7 Best GPU VPS Hosting Providers 2024

GPU VPS hosting is a game-changer for AI, deep learning, and other GPU-intensive tasks, offering specialized computing power for complex calculations.

The top five providers excel in delivering robust performance, making them perfect for cutting-edge projects that require significant graphical processing.

These services are essential for researchers, developers, and businesses pushing the boundaries in fields like artificial intelligence, where speed and accuracy are paramount.

1. GPU-Mart

Editor Rating

4.8

  • Dedicated GPU Server Hosting with 19+ latest GPU Models
  • Supports 8+ GPU Use Scenarios
  • Offers 20+ GPU Computing Applications
  • 24/7 technical support with most issues resolved within an hour
  • Starting at $21.00/month
See Pros & Cons

Pros

  • Cost-effective and customizable hosting solutions
  • High uptime and low latency
  • Multiple data centers in the USA
  • Versatile use cases and scalability

Cons

  • Complex hardware maintenance
  • Data security concerns on remote servers
  • Potential network latency issues

As a leading provider of professional GPU Hosting, GPU-Mart is notably recognized for its superior services which cater to high-performance computing projects. Its cutting-edge infrastructure supports more than 19 models of GPU cards, placing a spotlight on power, speed and complexity.

Unlike traditional hosting providers, GPU-Mart bolsters its servers with GPU cards designed to handle complex tasks efficiently. This translates into faster processing times and a higher level of reliability for users.

The company’s partnership with top GPU card manufacturers, coupled with its dedicated server offerings, make it a perfect fit for simulation running, deep learning algorithm development and other compute-intensive tasks.

In terms of pricing, GPU-Mart steps up with cost-effective solutions with its GPU VPS Hosting plans starting from as low as $21.00 per month. This balanced approach to performance and affordability makes it a viable choice for businesses and individual users alike.

Furthermore, they offer a wide range of GPU use scenarios and GPU Computing Applications. Coupled with their versatile use cases and scalability, GPU-Mart stands as an ideal choice for various high-performance tasks.

What makes it even more compatible is the possibility of installing Windows on these GPU Servers.

However, despite its strengths, prospective users should consider the complexity of the technology. While GPU-Mart’s expert support team is on hand 24/7 to tackle technical issues, concepts such as hardware configuration, data security on remote servers, and network latency can still pose challenges.

Overall, with its professional GPU Hosting, cost-effective solutions, and excellent customer support, GPU-Mart offers a compelling entry point for users requiring high-performance server solutions.

Read more: GPU-Mart GPU Server Hosting

2. OVHCloud

ovh logo
Editor Rating

4.7

  • Specialized in offering cloud servers for massively parallel tasks
  • Integrates NVIDIA graphic processors for enhanced computing power
  • Comes with certified information security management system (ISMS)
  • Suitable for needs of machine learning and deep learning tasks
  • Starting at $0.77/hour
See Pros & Cons

Pros

  • Potent hardware for machine learning and akin tasks
  • Flexible configurations to cater various workloads
  • Offers effective cloud-based GPU solution
  • Supports various AI frameworks for extensive applications

Cons

  • Outdated NVIDIA graphic processors
  • Mixed customer reviews
  • Lacks specific information about available CPU models
  • Limited geographical reach of data centers

Known for its comprehensive cloud solutions tailored for massively parallel tasks, OVHCloud is the preferred choice for users requiring high-performance computing power. Its servers are integrated with NVIDIA graphic processors, employing potent hardware for compute-intensive tasks, especially in the machine learning and deep learning domains.

Utilizing NVIDIA’s NGC platform, OVHCloud ensures the utmost efficiency and simplicity when deploying and managing GPU-accelerated containers. The service comes with broad AI framework support, making it apt for various artificial intelligence and machine learning applications.

OVHCloud’s servers are certified under ISO/IEC 27001, 27017, 27018, and 27701, guaranteeing a robust information security and privacy information management system. Moreover, compliance with health data hosting standards allows secure hosting of health care data.

With memory options from 45GB to 1520GB and storage capacities from 50GB SSD up to 2TB NVMe drives, OVHCloud offers a broad range of configurations to accomplish diverse workflow requirements.

Other noteworthy features include a robust management interface, guaranteed high speed connectivity, and compliance with stringent security standards. However, the service has received mixed reviews for customer support and may have a limited geographical reach, which potential users should note.

Despite these potential limitations, with its grit to offer a reliable, high-speed computing solution, OVHCloud has positioned itself as an efficacious choice for businesses and individuals delving into AI and machine learning applications.

