Recently, GPU VPS providers have become highly sought after in terms of the development of several new technologies that have gained immense popularity, such as deep learning, machine learning, and AI. All the providers listed below offer the capability of this hardware to handle these rather complex processes.
Our research shows GPU Mart is the best GPU VPS provider on the market based on criteria such as performance, reliability, and customer satisfaction.
The Top 9 Best GPU VPS Providers and Services
1. GPU Mart
- Wide Range of GPUs
- Flexible Pricing
- High Performance
- 24/7 Support
- Starting $16.8/month
Pros
- Scalability: Easily scale resources up or down based on needs.
- Cost Savings: No need for expensive hardware investment; pay-per-use model.
- Instant Availability: Immediate access to high-performance resources.
- Maintenance-Free: Hosting provider handles infrastructure and updates.
Cons
- Resource Sharing: Lower-end plans might involve shared resources.
- Complex Setup: Advanced configurations may require technical expertise.
- Availability: Some GPU models may be out of stock.
GPU Mart provides GPU hosting solutions tailored for high-performance computing tasks such as AI/deep learning, rendering, streaming, and gaming.
They offer a variety of GPU models, flexible pricing plans, and comprehensive support to ensure optimal performance and scalability for complex projects.
Specification
| GPU TYPE | PRICE (USD/month) | GPU SPEC | RAM | VCPU |
|---|---|---|---|---|
| GeForce GT730 | 16.8 | 384 CUDA Cores, 2GB DDR3 | 8 GB | 6 CPU Cores |
| Quadro K620 | 21.00 | 384 CUDA Cores, 2GB DDR3 | 12 GB | 9 CPU Cores |
| Quadro P600 | 29.00 | 384 CUDA Cores, 2GB GDDR5 | 16 GB | 12 CPU Cores |
| GeForce GT710 | 45.00 | 192 CUDA Cores, 1GB DDR3 | 16 GB | Quad-Core Xeon X3440 |
| Quadro P600 | 52.00 | 384 CUDA Cores, 2GB GDDR5 | 32 GB | Quad-Core Xeon E5-2643 |
| Quadro P620 | 59.00 | 512 CUDA Cores, 2GB GDDR5 | 32 GB | Eight-Core Xeon E5-2670 |
| Quadro P1000 | 64.00 | 640 CUDA Cores, 4GB GDDR5 | 32 GB | Eight-Core Xeon E5-2690 |
| GeForce GTX1650 | 99.00 | 896 CUDA Cores, 4GB GDDR5 | 64 GB | Eight-Core Xeon E5-2667v3 |
| Quadro T1000 | 99.00 | 896 CUDA Cores, 8GB GDDR6 | 64 GB | Eight-Core Xeon E5-2690 |
| Tesla K80 | 109.00 | 4992 CUDA Cores, 24GB GDDR5 | 64 GB | Eight-Core Xeon E5-2690 |
2. Hostkey
- High-Performance GPUs
- Flexible Configurations
- Pre-installed AI Frameworks
- Unmetered Bandwidth
- Starting $152/month
Pros
- Scalability
- DDoS Protection
- Eco-Friendly
Cons
- Complexity
- Availability: Custom servers may have a longer setup time.
Hostkey offers the cheapest GPU VPS with powerful cards like the NVIDIA RTX A4000/A5000/A6000 and Tesla A100/H100.
These servers are designed for high-load tasks such as 3D modeling, rendering, machine learning, VR, and VDI. They feature fast NVMe disks, large storage, high-performance CPUs, and unmetered 1 Gbps connectivity.
Custom configurations and instant servers with pre-installed AI frameworks (TensorFlow, PyTorch, Caffe, etc.) are available.
