Building and deploying powerful AI models like GPT requires a robust cloud server that can handle computational demands with ease.
The right cloud server provides scalability, fast processing, and seamless integration, ensuring optimal performance for AI workloads.
Whether you are a developer, researcher, or a business innovator, choosing the best cloud server is crucial to harness the full potential of GPT technology and drive meaningful outcomes.
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- Free AI Image Generator
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The Best Cloud Server for AI
| Provider | Key Features | Starting Price/hr | Best For |
|---|---|---|---|
| RunPod | – 50+ ready templates – Global infrastructure (30+ regions) – Custom containers – Instant GPU deployment | $0.20 | ML workload deployment |
| Beam Cloud | – One-line Python deployment – GPU autoscaling – Hot reloading – Data management | $0.19 (CPU core) | Developer-focused projects |
| TensorDock | – 45 GPU models – KVM virtualization – 100+ locations – No quotas or commitments | $0.35 | Budget-conscious developers |
| Vultr | – 32 data centers – Latest NVIDIA/AMD GPUs – Kubernetes support – Bare metal options | $1.671 | Enterprise AI workloads |
| DigitalOcean | – 1-Click Hugging Face models – GenAI platform – DOKS GPU support – Bare metal GPUs | $1.799 | Scalable AI applications |
RunPod – Fine Tune and Deploy AI Models
RunPod is an excellent choice for fine-tuning and deploying AI models, offering a globally distributed GPU cloud designed specifically for AI workloads. Its platform allows you to focus more on running machine learning models and less on managing infrastructure.
Features
- Seamless Deployment: Spin up GPU pods in mere seconds with drastically reduced cold-boot times, enabling you to start building immediately after deployment.
- Extensive GPU Options: Choose from powerful GPU configurations such as H100 PCIe, A100, RTX 4090, and more, ensuring compatibility with various AI needs.
- Preconfigured Templates: Access 50+ ready-to-use templates, including PyTorch and TensorFlow, to streamline your machine learning workflow.
- Customizable Environments: Bring your own custom container or configure your deployment templates to match your unique project requirements.
- Global Infrastructure: With thousands of GPUs across 30+ regions, you can deploy workloads securely on public or private cloud infrastructure.
- Cost-Effectiveness: RunPod offers competitive pricing, making high-performance GPUs accessible for every workload.
Pricing
- Starting from just $0.20/hour, with options tailored to your budget and performance demands.
- High-performance GPUs like the H100 PCIe are available, starting at $2.69/hour on secure cloud platforms.
- Flexible pricing plans across community and secure cloud options ensure you only pay for what you need.
RunPod is the ultimate choice for AI practitioners looking to deploy any machine learning workload quickly, securely, and affordably.
Beam Cloud – AI Infrastructure for Developers
Run AI workloads anywhere with zero complexity. With just one line of Python, you gain access to global GPUs, complete control, and unparalleled simplicity for deploying, scaling, and managing your AI infrastructure.
Features
- Deploy a Serverless Inference API: Launch a serverless inference API effortlessly with a single command. Beam APIs include essential features like authentication, autoscaling, logging, and a comprehensive suite of monitoring metrics.
- GPU Autoscaling: Scale your workloads to hundreds of containers with intelligent GPU autoscaling. Define custom scaling parameters, and Beam will handle the rest.
- Data Management: Store and access data seamlessly with globally distributed cloud volumes. Easily mount performant storage volumes to your containers for training and inference.
- Hot Reloading: Iterate faster with magical hot reloading, running your code almost instantly on any hardware.
Pricing
- CPU: $0.190 per core per hour
- RAM: $0.020 per GB per hour
- T4 GPU: $0.54 per hour
- RTX 4090 GPU: $0.69 per hour
- A10G GPU: $1.05 per hour
- A100-40 GPU: $2.75 per hour
Flexible pricing plans are available to match your needs:
- Developer Plan: $0 per month + usage, 15 hours included free
- Team Plan: $89 per month + usage
- Growth Plan: Contact us for a custom quote
Beam Cloud is tailored for ambitious developers seeking fast, scalable, and reliable AI infrastructure to power their projects.
TensorDock – Affordable GPU Servers for AI
TensorDock offers cutting-edge, affordable GPU servers tailored for AI workloads. Empower your projects with high-performance infrastructure at up to 80% less cost than traditional cloud providers.
Features
- Flexible Deployment: Launch servers instantly with no quotas, hidden fees, or commitments. Start with as little as $5 and get to work in just 30 seconds.
- Wide GPU Selection: Choose from 45 GPU models, including RTX 4090, A100, and H100, to suit various use cases and budgets—from gaming to advanced AI inference.
- KVM Virtualization: Enjoy root access with fully dedicated GPUs. Gain complete control over your operating system, manage your drivers, and avoid compatibility issues.
- Global Availability: Access a globally distributed fleet with up to 30,000 GPUs in over 100 locations. Scale your applications seamlessly wherever your users are.
- Bulletproof Reliability: All hardware is hosted in Tier 3/4 data centers with 99.99% uptime. TensorDock maintains rigorous standards for quality and security.
Pricing
TensorDock provides transparent, highly competitive pricing for on-demand GPU cloud services.
