4.2 out of 5 stars
(230 Ratings)
Runpod provides a cloud infrastructure that enables seamless deployment and scaling of AI workloads with GPU-powered pods. By offering access to a wide array of NVIDIA GPUs, such as the A100 and H100, Runpod supports training and deploying machine learning models with minimal latency and high performance. The platform emphasizes ease of use, allowing users to spin up pods in seconds and scale them dynamically to meet demand. With features like autoscaling, real-time analytics, and serverless scaling, Runpod is an ideal solution for startups, academic institutions, and enterprises seeking a flexible, powerful, and affordable platform for AI development and inference.
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5.0 out of 5 stars
(4 Ratings)
Hivenet Compute gives you on-demand RTX 5090 and RTX Pro 6000 GPUs, plus vCPU instances, billed per second while they run. Hivenet owns and operates the infrastructure, with data centres in France, the UAE and the US, so EU teams can keep workloads and data in Europe.
Use it for training and fine-tuning, inference, notebooks, rendering and batch jobs. Launch from ready-made templates in a few minutes, or automate everything through the public Compute API. If you'd rather not run the serving layer yourself, the Inference API gives you an OpenAI-compatible endpoint.
Teams get organisations with role-based access, prepaid credits, and S3-compatible object storage alongside compute.
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4.8 out of 5 stars
(15 Ratings)
Servers.com by Nexcess delivers hybrid bare metal cloud hosting solutions that give businesses greater control over their infrastructure while maintaining the flexibility needed to grow. Its portfolio includes Scalable Bare Metal for on-demand capacity, Enterprise Bare Metal for customized deployments, AI Compute for GPU-powered workloads, and Managed Kubernetes for containerized applications. The platform is built to accommodate organizations that require reliable performance, security, and predictable infrastructure management. Through a network of data centers across multiple continents, customers can deploy services closer to their users and minimize latency. Businesses in industries such as gaming, financial services, advertising technology, streaming, SaaS, and Web3 rely on the platform to support high-demand operations. The infrastructure is designed to handle traffic spikes, intensive computing requirements, and geographically distributed workloads. Advanced networking capabilities and direct connectivity options help optimize application responsiveness and uptime. Organizations can combine different infrastructure offerings to create environments that align with their operational and budget requirements. By providing scalable and customizable bare metal solutions, Servers.com helps businesses maintain performance while adapting to changing market demands.
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4.4 out of 5 stars
(1169 Ratings)
Compute Engine (IaaS), a platform from Google that allows organizations to create and manage cloud-based virtual machines, is an infrastructure as a services (IaaS).
Computing infrastructure in predefined sizes or custom machine shapes to accelerate cloud transformation. General purpose machines (E2, N1,N2,N2D) offer a good compromise between price and performance. Compute optimized machines (C2) offer high-end performance vCPUs for compute-intensive workloads. Memory optimized (M2) systems offer the highest amount of memory and are ideal for in-memory database applications. Accelerator optimized machines (A2) are based on A100 GPUs, and are designed for high-demanding applications. Integrate Compute services with other Google Cloud Services, such as AI/ML or data analytics. Reservations can help you ensure that your applications will have the capacity needed as they scale. You can save money by running Compute using the sustained-use discount, and you can even save more when you use the committed-use discount.
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