Specifications:
| GPU TYPE | PRICE (EUR) | GPU SPEC | RAM | VCPU |
|---|---|---|---|---|
| GTX 1080 | 152 | 4 cores x 3.5GHz | 16 GB | Xeon E3-1230v5 3.4GHz (4 cores) |
| GTX 1080Ti | 180 | 4 cores х 3.5GHz | 16 GB | Xeon E3-1230v6 3.5GHz (4 cores) |
| RTX 3060 | 204 | Xeon E3-1230v6 3.5GHz (4 cores) | 32 GB | 240Gb SSD |
| GTX 1080Ti | 208 | 10 cores х 2.8GHz | 64 GB | 240Gb SSD + 3Tb SATA |
| RTX 3080 | 419 | AMD Ryzen 9 3900X 3.8GHz (12 cores) | 32 GB | 480Gb SSD |
| RTX 3090 | 510 | Xeon E3-1230v6 3.5GHz (4 cores) | 32 GB | 480Gb NVMe SSD |
| RTX 3090 | 517 | AMD Ryzen 9 3900X 3.8GHz (12 cores) | 64 GB | 512Gb NVMe SSD |
| RTX 3090 | 1006 | Xeon E-2288G 3.7GHz (8 cores) | 64 GB | 960Gb NVMe SSD |
| RTX 3090 | 1013 | AMD Ryzen 9 3900X 3.8GHz (12 cores) | 128 GB | 1Tb NVMe SSD |
| GTX 1080Ti | 1345 | 2xXeon E5-2637v4 3.5GHz (4 cores) | 128 GB | 2x960Gb SSD |
| RTX 3090 | 1998 | Xeon E-2288G 3.7GHz (8 cores) | 128 GB | 960Gb NVMe SSD |
3. PaperSpace
- Designed for AI, ML, and deep learning
- Simple to use GPU cloud platform
- Powerful Gradient and Core products for developers
- High-speed storage and low latency networking
- Starting at $324/month
Pros
- Intuitive interface
- Top-notch performance for GPU tasks
- Optimized for data scientists and developers
- Competitive pricing
Cons
- Limited data center locations
- Some advanced configurations require manual setup
PaperSpace has carved a niche in the hosting industry with its specialized offerings for AI and deep learning tasks. Their platform provides a seamless experience, allowing professionals and researchers to harness the power of GPU without complex setups.
Their cloud platform is lauded for its simplicity, making GPU-accelerated workflows accessible to users with varying technical backgrounds. Coupled with their Gradient and Core products, developers find a rich environment tailored to their needs.
While PaperSpace offers impressive speeds and reliability, users might find some limitations in terms of data center locations. Nevertheless, for those seeking a dedicated GPU cloud platform with an emphasis on AI and ML tasks, PaperSpace is a top contender.
You have to know that PaperSpace is a company owned by DigitalOcean.
Specifications:
NVIDIA GPU
| GPU Type | Price | GPU Spec | RAM | vCPU | Multi-GPU Types |
|---|---|---|---|---|---|
| M4000 | $0.45/hour | 8 GB GPU | 30 GB | 8 | None |
| P4000 | $0.51/hour | 8 GB GPU | 30 GB | 8 | 2x, 4x |
| P5000 | $0.78/hour | 16 GB GPU | 30 GB | 8 | 2x, 4x |
| P6000 | $1.10/hour | 24 GB GPU | 30 GB | 8 | 2x, 4x |
| V100 | $2.30/hour | 16 GB GPU | 30 GB | 8 | 2x, 4x |
| RTX4000 | $0.56/hour | NVIDIA RTX4000 GPU | 30 GB | 8 | 2x, 4x |
| RTX5000 | $0.82/hour | NVIDIA RTX5000 GPU | 30 GB | 8 | 2x, 4x |
| A4000 | $0.76/hour | NVIDIA A4000 GPU | 45 GB | 8 | 2x, 4x |
| A5000 | $1.38/hour | NVIDIA A5000 GPU | 45 GB | 8 | 2x, 4x |
| A6000 | $1.89/hour | NVIDIA A6000 GPU | 45 GB | 8 | 2x, 4x |
| A100 | $3.09/hour | NVIDIA A100 GPU | 90 GB | 12 | 2x, 4x, 8x |
4. LambdaLabs
- Designed for deep learning tasks
- High-performance GPUs
- Optimized software stack for AI workflows
- Professional support for deep learning projects
- Custom pricing based on requirements
Pros
- Turn-key deep learning solutions
- Optimized for best performance in AI tasks
- State-of-the-art hardware components
- Active community and expert support
Cons
- Higher price point compared to competitors
- May be overkill for non-deep learning tasks
LambdaLabs specializes in delivering solutions for deep learning projects. By merging high-performance GPUs with an optimized software stack, they have created a unique niche for AI researchers and professionals.
