Alternatives to GPUBank
Compare GPUBank alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to GPUBank in 2026. Compare features, ratings, user reviews, pricing, and more from GPUBank 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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gpu.nz
Transtrade
gpu.nz is a cloud GPU rental service for developers, machine-learning engineers, researchers and creators who need on-demand compute for AI inference, model training, image and video generation, and rendering. Users compare GPU offers by model, memory, location and hourly rate, then launch servers with preconfigured environments such as ComfyUI, Stable Diffusion Forge, Ollama with Open WebUI, vLLM, PyTorch and Jupyter, or use a custom Docker image. GPU time is billed by the minute from a prepaid balance; the rate is fixed when a server starts, and stopping it ends GPU charges while disk storage remains billable. A web console, REST API, command-line tool and hosted Model Context Protocol server support manual and scripted server search, launch and management.Starting Price: $0.067/hour -
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Hinode
Hinode
Hinode is a cloud workspace for people who make images and video with AI. The workspace keeps your files, installed applications and a shared folder for models and datasets between sessions. When a job needs a whole GPU, you attach a machine beside it: NVIDIA L4 with 24 GB VRAM, L40S with 48 GB or RTX PRO 6000 with 96 GB, each with 32 to 256 GB of RAM. The machine starts from your saved workspace, so the tools you set up are already on it. You can reach your work through a streamed Ubuntu desktop in the Hinode app for Mac, Windows and Linux, or in Chrome and Edge with nothing to install. It also works over SSH, with the hinode command-line tool, from VS Code Remote-SSH, or through an MCP connector for Claude and other assistants. ComfyUI, PyTorch, JupyterLab, Ollama, vLLM, AI Toolkit, Axolotl and a few other apps install in one click.Starting Price: $0.29/h/workspace -
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Nextify
Nextify Now
Nextify is a cloud infrastructure platform for provisioning and managing virtual machines, confidential-computing VMs, GPU instances, and related networking and storage. It offers shared- and dedicated-vCPU AMD EPYC machines, AMD SEV-SNP secure VMs with encrypted guest memory, a virtual TPM and remote attestation, and GPU VMs with AMD Radeon AI PRO R9700 cards. Customers can attach NVMe-backed block storage, create snapshots and S3-compatible object-storage buckets, and use public IPv4, firewalls, private networks, VPN gateways and load balancers. Resources can be managed in the web portal or through a REST API and command-line client; the API also supports automation from scripts, CI pipelines and Terraform. Compute instances are billed hourly up to a published monthly cap, with plans for web services, development and test environments, databases, build jobs, GPU inference, fine-tuning and rendering workloads.Starting Price: $3.95/month -
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Trooper.AI
Trooper.AI
Trooper.AI lets you rent private, bare-metal GPU servers for AI training, inference, and experimentation — ready in minutes. Instantly deploy OpenWebUI, ComfyUI, Jupyter Notebook, Ubuntu Desktop, Ollama, and more with one click. No shared GPUs, no containers, full root access included. All servers are EU-hosted, GDPR and EU AI Act compliant, and operated from Germany. Trooper.AI is built on up-cycled high-end hardware, combining strong performance with sustainability. Pause or freeze servers anytime to save costs and pay only for what you use. Choose from a wide range of GPUs, from V100 and RTX 3090 to RTX 4090 and RTX Pro 6000 Blackwell, backed by fast NVMe storage, persistent machine state, automatic backups, and simple UI and API management. Trooper.AI is the smallest hyperscaler in Europe — built for developers who want performance, privacy, and full control without cloud complexity.Starting Price: €149/month -
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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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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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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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GPUonCLOUD
GPUonCLOUD
