Amazon EC2 Capacity Blocks for ML vs. Compute Exchange Comparison


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		Related Products Compute with 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. 4 Ratings Visit Website Runpod Runpod offers a cloud-based platform designed for running AI workloads, focusing on providing scalable, on-demand GPU resources to accelerate machine learning (ML) model training and inference. With its diverse selection of powerful GPUs like the NVIDIA A100, RTX 3090, and H100, Runpod supports a wide range of AI applications, from deep learning to data processing. The platform is designed to minimize startup time, providing near-instant access to GPU pods, and ensures scalability with autoscaling capabilities for real-time AI model deployment. Runpod also offers serverless functionality, job queuing, and real-time analytics, making it an ideal solution for businesses needing flexible, cost-effective GPU resources without the hassle of managing infrastructure. 230 Ratings Visit Website IONOS Cloud GPU Servers IONOS GPU Servers provide an accelerated computing infrastructure designed to handle workloads that require significantly more processing power than traditional CPU-based systems. 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About 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.	About Compute Exchange is a web-based marketplace for organizations sourcing GPU infrastructure. It brings together reserved cloud GPU capacity, data-center hardware and forward compute contracts in one place. Buyers can specify GPU model, quantity, region and term, review provider quotes and compare availability, pricing and service-level terms across participating suppliers. For hardware, the marketplace matches buyers and sellers of used and refurbished data-center GPUs, while verified counterparties negotiate transactions directly. For reserved capacity, it aggregates offers from cloud providers; Compute Exchange does not operate the compute itself. The service is designed for AI labs, startups, enterprises, data centers and other institutional buyers and sellers seeking GPU capacity or hardware for AI and machine-learning workloads.
Platforms Supported Windows Not Supported Mac Not Supported Linux Not Supported Cloud Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported	Platforms Supported Windows Not Supported Mac Not Supported Linux Not Supported Cloud Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported
Audience Companies in search of a solution to get scalable access to high-performance compute instances for their machine learning training and inference workloads	Audience Institutional GPU buyers and sellers, including AI teams, startups, enterprises, and data centers sourcing GPU capacity or data-center hardware.
Support Phone Support Supported 24/7 Live Support Supported Online Supported	Support Phone Support Not Supported 24/7 Live Support Not Supported Online Not Supported
API Offers API Not Supported	API Offers API Not Supported
Screenshots and Videos View more images or videos	Screenshots and Videos No images available
Pricing No information available. Free Version Not Supported Free Trial Not Supported	Pricing $1.10/GPU/hour H100 GPU capacity is advertised from $1.10 per GPU/hour. Rates vary by GPU model, region, quantity, and reservation term. Data-center hardware is priced by configuration and condition. Free Version Not Supported Free Trial Not Supported
Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software	Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software

Training Documentation Supported Webinars Supported Live Online Not Supported In Person Supported	Training Documentation Not Supported Webinars Not Supported Live Online Not Supported In Person Not Supported
Company Information Amazon Founded: 1994 United States aws.amazon.com/ec2/capacityblocks/	Company Information Compute Exchange Founded: 2024 United States compute.exchange/
Alternatives AWS EC2 Trn3 Instances Amazon	Alternatives GPUBank GPU Compute
Amazon EC2 Trn2 Instances Amazon	Pacific Pacific Intelligent Technologies
Amazon EC2 UltraClusters Amazon	airgpu Stackprint
Amazon EC2 Trn1 Instances Amazon	OneSource Cloud
AWS Neuron Amazon Web Services View All	TensorHost GPU Server Hosts View All
Categories AI Fine-Tuning Supported AI Inference Supported Cloud GPU Supported Machine Learning Supported	Categories Cloud GPU Supported

Integrations AWS Neuron Supported AWS Nitro System Supported AWS Trainium Supported Amazon EC2 Supported Amazon EC2 G5 Instances Supported Amazon EC2 Inf1 Instances Supported Amazon EC2 P4 Instances Supported Amazon EC2 P5 Instances Supported Amazon EC2 Trn1 Instances Supported Amazon EC2 Trn2 Instances Supported Amazon EC2 UltraClusters Supported Amazon EKS Supported Amazon Elastic Container Service (Amazon ECS) Supported Amazon SageMaker Supported Amazon Web Services (AWS) Supported Greenovative Supported PyTorch Supported TensorFlow Supported Show More Integrations View All 18 Integrations	Integrations AWS Neuron Not Supported AWS Nitro System Not Supported AWS Trainium Not Supported Amazon EC2 Not Supported Amazon EC2 G5 Instances Not Supported Amazon EC2 Inf1 Instances Not Supported Amazon EC2 P4 Instances Not Supported Amazon EC2 P5 Instances Not Supported Amazon EC2 Trn1 Instances Not Supported Amazon EC2 Trn2 Instances Not Supported Amazon EC2 UltraClusters Not Supported Amazon EKS Not Supported Amazon Elastic Container Service (Amazon ECS) Not Supported Amazon SageMaker Not Supported Amazon Web Services (AWS) Not Supported Greenovative Not Supported PyTorch Not Supported TensorFlow Not Supported Show More Integrations
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