Alternatives to Compute Exchange
Compare Compute Exchange alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Compute Exchange in 2026. Compare features, ratings, user reviews, pricing, and more from Compute Exchange competitors and alternatives in order to make an informed decision for your business.
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Google Compute Engine
Google
Compute Engine is Google's infrastructure as a service (IaaS) platform for organizations to create and run cloud-based virtual machines. Computing infrastructure in predefined or custom machine sizes to accelerate your cloud transformation. General purpose (E2, N1, N2, N2D) machines provide a good balance of price and performance. Compute optimized (C2) machines offer high-end vCPU performance for compute-intensive workloads. Memory optimized (M2) machines offer the highest memory and are great for in-memory databases. Accelerator optimized (A2) machines are based on the A100 GPU, for very demanding applications. Integrate Compute with other Google Cloud services such as AI/ML and data analytics. Make reservations to help ensure your applications have the capacity they need as they scale. Save money just for running Compute with sustained-use discounts, and achieve greater savings when you use committed-use discounts. -
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Amazon EC2
Amazon
Amazon Elastic Compute Cloud (Amazon EC2) is a web service that provides secure, resizable compute capacity in the cloud. It is designed to make web-scale cloud computing easier for developers. Amazon EC2’s simple web service interface allows you to obtain and configure capacity with minimal friction. It provides you with complete control of your computing resources and lets you run on Amazon’s proven computing environment. Amazon EC2 delivers the broadest choice of compute, networking (up to 400 Gbps), and storage services purpose-built to optimize price performance for ML projects. Build, test, and sign on-demand macOS workloads. Access environments in minutes, dynamically scale capacity as needed, and benefit from AWS’s pay-as-you-go pricing. Access the on-demand infrastructure and capacity you need to run HPC applications faster and cost-effectively. Amazon EC2 delivers secure, reliable, high-performance, and cost-effective compute infrastructure to meet demanding business needs. -
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Latitude.sh
Latitude.sh
Everything that you need to deploy and manage single-tenant, high-performance bare metal servers. If you are used to VMs, Latitude.sh will make you feel right at home — but with a lot more computing power. Get the speed of a dedicated physical server and the flexibility of the cloud—deploy instantly and manage your servers through the Control Panel or our powerful API. Hardware and connectivity solutions specific to your needs, while you still benefit from all the automation Latitude.sh is built on. Power your team with a robust, easy-to-use control panel, which you can use to view and change your infrastructure in real time. If you're like most of our customers, you're looking at Latitude.sh to run mission-critical services where uptime and latency are extremely important. We built our own private data center, so we know what great infrastructure looks like.Starting Price: $100/month/server -
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Kamatera
Kamatera
With our comprehensive suite of scalable cloud services, you can build your cloud server, your way. Kamatera’s infrastructure specializes in VPS hosting, with a choice of 24 data centers worldwide, including 8 data centers across the US as well as locations in Europe, Asia, and the Middle East. Our enterprise-grade cloud servers can meet your needs at every stage. We use cutting-edge hardware, such as Ice Lake Processors and NVMe SSD, to deliver consistent speed and 99.95% uptime. With a robust service like ours, you can expect plenty of great features, such as fantastic hardware, flexible and scalable cloud setup, fully managed hosting, windows server hosting, data security and safety, consultation, server migration, and disaster recovery. Our technical staff is always on duty, with 24/7 live support to assist you across all time zones. And our flexible, predictable pricing plans means you’ll only pay for what you use with our hourly or monthly billing options.Starting Price: $4 per month -
5
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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Pacific
Pacific Intelligent Technologies
Pacific provides GPU compute rental and modular AI infrastructure for organizations running AI training, fine-tuning and inference. Its catalog offers on-demand dedicated NVIDIA GPU nodes, including H100, H200 and B200 configurations, with larger systems and reserved capacity available by request. Rentals provide SSH access to bare-metal Linux hosts with NVIDIA drivers and CUDA. For longer-term or site-specific needs, Pacific offers reserved single-tenant clusters, managed on-premises deployments, colocation and bridge capacity while a permanent facility is prepared. Its factory-built modules combine compute, networking, cooling and power distribution for customer sites, colocation facilities or other suitable powered locations. Buyers include AI teams and infrastructure operators evaluating training or inference capacity, as well as organizations requiring greater control over compute deployment.Starting Price: $2.99/GPU-hour -