Traditionally, deep learning, 3D modeling, simulations, distributed analytics, and molecular modeling take days or weeks time. However, with GPUonCLOUD’s dedicated GPU servers, it's a matter of hours. You may want to opt for pre-configured systems or pre-built instances with GPUs featuring deep learning frameworks like TensorFlow, PyTorch, MXNet, TensorRT, libraries e.g. real-time computer vision library OpenCV, thereby accelerating your AI/ML model-building experience. Among the wide variety of GPUs available to us, some of the GPU servers are best fit for graphics workstations and multi-player accelerated gaming. Instant jumpstart frameworks increase the speed and agility of the AI/ML environment with effective and efficient environment lifecycle management.Starting Price: $1 per hour -
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Intel Tiber AI Cloud
Intel
Intel® Tiber™ AI Cloud is a powerful platform designed to scale AI workloads with advanced computing resources. It offers specialized AI processors, such as the Intel Gaudi AI Processor and Max Series GPUs, to accelerate model training, inference, and deployment. Optimized for enterprise-level AI use cases, this cloud solution enables developers to build and fine-tune models with support for popular libraries like PyTorch. With flexible deployment options, secure private cloud solutions, and expert support, Intel Tiber™ ensures seamless integration, fast deployment, and enhanced model performance.Starting Price: Free -
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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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BHK Cloud
BHK Cloud
BHK Cloud is a Frankfurt-based cloud infrastructure platform for AI and data-intensive workloads. It provides on-demand RTX 3090 GPU compute with 24 GB VRAM starting at $0.15 per GPU hour, S3-compatible object storage from $2.50 per TB/month with zero egress fees, and managed AI agent hosting. Customers can provision resources through a REST API and CLI, launch preconfigured PyTorch, TensorFlow, and CUDA environments, attach storage volumes, and use existing S3 tools such as AWS CLI and boto3 through a compatible endpoint. Infrastructure is operated from Frankfurt for teams seeking European data residency, predictable usage-based pricing, and no minimum commitments. BHK Cloud supports model inference, image generation, LoRA or QLoRA fine-tuning, rendering, video processing, backups, archives, and large model or data pipelines.Starting Price: $0.15 per GPU hour -
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Amazon EC2 G5 Instances
Amazon
Amazon EC2 G5 instances are the latest generation of NVIDIA GPU-based instances that can be used for a wide range of graphics-intensive and machine-learning use cases. They deliver up to 3x better performance for graphics-intensive applications and machine learning inference and up to 3.3x higher performance for machine learning training compared to Amazon EC2 G4dn instances. Customers can use G5 instances for graphics-intensive applications such as remote workstations, video rendering, and gaming to produce high-fidelity graphics in real time. With G5 instances, machine learning customers get high-performance and cost-efficient infrastructure to train and deploy larger and more sophisticated models for natural language processing, computer vision, and recommender engine use cases. G5 instances deliver up to 3x higher graphics performance and up to 40% better price performance than G4dn instances. They have more ray tracing cores than any other GPU-based EC2 instance.Starting Price: $1.006 per hour -
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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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Logen
TitanXT
Logen is a Windows and Linux desktop application for AI image generation on a local computer. It combines project-based chat, model management, workflow tools, image galleries and full-resolution viewing. Its setup prepares ComfyUI for image rendering and Ollama for local prompt assistance. Users can organize generated images by project, adjust generation options, and work with supported ComfyUI workflows. The free tier includes local image generation with FLUX.1-schnell. The one-time Pro upgrade adds batch generation, additional models and custom workflow presets. Logen is intended for creators who want to run image-generation workflows on their own computer rather than use a cloud image-generation service. Windows 10/11 x64 and Linux x64 are supported, and an NVIDIA GPU is recommended. Initial setup and model downloads require an internet connection; image generation runs locally after setup.Starting Price: £49 one-time -
