to deployment efficiently. Radiant’s AI Cloud includes NVIDIA-accelerated computing along with MLOps tools such as inference, fine-tuning, model registry, and serverless Kubernetes. Its proprietary software platform supports intelligent scheduling, automated node management, and secure multi-tenancy for large-scale operations. With infrastructure designed to scale from thousands to over 100,000 GPUs, Radiant ensures consistent performance and operational control. The platform also integrates energy solutions through its powered-land portfolio, optimizing costs and sustainability. Backed by significant capital resources, Radiant can support large-scale AI initiatives globally.Starting Price: $3.24 per month -
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NVIDIA Brev
NVIDIA
NVIDIA Brev is a cloud-based platform that provides instant access to fully configured GPU environments optimized for AI and machine learning development. Its Launchables feature offers prebuilt, customizable compute setups that let developers start projects quickly without complex setup or configuration. Users can create Launchables by specifying GPU resources, Docker images, and project files, then share them easily with collaborators. The platform also offers prebuilt Launchables featuring the latest AI frameworks, microservices, and NVIDIA Blueprints to jumpstart development. NVIDIA Brev provides a seamless GPU sandbox with support for CUDA, Python, and Jupyter Lab accessible via browser or CLI. This enables developers to fine-tune, train, and deploy AI models with minimal friction and maximum flexibility.Starting Price: $0.04 per hour -
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NetMind AI
NetMind AI
NetMind.AI is a decentralized computing platform and AI ecosystem designed to accelerate global AI innovation. By leveraging idle GPU resources worldwide, it offers accessible and affordable AI computing power to individuals, businesses, and organizations of all sizes. The platform provides a range of services, including GPU rental, serverless inference, and an AI ecosystem that encompasses data processing, model training, inference, and agent development. Users can rent GPUs at competitive prices, deploy models effortlessly with on-demand serverless inference, and access a wide array of open-source AI model APIs with high-throughput, low-latency performance. NetMind.AI also enables contributors to add their idle GPUs to the network, earning NetMind Tokens (NMT) as rewards. These tokens facilitate transactions on the platform, allowing users to pay for services such as training, fine-tuning, inference, and GPU rentals. -
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HPC-AI
HPC-AI
HPC-AI is an enterprise AI infrastructure and GPU cloud platform designed to accelerate deep learning training, inference, and large-scale compute workloads with high performance and cost efficiency. It delivers a pre-configured AI-optimized stack that enables rapid deployment and real-time inference while supporting demanding workloads that require high IOPS, ultra-low latency, and massive throughput. It provides a robust GPU cloud environment built for artificial intelligence, high-performance computing, and other compute-intensive applications, giving teams the tools needed to run complex workflows efficiently. At its core, the company’s software focuses on parallel and distributed training, inference, and fine-tuning of large neural networks, helping organizations reduce infrastructure costs while maintaining performance. It is powered in part by technologies such as Colossal-AI, which significantly accelerates model training and improves productivity.Starting Price: $3.05 per hour -
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Arc Compute
Arc Compute
Choosing the right GPUs and deployment strategy can be complex. Whether you're considering on-premises setups or cloud solutions, Arc Compute provides expert guidance to streamline your infrastructure planning and maximize performance. At Arc Compute, we start by understanding your specific AI or HPC objectives. Our team then crafts customized GPU infrastructure solutions—be it short-term rentals for peak demands or dedicated clusters for ongoing training needs. In-depth consultations to identify optimal GPU configurations and deployment models (cloud, on-premises, or hybrid). Efficient sourcing and delivery of NVIDIA GPU servers, managing all vendor interactions. Seamless installation and ongoing support to ensure peak performance of your GPU infrastructure. Our hands-on, consultative approach ensures you get the best mix of performance, cost efficiency, and scalability. -
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Tencent Cloud GPU Service
Tencent
Cloud GPU Service is an elastic computing service that provides GPU computing power with high-performance parallel computing capabilities. As a powerful tool at the IaaS layer, it delivers high computing power for deep learning training, scientific computing, graphics and image processing, video encoding and decoding, and other highly intensive workloads. Improve your business efficiency and competitiveness with high-performance parallel computing capabilities. Set up your deployment environment quickly with auto-installed GPU drivers, CUDA, and cuDNN and preinstalled driver images. Accelerate distributed training and inference by using TACO Kit, an out-of-the-box computing acceleration engine provided by Tencent Cloud.Starting Price: $0.204/hour -
