Supercharge Your AI and ML with GPU VPS.
Experience cutting-edge computing power with our GPU VPS. Designed for demanding workloads, our virtual private servers offer dedicated NVIDIA GPUs, ensuring lightning-fast performance for tasks like deep learning, machine learning, data science, and more. Enjoy the flexibility of scalable resources, customizable configurations, and robust security to meet your specific needs. Whether you're a researcher, developer, or data scientist, our GPU VPS provides the ideal environment to accelerate your projects.
- Powerful Nvidia GPU Servers
- Top Performance with AMD EPYC Processors
- Ultra-Fast SSD Storage, Upto 1 Gbps Network Speed
- State-of-the-art Tier IV India-Based Data Center
GPU (Graphics processing unit)
Graphics processing technology has evolved to deliver unique benefits in the world of computing. The latest graphics processing units (GPUs) unlock new possibilities in gaming, content creation, machine learning, and more. A graphics processing unit (GPU) is a specialized electronic circuit designed to rapidly manipulate and alter memory to accelerate the creation of images in a frame buffer intended for output to a display device. GPUs are used in embedded systems, mobile phones, personal computers, workstations, and game consoles. Modern GPUs are very efficient at manipulating computer graphics and image processing. Their highly parallel structure makes them more efficient than general-purpose central processing units (CPUs) for algorithms that process large blocks of data in parallel. In a personal computer, a GPU can be present on a video card or embedded on the motherboard. In certain CPUs, they are embedded on the CPU die.
A GPU (Graphics Processor Unit) is a familiar term – it’s the component that enables video and sophisticated graphics, such as video games, to run on the PC. GPU VPS Computing is a fast, stable, and elastic computing service based on GPU ideal for various scenarios such as deep learning training/inference, graphics processing, and scientific computing. GPU VPS Computing can be managed just like a standard VPS Virtual Machine instance with speed and ease. GPU is used together with a CPU to accelerate deep learning, analytics, and engineering applications for platforms ranging from artificial intelligence to cars, drones, robots, search engines, interactive speech, video recommendations and much more.
GPU VPS Plans
Experience the power of GPU acceleration in the VPS . Our GPU VPS offers dedicated GPU resources for demanding AI, machine learning, deep learning, and data-intensive workloads. With our scalable infrastructure, you can easily adjust your computing power to meet your project's needs.
1xA4000
₹13,700/MO
- RAM: 32 GB
- vCPU: 8
- Storage: 500 GB SSD
- Bandwidth: 2 TB
- IP Address: 1 Dedicated IP
- GPU: 1xA4000 Nvidia GPU
- CUDA Cores: 6144
- GPU Memory: 16GB
2xA4000
₹26,500/MO
- RAM: 64 GB
- vCPU: 16
- Storage: 1000 GB SD
- Bandwidth: 4 TB
- IP Address: 1 Dedicated IP
- GPU: 2xA4000 Nvidia GPU
- CUDA Cores: 6144
- GPU Memory: 16GB
3xA4000
₹38,900/MO
- RAM: 96 GB
- vCPU: 24
- Storage: 1500 GB SSD
- Bandwidth: 6 TB
- IP Address: 1 Dedicated IP
- GPU: 3xA4000 Nvidia GPU
- CUDA Cores: 6144
- GPU Memory: 16GB
4xA4000
₹51,500/MO