Read more: OVHcloud GPU Server Hosting Review 2024

3. Paperspace

Editor Rating

4.6

  • Perfectly designed for AI developers with a no-fuss environment
  • Predictable costs with no commitments
  • Infrastructure abstraction with job scheduling and resource provisioning
  • Pre-loaded with major ML frameworks and NVIDIA GPUs
  • Starting at $0.07/hour
See Pros & Cons

Pros

  • Easy setup and fast start
  • Scalability with a range of GPU options
  • Good value for money
  • Flexible and user-friendly

Cons

  • Complexities with Conda Environments
  • Restricted auto-shutdown feature
  • Occasional lags with lower-tier machines
  • Issues with billing and customer support responsiveness

Paperspace offers an ideal environment for AI developers, providing instant access to high-performance GPU and IPUs. It also prides itself on providing low-cost GPUs with per-second billing, allowing developers to save significantly on their computing costs compared to other major cloud platforms.

The user-friendly interface and no-commitment policy make it a go-to choice for developers who require flexibility and predictability in their costs. With Paperspace, you can easily change instance types at anytime and stop paying when you no longer need the services.

In addition to being cost-effective, Paperspace also offers a range of powerful features such as job scheduling, resource provisioning, and server management without the need for users to manage servers themselves. This makes the platform efficient and easy to use.

Paperspace sets itself apart with a pre-loaded “ML in a Box” template that comes with all the major ML frameworks and CUDE drivers. The platform also offers the largest GPU catalog in the world, providing users access to the latest NVIDIA GPUs.

Despite few limitations such as complexities with Conda environments and occasional lags on lower-tier machines, Paperspace has successfully carved a niche in the hosting market for AI developers. With a wide range of cost-effective and effective GPU options, robust support, and an easily scalable solution, Paperspace remains an excellent choice for high-performance computing needs.

Read more: PaperSpace GPU Server Hosting Review

4. Cherry Servers

Editor Rating

4.6

  • Dedicated GPU servers for high-performance computations and machine learning model training
  • Choice of 4 available GPU accelerators
  • In-memory computing with possibility to add up to 1536GB RAM
  • Secure data storage options and private networking
  • Starting at $81/month
See Pros & Cons

Pros

  • Reliable service with minimal downtime
  • Responsive and helpful customer support
  • Supports Crypto Proof of Stake (PoS) Validator
  • No hidden costs, with transparency in pricing

Cons

  • Limited SMTP services
  • Delayed server availability
  • Identity verification requirements may deter some customers

Cherry Servers is a renowned provider of dedicated GPU servers and hosting, offering cost-effective and high-performance solutions to businesses. Their servers provide raw compute power that is ideal for developers and organizations conducting high-performance computations and machine learning model training.

They offer a choice of four GPU Accelerators and the possibility of in-memory computing with up to 1536 GB RAM. This ensures hassle-free and rapid machine learning model training and computations. Secure data storage options are available as well, ranging from directly attached to block or object storage.

Cherry Servers provides a robust 10G virtual LAN for private networking and allows up to 100TB of free monthly traffic along with a highly competitive overage cost. Notably, the servers can be set up within 2 to 24 hours depending on your configuration.

Their pricing starts at a reasonable $81 per month and they showcase transparency in their pricing models. There are no hidden costs involved, leading to a trustful relationship with the user.

In conclusion, Cherry Servers offers an advanced and reliable hosting solution suitable for users who depend on high-performance computations and machine learning model training on the GPU. Their transparency in pricing, along with prompt customer support, makes them a worthwhile consideration for businesses.

Read more: GPU-Mart GPU Server Hosting 2024

5. Hostkey

Editor Rating

4.5

  • Professional GPU Powered Hosting
  • Support GPU cards such as RTX A4000 / A5000 / A6000
  • Fast NVMe disks and large storage
  • Pre-installed frameworks like Tensorflow and Pytorch
  • Starting at €70/month
See Pros & Cons

Pros

  • High-performance GPUs and CPUs
  • Efficient handling of DDoS attacks
  • Diverse server options for various needs
  • Long-Term reliability and performance

Cons

  • Occasional server downtime
  • Delayed customer support response
  • Occasional network performance degradation
  • Issues with identity verification and service suspension

Hostkey is known for its powerful GPU-powered hosting solutions, ideal for high-load tasks such as 3D modeling, rendering, machine learning, and processing large data sets. The vendor offers dedicated servers pre-configured with professional GPU cards such as RTX A4000, A5000, and A6000.

Among their standout features is their fast NVMe disks for quick data transfer and a large storage capacity for bulk data. They also support popular frameworks such as TensorFlow and Pytorch right out of the box, making it easy to get started with machine learning or data processing tasks.

Hostkey provides a range of server options, allowing users to select the best configuration for their specific needs, from machines with high-performing CPUs to servers interconnected with NVLink. It’s also worth noting their unmetered 1 Gbps speed, ensuring fast and efficient data transfer.