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airgpu
Stackprint
airgpu provides rented GPU-powered cloud computers for gaming and graphics-intensive tasks. Customers create a cloud PC, choose a hardware configuration and data-center location, then connect using Parsec or Moonlight. Unlike a fixed game-streaming catalog, the virtual computer lets users install their own games and applications, including software available through Steam and Epic Games Launcher. Typical uses include gaming, 3D rendering, video editing, virtual reality, and other workloads that benefit from a dedicated GPU. Computing is billed by use from account credit, with SSD storage charged separately. Hardware options and availability vary by GPU and region. Some multiplayer games may not work if anti-cheat systems block cloud PCs. airgpu serves gamers, creative professionals, and other users who want remote access to GPU-capable computing without purchasing a local computer.Starting Price: $0.65/hour -
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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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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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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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CUDO Compute
CUDO Compute
CUDO Compute is an enterprise AI infrastructure company delivering large scale GPU capacity on the latest generation hardware for organisations that require predictable, production ready AI environments. Operating at the intersection of Land, Power and Compute, CUDO Compute helps organisations build and scale AI environments with the speed, reliability and engineering expertise required for modern AI workloads. From dedicated GPU clusters and high performance networking to sovereign AI deployments, CUDO enables organisations to move from experimentation to production with confidence. Built on more than 20 years of experience across data centres, cloud operations and high performance computing, CUDO combines deep infrastructure expertise with a track record spanning 40,000+ GPUs globally. This operational heritage underpins how the company designs, deploys and manages large scale AI environments.Starting Price: $1.73 per hour -
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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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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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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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Kinesis Network
Kinesis Network
Kinesis is a unified compute platform that turns fragmented infrastructure across clouds, on-premises systems, edge environments, and partner data centers into one orchestrated grid. Teams can push a GitHub repository, provide a Dockerfile or container image, connect a registry, choose a template, or describe an application, and Kinesis inspects the workload, finds suitable CPU or GPU capacity, and returns a live deployment. Its intent-driven controls let users optimize for cost, reliability, latency, or multi-cloud operation without wiring VPCs, IAM hierarchies, security groups, or other infrastructure plumbing. Standard containers run across providers without rewrites or lock-in, while networking, autoscaling, monitoring, health checks, failover, recovery, certificates, secrets, and rollbacks are built into every deployment. It continuously makes placement, scaling, utilization, and failure-handling decisions across a heterogeneous compute graph. -
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SF Compute
SF Compute
SF Compute is a marketplace platform that offers on-demand access to large-scale GPU clusters, letting users rent powerful compute resources by the hour, not requiring long-term contracts or heavy upfront commitments. You can choose between virtual machine nodes or Kubernetes clusters (with InfiniBand support for high-speed interconnects), and specify the number of GPUs, duration, and start time as needed. It supports flexible “buy blocks” of compute; for example, you might request 256 NVIDIA H100 GPUs for three days at a capped hourly rate, or scale down/up dynamically depending on budget. For Kubernetes clusters, spin-up times are fast (about 0.5 seconds); VMs take around 5 minutes. Storage is robust, including 1.5+ TB NVMe and 1 TB + RAM, and there are no data transfer (ingress/egress) fees, so you don’t pay to move data. SF Compute’s architecture abstracts physical infrastructure behind a real-time spot-market and dynamic scheduler.Starting Price: $1.48 per hour -
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XRCLOUD
XRCLOUD
GPU cloud computing is a GPU-based computing service with real-time, high-speed parallel computing and floating-point computing capacity. It is ideal for various scenarios such as 3D graphics applications, video decoding, deep learning, and scientific computing. GPU instances can be managed just like a standard ECS with speed and ease, which effectively relieves computing pressures. RTX6000 GPU contains thousands of computing units and shows substantial advantages in parallel computing. For optimized deep learning, massive computing can be completed in a short time. GPU Direct seamlessly supports the transmission of big data among networks. Built-in acceleration framework, it can focus on the core tasks by quick deployment and fast instance distribution. We offer optimal cloud performance at a transparent price. The price of our cloud solution is open and cost-effective. You may choose to charge on-demand, and you can also get more discounts by subscribing to resources.Starting Price: $4.13 per month -