- RAM: 128 GB
- vCPU: 32
- Storage: 2000 GB SSD
- Bandwidth: 8 TB
- IP Address: 1 Dedicated IP
- GPU: 4xA4000 Nvidia GPU
- CUDA Cores: 6144
- GPU Memory: 16GB
1xA5000
₹17,800/MO
- RAM: 32 GB
- vCPU: 8
- Storage: 500 GB SSD
- Bandwidth: 2 TB
- IP Address: 1 Dedicated IP
- GPU: 1xA5000 Nvidia GPU
- CUDA Cores: 8192
- GPU Memory: 24GB
2xA5000
₹34,600/MO
- RAM: 64 GB
- vCPU: 16
- Storage: 1000 GB SSD
- Bandwidth: 4 TB
- IP Address: 1 Dedicated IP
- GPU: 2xA5000 Nvidia GPU
- CUDA Cores: 8192
- GPU Memory: 24GB
3xA5000
₹51,500/MO
- RAM: 96 GB
- vCPU: 24
- Storage: 1500 GB SSD
- Bandwidth: 6 TB
- IP Address: 1 Dedicated IP
- GPU: 3xA5000 Nvidia GPU
- CUDA Cores: 8192
- GPU Memory: 24GB
4xA5000
₹68,200/MO
- RAM: 128 GB
- vCPU: 32
- Storage: 2000 GB SSD
- Bandwidth: 8 TB
- IP Address: 1 Dedicated IP
- GPU: 4xA5000 Nvidia GPU
- CUDA Cores: 8192
- GPU Memory: 24GB
1xA6000
₹27,200/MO
- RAM: 32 GB
- vCPU: 8
- Storage: 500 GB SSD
- Bandwidth: 2 TB
- IP Address: 1 Dedicated IP
- GPU: 1xA6000 Nvidia GPU
- CUDA Cores: 10752
- GPU Memory: 48GB
2xA6000
₹53,500/MO
- RAM: 64 GB
- vCPU: 16
- Storage: 1000 GB SSD
- Bandwidth: 4 TB
- IP Address: 1 Dedicated IP
- GPU: 2xA6000 Nvidia GPU
- CUDA Cores: 10752
- GPU Memory: 48GB
3xA6000
₹79,500/MO
- RAM: 96 GB
- vCPU: 24
- Storage: 1500 GB SSD
- Bandwidth: 6 TB
- IP Address: 1 Dedicated IP
- GPU: 3xA6000 Nvidia GPU
- CUDA Cores: 10752
- GPU Memory: 48GB
4xA6000
₹1,05,500/MO
- RAM: 128 GB
- vCPU: 32
- Storage: 2000 GB SSD
- Bandwidth: 8 TB
- IP Address: 1 Dedicated IP
- GPU: 4xA6000 Nvidia GPU
- CUDA Cores: 10752
- GPU Memory: 48GB
1xA40
₹28,200/MO
- RAM: 32 GB
- vCPU: 8
- Storage: 500 GB SSD
- Bandwidth: 2 TB
- IP Address: 1 Dedicated IP
- GPU: 1xA40 Nvidia GPU
- CUDA Cores: 10752
- GPU Memory: 48GB
2xA40
₹55,500/MO
- RAM: 64 GB
- vCPU: 16
- Storage: 1000 TB SSD
- Bandwidth: 4 TB
- IP Address: 1 Dedicated IP
- GPU: 2xA40 Nvidia GPU
- CUDA Cores: 10752
- GPU Memory: 48GB
3xA40
₹82,600/MO
- RAM: 96 GB
- vCPU: 24
- Storage: 1500 GB SSD
- Bandwidth: 6 TB
- IP Address: 1 Dedicated IP
- GPU: 3xA40 Nvidia GPU
- CUDA Cores: 10752
- GPU Memory: 48GB
4xA40
₹1,09,800/MO
- RAM: 128 GB
- vCPU: 32
- Storage: 2000 GB SSD
- Bandwidth: 8 TB
- IP Address: 1 Dedicated IP
- GPU: 4xA40 Nvidia GPU
- CUDA Cores: 10752
- GPU Memory: 48GB
1xA100
₹88,500/MO
- RAM: 32 GB
- vCPU: 8
- Storage: 500 GB SSD
- Bandwidth: 2 TB
- IP Address: 1 Dedicated IP
- GPU: 1xA100 Nvidia GPU
- CUDA Cores: 6912
- GPU Memory: 80GB
2xA100
₹1,75,900/MO
- RAM: 64 GB
- vCPU: 16
- Storage: 1000 GB SSD
- Bandwidth: 4 TB
- IP Address: 1 Dedicated IP
- GPU: 2xA100 Nvidia GPU
- CUDA Cores: 6912
- GPU Memory: 80GB
3xA100
₹2,63,500/MO
- RAM: 96 GB
- vCPU: 24
- Storage: 1500 GB SSD
- Bandwidth: 6 TB
- IP Address: 1 Dedicated IP
- GPU: 3xA100 Nvidia GPU
- CUDA Cores: 6912
- GPU Memory: 80GB
4xA100
₹3,50,700/MO
- RAM: 128 GB
- vCPU: 32
- Storage: 2000 GB SSD
- Bandwidth: 8 TB
- IP Address: 1 Dedicated IP
- GPU: 4xA100 Nvidia GPU
- CUDA Cores: 6912
- GPU Memory: 80GB
GPU servers are suitable for a wide range of Industries
AI (Artificial Intelligence)
GPU servers are used in AI to provide more computing power and speed for deep learning and other intensive tasks. Companies often use GPU VPS computing to support and scale their AI workflows.