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Compute Exchange
Compute Exchange
Compute Exchange is a web-based marketplace for organizations sourcing GPU infrastructure. It brings together reserved cloud GPU capacity, data-center hardware and forward compute contracts in one place. Buyers can specify GPU model, quantity, region and term, review provider quotes and compare availability, pricing and service-level terms across participating suppliers. For hardware, the marketplace matches buyers and sellers of used and refurbished data-center GPUs, while verified counterparties negotiate transactions directly. For reserved capacity, it aggregates offers from cloud providers; Compute Exchange does not operate the compute itself. The service is designed for AI labs, startups, enterprises, data centers and other institutional buyers and sellers seeking GPU capacity or hardware for AI and machine-learning workloads.Starting Price: $1.10/GPU/hour -
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CoreSite
CoreSite
A colocation data center is a physical facility that offers space with the proper power, cooling and security to host businesses’ computing hardware and servers. This capacity includes anything from cabinets to cages or private suites. Often, colocation providers lease space to various tenants looking for colocation services – including network providers, cloud providers, and enterprises. These tenants can then interconnect to one another within the colocation data center and do business together. This allows businesses to centralize their IT operations and create an efficient architecture that can reduce costs. Colocation facilities should be able to support your future growth. Whether you start small and need to expand, move into a new market, have a build-to-suit requirement, or need to connect to the cloud, we work hard to find solutions to support nearly any need. -
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Amazon EC2 G4 Instances
Amazon
Amazon EC2 G4 instances are optimized for machine learning inference and graphics-intensive applications. It offers a choice between NVIDIA T4 GPUs (G4dn) and AMD Radeon Pro V520 GPUs (G4ad). G4dn instances combine NVIDIA T4 GPUs with custom Intel Cascade Lake CPUs, providing a balance of compute, memory, and networking resources. These instances are ideal for deploying machine learning models, video transcoding, game streaming, and graphics rendering. G4ad instances, featuring AMD Radeon Pro V520 GPUs and 2nd-generation AMD EPYC processors, deliver cost-effective solutions for graphics workloads. Both G4dn and G4ad instances support Amazon Elastic Inference, allowing users to attach low-cost GPU-powered inference acceleration to Amazon EC2 and reduce deep learning inference costs. They are available in various sizes to accommodate different performance needs and are integrated with AWS services such as Amazon SageMaker, Amazon ECS, and Amazon EKS. -
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Voltage Park
Voltage Park
Voltage Park is a next-generation GPU cloud infrastructure provider, offering on-demand and reserved access to NVIDIA HGX H100 GPUs housed in Dell PowerEdge XE9680 servers, each equipped with 1TB of RAM and v52 CPUs. Their six Tier 3+ data centers across the U.S. ensure high availability and reliability, featuring redundant power, cooling, network, fire suppression, and security systems. A state-of-the-art 3200 Gbps InfiniBand network facilitates high-speed communication and low latency between GPUs and workloads. Voltage Park emphasizes uncompromising security and compliance, utilizing Palo Alto firewalls and rigorous protocols, including encryption, access controls, monitoring, disaster recovery planning, penetration testing, and regular audits. With a massive inventory of 24,000 NVIDIA H100 Tensor Core GPUs, Voltage Park enables scalable compute access ranging from 64 to 8,176 GPUs.Starting Price: $1.99 per hour -
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FPT Cloud
FPT Cloud
FPT Cloud is a next‑generation cloud computing and AI platform that streamlines innovation by offering a robust, modular ecosystem of over 80 services, from compute, storage, database, networking, and security to AI development, backup, disaster recovery, and data analytics, built to international standards. Its offerings include scalable virtual servers with auto‑scaling and 99.99% uptime; GPU‑accelerated infrastructure tailored for AI/ML workloads; FPT AI Factory, a comprehensive AI lifecycle suite powered by NVIDIA supercomputing (including infrastructure, model pre‑training, fine‑tuning, model serving, AI notebooks, and data hubs); high‑performance object and block storage with S3 compatibility and encryption; Kubernetes Engine for managed container orchestration with cross‑cloud portability; managed database services across SQL and NoSQL engines; multi‑layered security with next‑gen firewalls and WAFs; centralized monitoring and activity logging. -
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Core42
Core42
Core42 delivers sovereign AI and cloud solutions that help individuals, enterprises, and nations unlock the full potential of AI through secure, scalable, and performance-driven infrastructure. Its AI Cloud is a full-stack platform built for the entire intelligence lifecycle, from data movement and training to optimization, fine-tuning, deployment, governance, and production inference. It gives AI builders access to leading accelerators, integrated tools, orchestration, high-performance storage, and expert support so they can train, fine-tune, and deploy agentic and inference workloads faster. Core42 AI Cloud supports GenAI services, model hosting and inference, AI operations, and infrastructure as a service, enabling teams to build and scale next-generation AI applications with confidence and speed. Its GenAI services help accelerate innovation with agents, retrieval-augmented generation, guardrails, and fine-tuning. -