Beyond the technical aspects, Hostkey shines in its security and DDoS attack handling, keeping servers operational even under attack. Though there have been instances of server downtime and slow customer service response times, the overall performance and reliability of the service have earned it a loyal customer base over the years.

With competitive pricing starting at €70 per month, Hostkey offers a solid, feature-rich option for businesses and individuals seeking powerful, GPU-based hosting services.

Read more: HostKey GPU Hosting Review

6. Lambda

lambda
Editor Rating

4.7

  • Datacenter power from NVIDIA GH200
  • On-demand GPU instances billed by the hour
  • Choice of single, dual, quad, or octa GPU instances
  • Tensorbook designed for data scientists
  • Starting at $2.49/hour
See Pros & Cons

Pros

  • Plug and play system
  • Diverse range of GPU instances
  • Powerful AI innovation capabilities
  • Ready-to-use Tensorbooks for data scientist

Cons

  • High prices and value concerns
  • Some reported hardware reliability issues
  • Lack of NVlink in some multi-GPU systems
  • Quality of technical support could be improved

Lambda takes pride in powering the forefront of human knowledge, with products and services favored by Intel, Microsoft, Amazon Research, and notable universities.

Offering an effortless plug-and-play system, engineers and researchers can jumpstart scientific and business innovations using Lambda’s range of workstations, servers, and laptop offerings.

Lambda also leads in cloud services, providing on-demand GPU instances billed by the hour, starting at an affordable rate of $2.49/hr. The provision of single, dual, quad, or octa GPU instances offers versatility to cater to different workload and budget requirements.

To pave way for AI innovation, Lambda harnesses the power of NVIDIA H100 Tensor Core GPUs and NVIDIA DGX™ SuperPOD, a turnkey full-stack infrastructure solution..

For Data Scientists, Lambdas Tensorbook has been readily appreciated for handling machine learning tasks effectively right out of the box, making it instrumental for immediate project commencement without any additional setup.

While the high-value services are somewhat reflected in its pricing, it is generally viewed that with its vast array of offerings and dedicated tools and features for optimization, Lambda presents an excellent investment for organizations invested stringently in research and development.

7. Google Cloud

google cloud
Editor Rating

4.6

  • A great diversity of NVIDIA GPUs for various performance and price points
  • Efficient compute tasks like generative AI, 3D visualization, and High-Performance Computing
  • Flexible pricing and machine customizations for workload optimization
  • Google Cloud provides access to industry-leading storage, networking, and data analytics technologies
  • Starting at $0.35/GPU
See Pros & Cons

Pros

  • Wide selection of GPUs promotes resources flexibility
  • Powerful GPUs available despite high demand
  • Seamless deep learning work support
  • Easy setup and usability

Cons

  • Scarcity of high-demand GPUs
  • Quota limitations and allocation issues
  • Lack of transparency in GPU availability
  • Possible inequity for smaller entities or independent developers

Google Cloud is remarkable for its agile and reliable Google Cloud GPU VPS hosting services. Accessible even in high-demand situations, Google Cloud delivers high-performance computing with cutting-edge NVIDIA GPUs.

Capable of handling complex computational tasks like 3D visualization, HPC, and generative AI, Google Cloud offers a wide variety of GPUs to match diverse performance needs and price points.

Google Cloud also provides flexible performance – allowing you to balance the processor, memory, high-performance disk, and up to 8 GPUs per instance optimally. Here, you only pay per second, thus, only paying for what you need.

With a user-friendly interface, Google Cloud GPU VPS are easy to set up, making it accessible even for beginners in the field. Such a feature is extremely beneficial for individuals and teams working on deep learning, AI, and machine learning projects.

However, the scarcity of high-demand GPUs and issues with quota allocation and management are common concerns among users. However, despite these slight hiccups, Google Cloud continues to be a leading choice for users seeking a powerful and efficient GPU VPS hosting provider.

Conclusion

In summary, selecting the right dedicated GPU hosting service is crucial for businesses and professionals working on compute-intensive tasks. Each provider, from OVHCloud’s global infrastructure and eco-friendly practices to Paperspace’s user-centric platform, GPU-Mart’s extensive selection, Cherry Servers’ customizable solutions, and Hostkey’s high-performance NVIDIA GPUs, offers unique benefits tailored to different needs.

Key considerations for choosing a provider include computational requirements, budget, customization needs, and environmental impact. The ideal choice will balance performance, cost, and scalability, supporting your project’s growth and adaptation over time.

As the cloud computing landscape evolves, staying updated on each provider’s latest technologies and services is essential. The decision should ultimately align with your project’s specific goals and technical demands, ensuring access to the necessary resources for success in a competitive environment.

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