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Zhixing Cloud
Zhixing Cloud
Zhixing Cloud is a GPU computing platform offering low-investment cloud computing with no space, electricity, or bandwidth costs, accessible via high-speed fiber optics for unrestricted access. It supports elastic GPU deployment for applications such as AIGC, deep learning, cloud gaming, rendering and mapping, metaverse, and HPC. The platform provides high cost-effectiveness, speed, and flexibility, ensuring that costs are solely directed toward the business itself, alleviating concerns about idle computing power. AI Galaxy offers solutions including computing power cluster construction, digital human development, support for university scientific research, artificial intelligence, metaverse projects, rendering and mapping, and biomedicine. The platform's advantages include continuous hardware updates, open and upgradeable software, integrated services providing a full-stack deep learning environment, and user-friendly operations without the need for installation.Starting Price: $0.10 per hour -
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Shadeform
Shadeform
Shadeform is a GPU cloud marketplace that provides a single platform, unified console, and API for finding, comparing, launching, and managing on-demand GPU instances across numerous cloud providers, making it easier to develop, train, and deploy AI models without juggling multiple accounts or provider interfaces. It lets users view live pricing and availability for GPUs across clouds, launch instances in either their own cloud accounts or in Shadeform-managed accounts, and manage a cross-cloud fleet from one place with standardized tooling such as curl, Python, or Terraform. It aggregates GPU capacity and pricing data so teams can optimize compute spend, deploy containerized workloads with consistent interfaces, centralize billing and account management, and avoid vendor-specific complexity by using a unified API that supports multiple providers. Shadeform also offers scheduling and automated provisioning so that users can secure resources when they become available.Starting Price: $0.15 per hour -
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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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GPUniq
GPUniq
GPUniq is a decentralized GPU cloud platform that aggregates GPUs from multiple global providers into a single, reliable infrastructure for AI training, inference, and high-performance workloads. The platform automatically routes tasks to the best available hardware, optimizes cost and performance, and provides built-in failover to ensure stability even if individual nodes go offline. Unlike traditional hyperscalers, GPUniq removes vendor lock-in and overhead by sourcing compute directly from private GPU owners, data centers, and local rigs. This allows users to access high-end GPUs at up to 3–7× lower cost while maintaining production-level reliability. GPUniq supports on-demand scaling through GPU Burst, enabling instant expansion across multiple providers. With API and Python SDK integration, teams can seamlessly connect GPUniq to their existing AI pipelines, LLM workflows, computer vision systems, and rendering tasks.Starting Price: $5/month -
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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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Dapple
Dapple
Dapple is an Enterprise OS Cloud built for regulated enterprises and AI-native companies that need dedicated AI infrastructure without compromising on isolation, data residency, governance, or performance. It sits between the public cloud and the private data center, combining dedicated, single-tenant GPU infrastructure with orchestration, compliance, connectivity, observability, and operations through one control plane. Topology-aware placement, multi-GPU scheduling, fault-domain isolation, and reserved clusters provide predictable performance without noisy neighbors. Private connectivity extends existing cloud environments directly to dedicated compute, while identity, container orchestration, threat protection, and governance policies continue working across the deployment. Compliance is enforced at the architecture level before workloads execute, supporting in-country data residency, audit requirements, and regulatory frameworks. -
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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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Hathora
Hathora
Hathora is a real-time compute orchestration platform designed to enable high-performance, low-latency applications by aggregating CPUs and GPUs across clouds, edge, and on-prem infrastructure. It supports universal orchestration, letting teams run workloads across their own data centers or Hathora’s global fleet with intelligent load balancing, automatic spill-over, and built-in 99.9% uptime. Edge-compute capabilities ensure sub-50 ms latency worldwide by routing workloads to the closest region, while container-native support allows any Docker-based workload, including GPU-accelerated inference, game servers, or batch compute, to deploy without re-architecture. Data-sovereignty features let organizations enforce region-locked deployments and meet compliance obligations. Use-cases span real-time inference, global game-server hosting, build farms, and elastic “metal” availability, all accessible through a unified API and global observability dashboards.Starting Price: $4 per month -