One of the standout features of LambdaLabs is their turn-key solutions that remove the complexity from setting up deep learning environments. However, this specialized focus means their services might come at a premium compared to more generalized VPS providers. Nevertheless, for AI enthusiasts and professionals, LambdaLabs promises a premium experience tailored for deep learning.
Specifications
| Instance Type | GPU | GPU Memory | vCPUs | Storage | Network Bandwidth (Gbps) | Per Hour Price | Term | # of GPUs |
|---|---|---|---|---|---|---|---|---|
| Reserved | 8x NVIDIA H100 | H100 SXM | 80 GB | 20 TB NVMe SSD local storage minimum | 3200 | $1.89/H100/hour | 3-years | 64 – 60,000 |
| Sprint | 8x NVIDIA H100 | H100 SXM | 80 GB | 27 TB NVMe SSD local storage minimum | 3200 | $4.85/H100/hour | 3-months | 248 |
5. OVHCloud
- Specialized in GPU-intensive applications
- Extensive range of customizable servers
- Global data centers to cater to different regions
- Anti-DDoS protection standard with all servers
- Starting at $5.99/month
Pros
- High-performance infrastructure
- Flexible configurations for GPU needs
- Competitive pricing model
- Excellent customer support
Cons
- Complex interface for beginners
- Additional costs for premium support
OVHCloud is an industry leader in GPU VPS hosting solutions. Known for its scalable and reliable infrastructure, it caters to professionals requiring GPU-intensive applications, be it for AI, deep learning, or complex simulations.
With data centers located across multiple continents, OVHCloud ensures low latency and high-speed connections for users everywhere. This is coupled with their specialized anti-DDoS protection that ensures uninterrupted service.
Pricing is flexible, allowing both small developers and large enterprises to find a plan that suits their needs. The hosting provider offers an extensive range of configurations, ensuring that every user can customize their server to their specific requirements.
OVHCloud's reputation for high performance, top-notch security, and extensive customization options makes it an excellent choice for anyone in need of GPU-powered hosting solutions.
Specifications
NVIDIA Tesla V100S Features
| Performance with NVIDIA GPU Boost | Bidirectional connection bandwidth | CoWoS Stacked HBM2 memory |
|---|---|---|
| double-precision, 7 tera FLOPS single-precision, 14 tera FLOPS deep learning, 112 teraFLOPS | PCIe 32GB/s | capacity, 32GB HBM2bandwidth, 900GB/s |
6. Linode
- GPU plans optimized for machine learning, AI, and more
- Flat and transparent pricing
- 11 global data centers
- 100% uptime SLA
- Starting at $10/month
Pros
- Consistent and predictable pricing
- Powerful GPU instances
- Highly regarded customer support
- Dedicated CPU options
Cons
- Lacks some advanced features
- No built-in DDoS protection
Linode, with its rich history in the cloud hosting sphere, is a favorite among developers and professionals alike for GPU VPS solutions. They offer specialized GPU plans tailored for high-performance tasks such as machine learning, graphics rendering, and artificial intelligence.
One of Linode's strong suits is its clear, transparent, and flat pricing. This makes it easier for users to anticipate costs without any hidden fees. With a vast network of 11 global data centers, they provide a robust and speedy infrastructure ensuring that applications run smoothly regardless of the user's location.
Linode's commitment to service is evident in their 100% uptime SLA. They ensure that their services remain reliable, with top-tier customer support ready to assist at any time. However, they prioritize simplicity, which means while they offer powerful core features, some advanced features found in other platforms might be absent.
Overall, Linode stands as a solid choice for GPU hosting, especially for those who appreciate transparency and straightforwardness in their hosting solutions.