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OpenGPU
OpenGPU
OpenGPU Network is a decentralized GPU compute platform that connects users who need high-performance computing power with a global network of independent GPU providers, enabling AI inference, machine learning training, rendering, and other intensive workloads to run across distributed infrastructure instead of centralized cloud services. It acts as a global routing layer that automatically matches workloads with available GPU capacity worldwide, allowing tasks to be executed instantly without managing infrastructure or dealing with region limits, queues, or provisioning delays. It addresses the growing imbalance between high demand for GPUs and fragmented, underutilized supply by aggregating resources from data centers, cloud providers, and individual machines into a single network. OpenGPU operates on a blockchain-based system that coordinates task execution, verifies results, and distributes rewards, creating a trustless environment. -
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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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Verda
Verda
Verda is a frontier AI cloud platform delivering premium GPU servers, clusters, and model inference services powered by NVIDIA®. Built for speed, scalability, and simplicity, Verda enables teams to deploy AI workloads in minutes with pay-as-you-go pricing. The platform offers on-demand GPU instances, custom-managed clusters, and serverless inference with zero setup. Verda provides instant access to high-performance NVIDIA Blackwell GPUs, including B200 and GB300 configurations. All infrastructure runs on 100% renewable energy, supporting sustainable AI development. Developers can start, stop, or scale resources instantly through an intuitive dashboard or API. Verda combines dedicated hardware, expert support, and enterprise-grade security to deliver a seamless AI cloud experience.Starting Price: $3.01 per hour -
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TensorWave
TensorWave
TensorWave is an AI and high-performance computing (HPC) cloud platform purpose-built for performance, powered exclusively by AMD Instinct Series GPUs. It delivers high-bandwidth, memory-optimized infrastructure that scales with your most demanding models, training, or inference. TensorWave offers access to AMD’s top-tier GPUs within seconds, including the MI300X and MI325X accelerators, which feature industry-leading memory capacity and bandwidth, with up to 256GB of HBM3E supporting 6.0TB/s. TensorWave's architecture includes UEC-ready capabilities that optimize the next generation of Ethernet for AI and HPC networking, and direct liquid cooling that delivers exceptional total cost of ownership with up to 51% data center energy cost savings. TensorWave provides high-speed network storage, ensuring game-changing performance, security, and scalability for AI pipelines. It offers plug-and-play compatibility with a wide range of tools and platforms, supporting models, libraries, etc. -
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hosted·ai
hosted·ai
hosted·ai is a turnkey neocloud platform for turning servers and GPUs into efficient, profitable AI cloud infrastructure and services. It combines GPU orchestration, monetization, and neocloud operations while software-defining GPU resources to enable true multi-tenancy, dynamic scheduling, capacity sharing, and configurable overcommit. GPU pools can support shared or dedicated use cases, with isolated workloads, adaptive scheduling, and flexible allocation designed to push utilization toward 100% and serve more customers per GPU. It supports elastic GPUaaS, bare metal GPU servers, GPU-enabled virtual machines, AI as a service, model libraries, bring-your-own-model deployments, tokenized AI workloads, and traditional CPU, storage, and networking services. GPU Mesh adds wholesale capacity on demand and gives infrastructure owners another channel for selling idle resources.Starting Price: $750 per month -
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Nebius
Nebius
Training-ready platform with NVIDIA® H100 Tensor Core GPUs. Competitive pricing. Dedicated support. Built for large-scale ML workloads: Get the most out of multihost training on thousands of H100 GPUs of full mesh connection with latest InfiniBand network up to 3.2Tb/s per host. Best value for money: Save at least 50% on your GPU compute compared to major public cloud providers*. Save even more with reserves and volumes of GPUs. Onboarding assistance: We guarantee a dedicated engineer support to ensure seamless platform adoption. Get your infrastructure optimized and k8s deployed. Fully managed Kubernetes: Simplify the deployment, scaling and management of ML frameworks on Kubernetes and use Managed Kubernetes for multi-node GPU training. Marketplace with ML frameworks: Explore our Marketplace with its ML-focused libraries, applications, frameworks and tools to streamline your model training. Easy to use. We provide all our new users with a 1-month trial period.Starting Price: $2.66/hour