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Parasail
Parasail
Parasail is an AI deployment network offering scalable, cost-efficient access to high-performance GPUs for AI workloads. It provides three primary services, serverless endpoints for real-time inference, Dedicated instances for private model deployments, and Batch processing for large-scale tasks. Users can deploy open source models like DeepSeek R1, LLaMA, and Qwen, or bring their own, with the platform's permutation engine matching workloads to optimal hardware, including NVIDIA's H100, H200, A100, and 4090 GPUs. Parasail emphasizes rapid deployment, with the ability to scale from a single GPU to clusters within minutes, and offers significant cost savings, claiming up to 30x cheaper compute compared to legacy cloud providers. It supports day-zero availability for new models and provides a self-service interface without long-term contracts or vendor lock-in.Starting Price: $0.80 per million tokens -
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AMD Developer Cloud provides developers and open-source contributors with immediate access to high-performance AMD Instinct MI300X GPUs through a cloud interface, offering a pre-configured environment with Docker containers, Jupyter notebooks, and no local setup required. Developers can run AI, machine-learning, and high-performance-computing workloads on either a small configuration (1 GPU with 192 GB GPU memory, 20 vCPUs, 240 GB system memory, 5 TB NVMe) or a large configuration (8 GPUs, 1536 GB GPU memory, 160 vCPUs, 1920 GB system memory, 40 TB NVMe scratch disk). It supports pay-as-you-go access via linked payment method and offers complimentary hours (e.g., 25 initial hours for eligible developers) to help prototype on the hardware. Users retain ownership of their work and can upload code, data, and software without giving up rights.
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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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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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Elastic GPU Service
Alibaba
Elastic computing instances with GPU computing accelerators suitable for scenarios (such as artificial intelligence (specifically deep learning and machine learning), high-performance computing, and professional graphics processing). Elastic GPU Service provides a complete service system that combines software and hardware to help you flexibly allocate resources, elastically scale your system, improve computing power, and lower the cost of your AI-related business. It applies to scenarios (such as deep learning, video encoding and decoding, video processing, scientific computing, graphical visualization, and cloud gaming). Elastic GPU Service provides GPU-accelerated computing capabilities and ready-to-use, scalable GPU computing resources. GPUs have unique advantages in performing mathematical and geometric computing, especially floating-point and parallel computing. GPUs provide 100 times the computing power of their CPU counterparts.Starting Price: $69.51 per month -
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Hyperbolic
Hyperbolic
Hyperbolic is an open-access AI cloud platform dedicated to democratizing artificial intelligence by providing affordable and scalable GPU resources and AI services. By uniting global compute power, Hyperbolic enables companies, researchers, data centers, and individuals to access and monetize GPU resources at a fraction of the cost offered by traditional cloud providers. Their mission is to foster a collaborative AI ecosystem where innovation thrives without the constraints of high computational expenses.Starting Price: $0.50/hour -
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supercomputer
supercomputer
supercomputer is a hosted cloud-compute service that provides GPU and CPU sessions for machine-learning and other compute-intensive workloads. Developers, researchers, and teams can launch and manage sessions from a command-line interface or Python SDK, run code on configurable GPU instances, and preserve workspace files between sessions. The service supports model training and fine-tuning, inference, experiments, evaluations, batch processing, hyperparameter sweeps, and data-processing jobs. Users can upload scripts and datasets, execute commands in persistent sessions, and retrieve results or save them in shared volumes. Compute charges accrue only while sessions are running, and stopped sessions retain their workspace for later use. The service uses prepaid credits and bills compute by the second, with rates varying by GPU configuration. -
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NVIDIA DGX Cloud
NVIDIA