Specifications
Quadro RTX 6000 Specs
| CUDA Cores (Parallel-Processing) | 4,608 |
|---|---|
| Tensor Cores (Machine & Deep Learning) | 576 |
| RT Cores (Ray Tracing) | 72 |
| GPU Memory | 24 GB GDDR6 |
| RTX-OPS | 84T |
| Rays Cast | 10 Giga Rays / Sec |
| FP32 Performance | 16.3 TFLOPS |
7. Google Cloud
- High-performance GPU solutions
- Extensive global infrastructure
- Integrated with various Google services
- Real-time analytics and machine learning capabilities
- Varies based on configuration
Pros
- Highly scalable solutions
- Comprehensive developer tools
- Robust security measures
- Wide array of machine learning tools
Cons
- Steep learning curve for newcomers
- Cost can be unpredictable with complex setups
Google Cloud, a heavyweight in the cloud industry, provides GPU servers that are both powerful and scalable. Leveraging its vast global infrastructure, Google Cloud ensures that applications achieve optimal performance regardless of their scale.
What sets Google Cloud apart is its seamless integration with other Google services and its state-of-the-art machine learning and analytics tools. However, with such a wide array of features, newcomers might find the platform a tad overwhelming. Regardless, for enterprises and professionals seeking top-tier GPU solutions, Google Cloud remains a premium choice.
Read More: Google Cloud VPS Pricing 2023 – Does it worth it?
Specifications:
| Model | GPUs | GPU memory | GPU price (USD) | 1 year commitment price** (USD) | 3 year commitment price** (USD) | Spot price* (USD) |
|---|---|---|---|---|---|---|
| NVIDIA T4 | 1 GPU | 16 GB GDDR6 | $0.35 per GPU | $0.220 per GPU | $0.160 per GPU | $0.1155 per GPU |
| 2 GPUs | 32 GB GDDR6 | |||||
| 4 GPUs | 64 GB GDDR6 | |||||
| NVIDIA P4 | 1 GPU | 8 GB GDDR5 | $0.60 per GPU | $0.378 per GPU | $0.270 per GPU | $0.216 per GPU |
| 2 GPUs | 16 GB GDDR5 | |||||
| 4 GPUs | 32 GB GDDR5 | |||||
| NVIDIA V100 | 1 GPU | 16 GB HBM2 | $2.48 per GPU | $1.562 per GPU | $1.116 per GPU | $0.777 per GPU |
| 2 GPUs | 32 GB HBM2 | |||||
| 4 GPUs | 64 GB HBM2 | |||||
| 8 GPUs | 128 GB HBM2 | |||||
| NVIDIA P100 | 1 GPU | 16 GB HBM2 | $1.46 per GPU | $0.919 per GPU | $0.657 per GPU | $0.43 per GPU |
| 2 GPUs | 32 GB HBM2 | |||||
| 4 GPUs | 64 GB HBM2 | |||||
| NVIDIA K80 | 1 GPU | 12 GB GDDR5 | $0.45 per GPU | $0.283 per GPU | Not available in this region | $0.0394 per GPU |
| 2 GPUs | 24 GB GDDR5 | |||||
| 4 GPUs | 48 GB GDDR5 | |||||
| 8 GPUs | 96 GB GDDR5 | |||||
8. AWS EC2
- Reliable and scalable GPU instances
- Wide range of GPU types to cater to different workloads
- Seamless integration with AWS services
- Robust security and monitoring tools
- Price varies based on the GPU instance and region
Pros
- Highly customizable instances
- World-class data center infrastructure
- Perfect for large-scale GPU projects
- Supports various operating systems and frameworks
Cons
- Can be complex for beginners
- Cost structure can be confusing
AWS EC2 stands at the forefront of cloud solutions, offering GPU instances that are both versatile and powerful. Known for its vast infrastructure and reliability, EC2 provides a range of GPU types, catering to a myriad of workloads from gaming to deep learning.
With its seamless integration with other AWS services, EC2 ensures an efficient workflow. However, its extensive feature set might be daunting for newcomers. The flexibility and robustness come at the expense of complexity, but for those who can navigate it, AWS EC2 offers unparalleled GPU capabilities.
Specifications:
- Amazon EC2 P3 Instances have up to 8 NVIDIA Tesla V100 GPUs.
- Amazon EC2 P4 Instances have up to 8 NVIDIA Tesla A100 GPUs.
- Amazon EC2 G3 Instances have up to 4 NVIDIA Tesla M60 GPUs.