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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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AWS Neuron
Amazon Web Services
It supports high-performance training on AWS Trainium-based Amazon Elastic Compute Cloud (Amazon EC2) Trn1 instances. For model deployment, it supports high-performance and low-latency inference on AWS Inferentia-based Amazon EC2 Inf1 instances and AWS Inferentia2-based Amazon EC2 Inf2 instances. With Neuron, you can use popular frameworks, such as TensorFlow and PyTorch, and optimally train and deploy machine learning (ML) models on Amazon EC2 Trn1, Inf1, and Inf2 instances with minimal code changes and without tie-in to vendor-specific solutions. AWS Neuron SDK, which supports Inferentia and Trainium accelerators, is natively integrated with PyTorch and TensorFlow. This integration ensures that you can continue using your existing workflows in these popular frameworks and get started with only a few lines of code changes. For distributed model training, the Neuron SDK supports libraries, such as Megatron-LM and PyTorch Fully Sharded Data Parallel (FSDP). -
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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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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 -
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Amazon EC2 P4 Instances
Amazon
Amazon EC2 P4d instances deliver high performance for machine learning training and high-performance computing applications in the cloud. Powered by NVIDIA A100 Tensor Core GPUs, they offer industry-leading throughput and low-latency networking, supporting 400 Gbps instance networking. P4d instances provide up to 60% lower cost to train ML models, with an average of 2.5x better performance for deep learning models compared to previous-generation P3 and P3dn instances. Deployed in hyperscale clusters called Amazon EC2 UltraClusters, P4d instances combine high-performance computing, networking, and storage, enabling users to scale from a few to thousands of NVIDIA A100 GPUs based on project needs. Researchers, data scientists, and developers can utilize P4d instances to train ML models for use cases such as natural language processing, object detection and classification, and recommendation engines, as well as to run HPC applications like pharmaceutical discovery and more.Starting Price: $11.57 per hour -
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Amazon EC2 P5 Instances
Amazon
Amazon Elastic Compute Cloud (Amazon EC2) P5 instances, powered by NVIDIA H100 Tensor Core GPUs, and P5e and P5en instances powered by NVIDIA H200 Tensor Core GPUs deliver the highest performance in Amazon EC2 for deep learning and high-performance computing applications. They help you accelerate your time to solution by up to 4x compared to previous-generation GPU-based EC2 instances, and reduce the cost to train ML models by up to 40%. These instances help you iterate on your solutions at a faster pace and get to market more quickly. You can use P5, P5e, and P5en instances for training and deploying increasingly complex large language models and diffusion models powering the most demanding generative artificial intelligence applications. These applications include question-answering, code generation, video and image generation, and speech recognition. You can also use these instances to deploy demanding HPC applications at scale for pharmaceutical discovery. -
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Provision a VM quickly with everything you need to get your deep learning project started on Google Cloud. Deep Learning VM Image makes it easy and fast to instantiate a VM image containing the most popular AI frameworks on a Google Compute Engine instance without worrying about software compatibility. You can launch Compute Engine instances pre-installed with TensorFlow, PyTorch, scikit-learn, and more. You can also easily add Cloud GPU and Cloud TPU support. Deep Learning VM Image supports the most popular and latest machine learning frameworks, like TensorFlow and PyTorch. To accelerate your model training and deployment, Deep Learning VM Images are optimized with the latest NVIDIA® CUDA-X AI libraries and drivers and the Intel® Math Kernel Library. Get started immediately with all the required frameworks, libraries, and drivers pre-installed and tested for compatibility. Deep Learning VM Image delivers a seamless notebook experience with integrated support for JupyterLab.