NVIDIA DGX Cloud offers a fully managed, end-to-end AI platform that leverages the power of NVIDIA’s advanced hardware and cloud computing services. This platform allows businesses and organizations to scale AI workloads seamlessly, providing tools for machine learning, deep learning, and high-performance computing (HPC). DGX Cloud integrates seamlessly with leading cloud providers, delivering the performance and flexibility required to handle the most demanding AI applications. This service is ideal for businesses looking to enhance their AI capabilities without the need to manage physical infrastructure. -
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Medjed AI
Medjed AI
Medjed AI is a next-generation GPU cloud computing platform designed to meet the growing demands of AI developers and enterprises. It provides scalable, high-performance GPU resources optimized for AI training, inference, and other compute-intensive workloads. With flexible deployment options, seamless integration, and cutting-edge hardware, Medjed AI enables organizations to accelerate AI development, reduce time-to-insight, and handle workloads of any scale with efficiency and reliability.Starting Price: $2.39/hour -
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Coreframe Cloud
Coreframe Compute Labs Private Limited
Coreframe Cloud provides Windows GPU workstations for architecture, interior design, 3D visualization, rendering and engineering. Customers connect from a Windows computer using the Coreframe Connect app and work on a desktop with a dedicated NVIDIA RTX GPU. Blender, D5 Render, Twinmotion and Unreal Engine are preinstalled; commercial applications require the customer's own license and can be set up with assistance. On-demand access starts at $1.49 per GPU-hour and is billed by the minute from a prepaid wallet. Team plans with shared hours and storage are also available. Files saved to the project drive remain between sessions, while standard workstation sessions reset to a clean image; an optional persistent workstation retains its Windows disk. Workstations are hosted in a Tier III data center in India. It serves architects, interior designers, 3D artists, visualization studios and engineers who need GPU-intensive software without maintaining workstation hardware.Starting Price: $1.49/GPU-hour -
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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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Weasel.Cloud
Weasel.Cloud
WeaselCloud provides virtual private server (VPS/VDS) hosting for developers, website operators, and organizations that need remotely administered computing resources. Customers choose virtual server configurations with different amounts of processor capacity, memory, SSD storage, and network bandwidth, then use the server for websites, applications, development environments, or other workloads. The service offers a web-based client area for ordering and managing servers and data-center locations in Europe and the United States. Customers select an operating-system image when configuring a server; the current knowledge base lists Linux distributions and describes Windows support as forthcoming. VPS instances give customers control over the software and workloads they install. Plans start with a small configuration and scale to higher resource tiers, with billing cycle options selected during checkout.Starting Price: $3/month -
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Coreshub
Coreshub
Coreshub provides GPU cloud services, AI training clusters, parallel file storage, and image repositories, delivering secure, reliable, and high-performance cloud-based AI training and inference environments. The platform offers a range of solutions, including computing power market, model inference, and various industry-specific applications. Coreshub's core team comprises experts from Tsinghua University, leading AI companies, IBM, renowned venture capital firms, and major internet corporations, bringing extensive AI technical expertise and ecosystem resources. The platform emphasizes an independent and open cooperative ecosystem, actively collaborating with AI model suppliers and hardware manufacturers. Coreshub's AI computing platform enables unified scheduling and intelligent management of diverse heterogeneous computing power, meeting AI computing operation, maintenance, and management needs in a one-stop manner.Starting Price: $0.24 per hour -
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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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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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portvMind Cloud
vMind Information Technologies
portvMind Cloud is a self-service public cloud and infrastructure-as-a-service platform from vMind for deploying application workloads. Through a web console and documented REST API, users can provision virtual servers, attach block storage, create S3-compatible object storage, configure virtual networks, routers, floating IPs and load balancers, and deploy managed Kubernetes clusters. The platform also offers GPU compute, backup services and dedicated cloud resources. Its OpenStack-based infrastructure, Kubernetes, Terraform automation and S3-compatible storage support familiar cloud workflows. Usage-based billing lets customers consume cloud resources as needed. portvMind Cloud is designed for software and infrastructure teams, including development, DevOps, data and AI teams, that need cloud capacity hosted in Türkiye, including workloads with local data-residency requirements. -
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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 -
43
Shadow PC