- Amazon EC2 G4 Instances have up to 4 NVIDIA T4 GPUs.
- Amazon EC2 G5 Instances have up to 8 NVIDIA A10G GPUs.
- Amazon EC2 G5g Instances have Arm-based AWS Graviton2 processors.
9. Microsoft Azure
- Powerful GPU-based virtual machines
- Seamlessly integrates with other Microsoft products
- Vast suite of cloud services
- Hybrid cloud capabilities
- Varied pricing depending on VM type and region
Pros
- Scalable and flexible solutions for enterprises
- Comprehensive security features
- Strong support and extensive documentation
- Commitment to sustainability and green energy
Cons
- Can be overwhelming for beginners
- Complex billing and pricing model
Microsoft Azure stands as a titan in the cloud services industry, offering an extensive suite of tools and services that cater to businesses of all sizes. Their GPU-based virtual machines are highly sought-after for tasks ranging from deep learning model training to graphics rendering.
One of Azure's standout features is its seamless integration with the broader Microsoft ecosystem. Organizations deeply entrenched in Microsoft's software, like Office 365 or Dynamics, will find Azure's connectivity and integration capabilities invaluable. The hybrid cloud capabilities also ensure businesses can maintain a balance between on-premises and cloud resources.
While Azure offers a robust suite of tools, newcomers might find its extensive offerings a bit daunting. The platform's pricing can also be intricate, demanding potential users to thoroughly assess and predict their usage to avoid unexpected costs. However, with its commitment to innovation and a vast array of services, Azure continues to be a formidable choice for enterprises worldwide.
Specifications
| VM Series | Description | GPU Used | CPU Used | Application & Use Case |
|---|---|---|---|---|
| NCv3-series | Optimized for compute-intensive GPU-accelerated applications. | NVIDIA’s Tesla V100 GPU | – | CUDA, OpenCL apps, AI, Deep Learning |
| NC T4_v3-series | Focused on inference workloads. | NVIDIA's Tesla T4 GPU | AMD EPYC2 Rome processor | AI, Deep Learning |
| ND A100 v4-series | Focused on scale-up and scale-out deep learning training and accelerated HPC applications. | 8 NVIDIA A100 TensorCore GPUs (40 GB each) | – | Deep Learning, HPC |
| NGads V620-series (preview) | Optimized for high performance, interactive gaming experiences hosted in Azure. | AMD Radeon PRO V620 GPU | AMD EPYC 7763 (Milan) | Gaming |
| NV-series | Optimized for remote visualization, streaming, gaming, encoding, and VDI scenarios. | NVIDIA Tesla M60 GPU | – | OpenGL, DirectX |
| NVv3-series | Optimized for remote visualization, streaming, gaming, encoding, and VDI scenarios. | NVIDIA Tesla M60 GPU | – | OpenGL, DirectX |
| NVv4-series | Optimized for VDI and remote visualization with partitioned GPUs. | AMD Radeon Instinct MI25 GPU | – | VDI, Remote Visualization (Only Windows OS) |
| NDm A100 v4-series | A flagship addition for high-end Deep Learning training and tightly coupled scale-up and scale-out HPC workloads. Starts with a single VM. | 8 NVIDIA Ampere A100 80GB Tensor Core GPUs | – | High-end Deep Learning, HPC |
Conclusion
In this article, I hope you've found it enjoyable and identified a VPS that meets your needs. I've endeavored to compile the best providers in circulation that offer this unique and rare service. In this listing, you'll find VPS systems for both Linux and Windows, so you can develop machine learning or any other application that requires powerful and dedicated GPUs
As one of the co-founders of Codeless, I bring to the table expertise in developing WordPress and web applications, as well as a track record of effectively managing hosting and servers. My passion for acquiring knowledge and my enthusiasm for constructing and testing novel technologies drive me to constantly innovate and improve.
Expertise:
Web Development,
Web Design,
Linux System Administration,
SEO
Experience:
15 years of experience in Web Development by developing and designing some of the most popular WordPress Themes like Specular, Tower, and Folie.
Education:
I have a degree in Engineering Physics and MSC in Material Science and Opto Electronics.
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