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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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Skyportal
Skyportal
Skyportal is a GPU cloud platform built for AI engineers, offering 50% less cloud costs and 100% GPU performance. It provides a cost-effective GPU infrastructure for machine learning workloads, eliminating unpredictable cloud bills and hidden fees. Skyportal has seamlessly integrated Kubernetes, Slurm, PyTorch, TensorFlow, CUDA, cuDNN, and NVIDIA Drivers, fully optimized for Ubuntu 22.04 LTS and 24.04 LTS, allowing users to focus on innovating and scaling with ease. It offers high-performance NVIDIA H100 and H200 GPUs optimized specifically for ML/AI workloads, with instant scalability and 24/7 expert support from a team that understands ML workflows and optimization. Skyportal's transparent pricing and zero egress fees provide predictable costs for AI infrastructure. Users can share their AI/ML project requirements and goals, deploy models within the infrastructure using familiar tools and frameworks, and scale their infrastructure as needed.Starting Price: $2.40 per hour -
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Amazon Elastic Inference
Amazon
Amazon Elastic Inference allows you to attach low-cost GPU-powered acceleration to Amazon EC2 and Sagemaker instances or Amazon ECS tasks, to reduce the cost of running deep learning inference by up to 75%. Amazon Elastic Inference supports TensorFlow, Apache MXNet, PyTorch and ONNX models. Inference is the process of making predictions using a trained model. In deep learning applications, inference accounts for up to 90% of total operational costs for two reasons. Firstly, standalone GPU instances are typically designed for model training - not for inference. While training jobs batch process hundreds of data samples in parallel, inference jobs usually process a single input in real time, and thus consume a small amount of GPU compute. This makes standalone GPU inference cost-inefficient. On the other hand, standalone CPU instances are not specialized for matrix operations, and thus are often too slow for deep learning inference. -
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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 -
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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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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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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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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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Amazon EC2 Inf1 Instances
Amazon
Amazon EC2 Inf1 instances are purpose-built to deliver high-performance and cost-effective machine learning inference. They provide up to 2.3 times higher throughput and up to 70% lower cost per inference compared to other Amazon EC2 instances. Powered by up to 16 AWS Inferentia chips, ML inference accelerators designed by AWS, Inf1 instances also feature 2nd generation Intel Xeon Scalable processors and offer up to 100 Gbps networking bandwidth to support large-scale ML applications. These instances are ideal for deploying applications such as search engines, recommendation systems, computer vision, speech recognition, natural language processing, personalization, and fraud detection. Developers can deploy their ML models on Inf1 instances using the AWS Neuron SDK, which integrates with popular ML frameworks like TensorFlow, PyTorch, and Apache MXNet, allowing for seamless migration with minimal code changes.Starting Price: $0.228 per hour -
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MimicPC
MimicPC
MimicPC is a cloud-based AI platform that frees you from the need for a high-performance computer or GPU. Seamlessly run cutting-edge applications like Stable Diffusion, ComfyUI, Automatic 111t Face Fusion, RVC, Ollama, and Fooocus right from you r browser. Whether you're a developer, artist, or tech enthusiast, MimicPC provides the powerful tools you need to bring your creative visions to life effortlessly.Starting Price: $0.49/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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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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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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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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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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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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AWS Elastic Fabric Adapter (EFA)
United States
Elastic Fabric Adapter (EFA) is a network interface for Amazon EC2 instances that enables customers to run applications requiring high levels of inter-node communications at scale on AWS. Its custom-built operating system (OS) bypass hardware interface enhances the performance of inter-instance communications, which is critical to scaling these applications. With EFA, High-Performance Computing (HPC) applications using the Message Passing Interface (MPI) and Machine Learning (ML) applications using NVIDIA Collective Communications Library (NCCL) can scale to thousands of CPUs or GPUs. As a result, you get the application performance of on-premises HPC clusters with the on-demand elasticity and flexibility of the AWS cloud. EFA is available as an optional EC2 networking feature that you can enable on any supported EC2 instance at no additional cost. Plus, it works with the most commonly used interfaces, APIs, and libraries for inter-node communications. -
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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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LeaderGPU
LeaderGPU