Shadow
Shadow PC is a high-performance, cloud-based service that delivers virtual Windows computers accessible from any device. This service eliminates the need to purchase expensive hardware for intensive tasks and allows businesses to scale up without buying a fleet of devices. It supports a wide range of uses, from simple productivity apps to demanding applications like 3D modeling and video editing. Accessible from PCs, Macs, smartphones, tablets, and smart TVs, Shadow PC ensures compatibility with a wide range of devices, providing a seamless and powerful computing experience.Starting Price: Essential: $9.99/month/user -
44
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 -
45
Vast.ai
Vast.ai
Vast.ai is the market leader in low-cost cloud GPU rental. Use one simple interface to save 5-6X on GPU compute. Use on-demand rentals for convenience and consistent pricing. Or save a further 50% or more with interruptible instances using spot auction based pricing. Vast has an array of providers that offer different levels of security: from hobbyists up to Tier-4 data centers. Vast.ai helps you find the best pricing for the level of security and reliability you need. Use our command line interface to search the entire marketplace for offers while utilizing scriptable filters and sort options. Launch instances quickly right from the CLI and easily automate your deployment. Save an additional 50% or more by using interruptible instances and auction pricing. The highest bidding instances run; other conflicting instances are stopped.Starting Price: $0.20 per hour -
46
Google Cloud GPUs
Google
Speed up compute jobs like machine learning and HPC. A wide selection of GPUs to match a range of performance and price points. Flexible pricing and machine customizations to optimize your workload. High-performance GPUs on Google Cloud for machine learning, scientific computing, and 3D visualization. NVIDIA K80, P100, P4, T4, V100, and A100 GPUs provide a range of compute options to cover your workload for each cost and performance need. Optimally balance the processor, memory, high-performance disk, and up to 8 GPUs per instance for your individual workload. All with the per-second billing, so you only pay only for what you need while you are using it. Run GPU workloads on Google Cloud Platform where you have access to industry-leading storage, networking, and data analytics technologies. Compute Engine provides GPUs that you can add to your virtual machine instances. Learn what you can do with GPUs and what types of GPU hardware are available.Starting Price: $0.160 per GPU -
47
Xesktop
Xesktop
After the advent of GPU computing and the horizons it expanded in the worlds of Data Science, Programming and Computer Graphics came the need for access to cost-friendly and reliable GPU Server rental services. That’s why we’re here. Our powerful, dedicated GPU servers in the cloud are at your disposal for GPU 3D rendering. Xesktop high-performance servers are perfect for intense rendering workloads. Each server runs on dedicated hardware meaning you’re getting maximum GPU performance and no compromises like on typical Virtual Machines. Maximize the GPU capabilities of engines like Octane, Redshift, Cycles, or any other engine you work with. You can connect to a server or multiple servers using your existing Windows system image at any time. All images that you create are reusable. Use the server as if it were your own personal computer.Starting Price: $6 per hour -
48
GPU Trader
GPU Trader
GPU Trader is a secure, enterprise-class marketplace that connects organizations with high-performance GPUs in on-demand and reserved instance models. It offers instant access to powerful GPUs tailored for AI, machine learning, data analytics, and high-performance compute workloads. With flexible pricing options and instance templates, users can scale effortlessly and pay only for what they use. It ensures complete security with a zero-trust architecture, transparent billing, and real-time performance monitoring. GPU Trader's decentralized architecture maximizes GPU efficiency and scalability with secure workload management across distributed networks. GPU Trader manages workload dispatch and real-time monitoring, while containerized agents on GPUs autonomously execute tasks. AI-driven validation ensures all GPUs meet high-performance standards, providing reliable resources for renters.Starting Price: $0.99 per hour -
49
Phala
Phala
Phala is a hardware-secured cloud platform designed to help organizations deploy confidential AI with verifiable trust and enterprise-grade privacy. Using Trusted Execution Environments (TEEs), Phala ensures that AI models, data, and computations run inside fully isolated, encrypted environments that even cloud providers cannot access. The platform includes pre-configured confidential AI models, confidential VMs, and GPU TEE support for NVIDIA H100, H200, and B200 hardware, delivering near-native performance with complete privacy. With Phala Cloud, developers can build, containerize, and deploy encrypted AI applications in minutes while relying on automated attestations and strong compliance guarantees. Phala powers sensitive workloads across finance, healthcare, AI SaaS, decentralized AI, and other privacy-critical industries. Trusted by thousands of developers and enterprise customers, Phala enables businesses to build AI that users can trust.Starting Price: $50.37/month -
50
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