- H100 SXM5 80GB: From $2.80/hour
- A100 SXM4 80GB: From $1.80/hour
- RTX 4090: From $0.35/hour
- RTX A6000: From $0.45/hour
Additional pricing for CPU, RAM, and storage is fully customizable. TensorDock’s marketplace ensures you always have access to the best prices with no unnecessary overhead.
Vultr – AI Cloud GPUs
Vultr’s AI Cloud GPUs offer cutting-edge performance for developers and businesses needing robust GPU-accelerated computing.vult
Globally accessible across 32 cloud data center regions, our platform enables seamless deployment of AI/ML workloads, AR/VR applications, high-performance computing (HPC), virtual desktop infrastructure (VDI), and more. Whether you require virtual machines or bare metal, Vultr delivers state-of-the-art GPU infrastructure tailored to your needs.
Features
- Global Reach: With 32 cloud data centers worldwide, deploy and scale workloads wherever your business requires.
- Advanced Hardware: Powered by the latest NVIDIA and AMD GPUs, including H100, L40S, A100, and MI300X, optimized for AI, HPC, and graphical workloads.
- Simplified Management: Avoid complexities of driver setups and licensing with Vultr’s streamlined infrastructure.
- Flexible Deployment: Configure fractional, single, or multiple GPU setups with options for virtual machines or dedicated bare metal servers.
- Developer-Friendly Tools: Build locally and deploy globally® using GPU-accelerated Kubernetes clusters, facilitating even the most resource-intensive AI applications.
Pricing
Vultr provides transparent, usage-based pricing, ensuring flexibility for projects of any scale. Below are examples of hourly on-demand pricing:
- AMD MI300X: $2.190/GPU/hr
- NVIDIA HGX H100: $2.990/GPU/hr
- NVIDIA L40S (1 GPU): $1.671/hr
- NVIDIA HGX A100 (8 GPUs): $2.800/hr
- NVIDIA PCIe A100 (1 GPU): $2.397/hr
- NVIDIA A16 (16 GPUs): $7.534/hr
Prepaid options and contract durations are also available for further cost optimization.
Harness the power of Vultr AI Cloud GPUs for your next-gen AI/ML systems and unlock new possibilities. Contact sales or start your project today with a free Vultr account!
DigitalOcean – Build and Run AI
Everything you need to build, run, and manage the next big thing, powered by DigitalOcean’s AI and machine learning tools. Get started with ease and integrate AI into your applications within minutes.
Features
- 1-Click Models Powered by Hugging Face
Deploy the most popular third-party models with just one click. Avoid complex setups and focus on integrating AI quickly into your projects.
- GPU Droplets
Simple, scalable, and flexible NVIDIA H100 machines designed for AI/ML workloads. GPU Droplets provide the ideal infrastructure for developers requiring on-demand, high-performance GPU compute.
- GenAI Platform
Build and deploy powerful AI agents with ease using DigitalOcean’s Generative AI platform, tailored to support modern AI innovation.
- Bare Metal GPUs
Enable complex and custom AI/ML projects with bare metal GPU infrastructure, perfect for demanding workloads requiring maximum performance and configurability.
- GPUs for DOKS
Run scalable AI/ML applications in Kubernetes environments with GPU support for DigitalOcean Kubernetes (DOKS).
- Additional GPU Options
Discover a variety of compute and GPU solutions suited for diverse project needs, from single-node to multi-node training setups.
Pricing
DigitalOcean offers usage-based pricing with flexibility for projects of all sizes. Below are examples of select GPU pricing tiers:
- NVIDIA H100 (1 GPU): $3.890/GPU/hr
- NVIDIA A100 (1 GPU): $2.499/GPU/hr
- NVIDIA V100 (1 GPU): $1.799/GPU/hr
Prepaid plans and contract options are available for additional cost savings. Whether you’re building a simple AI application or running a large-scale training workload, DigitalOcean’s pricing model ensures transparency and scalability.
Build smarter, faster applications with DigitalOcean’s AI and machine learning tools. Contact sales, or get started now with GPUs designed for your vision!
Frequently Asked Questions (FAQs)
What types of projects can benefit from GPU support in DOKS?
GPU support in DOKS is ideal for AI/ML workloads, including deep learning, data analysis, and high-performance computing tasks. It suits projects of all sizes, from small-scale applications to complex, multi-node training setups.
Are there any discounts available for GPU usage?
Yes, DigitalOcean offers prepaid plans and contract options that can reduce costs, providing more savings for long-term or consistent usage.
How do I get started with GPUs in DigitalOcean Kubernetes?
You can start by contacting sales for guidance or deploying GPU-equipped nodes directly in your Kubernetes cluster through DigitalOcean’s platform. The process is straightforward and designed for scalability.
Final Thoughts!
DigitalOcean’s integration of GPU support within Kubernetes provides unparalleled opportunities for developers and businesses to optimize their AI and machine learning workflows. With flexible pricing structures, robust scalability, and ease of deployment, DigitalOcean empowers users to build innovative, high-performance applications effortlessly. Whether you’re working on small projects or scaling up to tackle complex workloads, DigitalOcean’s tools ensure you have the resources needed to succeed. Take the first step today and unlock the full potential of your projects with DigitalOcean.