Conventional CPUs can no longer cope with the increased demand for computing power. GPU processors exceed the data processing speed of conventional CPUs by 100-200 times. We provide servers that are specifically designed for machine learning and deep learning purposes and are equipped with distinctive features. Modern hardware based on the NVIDIA® GPU chipset, which has a high operation speed. The newest Tesla® V100 cards with their high processing power. Optimized for deep learning software, TensorFlow™, Caffe2, Torch, Theano, CNTK, MXNet™. Includes development tools based on the programming languages Python 2, Python 3, and C++. We do not charge fees for every extra service. This means disk space and traffic are already included in the cost of the basic services package. In addition, our servers can be used for various tasks of video processing, rendering, etc. LeaderGPU® customers can now use a graphical interface via RDP out of the box.Starting Price: €0.14 per minute -
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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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Aqaba.ai
Aqaba.ai
Aqaba.ai is a cloud GPU platform that gives AI developers instant access to high-performance computing power without the typical barriers of cost, availability, or environmental guilt. We provide dedicated H100s, A100s, and RTX GPUs that launch in seconds, not hours, with simple hourly pricing and no hidden fees. Unlike traditional cloud providers where you're stuck in waitlists or sharing resources with other users, every GPU instance on Aqaba.ai is exclusively yours, ensuring predictable performance for training everything from computer vision models to large language models.Starting Price: $0.39/hour -
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RunComfy
RunComfy
Our cloud-based environment that automatically sets up your ComfyUI workflow. Each workflow fully equipped with all the essential custom nodes and models, ensuring a hassle-free beginning. Unlock the full potential of your creative projects with ComfyUI Cloud's high-performance GPUs. Benefit from faster processing speeds at market-leading rates, ensuring both time and cost savings. Launch ComfyUI cloud instantly, no installation required, for a seamless start with a fully prepared environment, ready for immediate use. Access ready-to-use ComfyUI workflows with pre-set models and nodes, avoiding configuration hassles in the cloud. Experience rapid results with our powerful GPUs, boosting productivity and efficiency in creative projects. -
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GreenNode
GreenNode
GreenNode is a high-performance, self-service enterprise AI cloud platform that centralizes the full AI/ML model lifecycle, from development to deployment, on a scalable GPU-accelerated infrastructure designed for modern AI workloads. It provides cloud-hosted notebook instances where teams can write code, visualize data, and collaborate, supports model training and fine-tuning with flexible compute, and offers a model registry to manage versions and performance across deployments. It includes serverless AI model-as-a-service capabilities with a catalog of 20+ pre-trained open-source models for text generation, embeddings, vision, speech, and more that can be accessed through standard APIs for fast experimentation and integration into applications without building model infrastructure from scratch. GreenNode’s environment accelerates model inference with low-latency GPU execution, enables seamless integration with tools and frameworks, and features performance.Starting Price: 0.06$ per GB -
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Bayesforge
Quantum Programming Studio
Bayesforge™ is a Linux machine image that curates the very best open source software for the data scientist who needs advanced analytical tools, as well as for quantum computing and computational mathematics practitioners who seek to work with one of the major QC frameworks. The image combines common machine learning frameworks, such as PyTorch and TensorFlow, with open source software from D-Wave, Rigetti as well as the IBM Quantum Experience and Google's new quantum computing language Cirq, as well as other advanced QC frameworks. For instance our quantum fog modeling framework, and our quantum compiler Qubiter which can cross-compile to all major architectures. All software is made accessible through the Jupyter WebUI which, due to its modular architecture, allows the user to code in Python, R, and Octave. -
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AceCloud
AceCloud
AceCloud is a comprehensive public cloud and cybersecurity platform designed to support businesses with scalable, secure, and high-performance infrastructure. Its public cloud services include compute options tailored for RAM-intensive, CPU-intensive, and spot instances, as well as cloud GPU offerings featuring NVIDIA A2, A30, A100, L4, L40S, RTX A6000, RTX 8000, and H100 GPUs. It provides Infrastructure as a Service (IaaS), enabling users to deploy virtual machines, storage, and networking resources on demand. Storage solutions encompass object storage, block storage, volume snapshots, and instance backups, ensuring data integrity and accessibility. AceCloud also offers managed Kubernetes services for container orchestration and supports private cloud deployments, including fully managed cloud, one-time deployment, hosted private cloud, and virtual private servers.Starting Price: $0.0073 per hour -
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Akamai Cloud
Akamai
Akamai Cloud (formerly Linode) is the world’s most distributed cloud computing platform, designed to help businesses deploy low-latency, high-performance applications anywhere. It delivers GPU acceleration, managed Kubernetes, object storage, and compute instances optimized for AI, media, and SaaS workloads. With flat, predictable pricing and low egress fees, Akamai Cloud offers a transparent and cost-effective alternative to traditional hyperscalers. Its global infrastructure ensures faster response times, improved reliability, and data sovereignty across key regions. Developers can scale securely using Akamai’s firewall, database, and networking solutions, all managed through an intuitive interface or API. Backed by enterprise-grade support and compliance, Akamai Cloud empowers organizations to innovate confidently at the edge. -
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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