Machine Learning
HapiH Host's GPU VPS hosting is ideal for Big Data and machine learning applications, with the ability to quickly solve challenging computational problems with parallel-running queries and algorithms
Automobiles
GPU servers are used in the automobile industry for CAD and simulation, autonomous driving, virtual testing and validation, and image and video processing, helping to reduce costs and improve efficiency, accuracy, and product development.
Healthcare sector
GPU servers are used in the healthcare sector to process medical imaging data, analyze genetic and patient data, and support telemedicine applications, improving efficiency, reducing costs, and providing better care to patients.
Virtual infrastructure-based applications
GPU Servers provide improved performance, scalability, and security for VDI (Virtual Desktop Interface) applications, such as video editing and 3D modeling.
GPU Plan Features
AMD EPYC Server
Our GPU Server uses AMD EPYC Processors. AMD EPYC servers provide a powerful and versatile computing platform for enterprise-level applications, with high performance, scalability, and advanced security features.
99.95% Uptime SLA
Due to the highly redundant infrastructure, increased network connectivity, and enterprise-grade hardware, our GPU servers provide the best uptime of 99.95%. Our Tier-4 and ISO-certified data centres are highly secure, furnished and well-equipped with top-tier hardware.
Full Control
Get full root administrative access to your GPU servers! Change the programme settings, add or remove applications, control the accessible ports, and so much more.
Both Linux and Windows operating systems!
Both Linux and Windows operating systems are available for your use. Simply pick your preferred operating system, and it will be installed for you!
Up to 1 Gbps Network Speed
We make an effort to give you the best! Our cutting-edge network is configured for lightning-fast loading times. You can host websites and apps with no performance problems with a data transfer speed of 1Gbps.
Visitors can even enjoy some excellent surfing there.
Frequently Asked Questions
A GPU server is basically a type of computing server that has a GPU card that provides fast, flexible computing and a highly stable environment. It’s basically used in different scenarios like Artificial Intelligence, Machine Learning, deep learning, decoding, scientific computing, etc.
In the world of supercomputers, GPU is really popular, yet it utilizes the conventional concept of parallel processing. The GPU breaks big tasks into small tasks and functions on them in one go, however, unlike the CPU, that appears to work on a sequence of tasks. CPU can handle fewer tasks at a time, while GPU can handle several concurrent tasks at a time. Thus, GPUs offer a higher level of latency than CPUs. It's the best option to host resource-intensive applications.
CPUs are not built to run lots of tasks at the same time. They focus on one task at a time and then assign the task in sequence on a priority basis. It runs several tasks simultaneously and will lag the CPU, and the performance will be low. By adding a GPU server, you can distribute the demanding tasks to the GPU, and the CPU resources will remain free. The combination effectively reduces the CPU workload, and the GPU can escalate the computing task much faster.
It is general-purpose computing with the help of a Graphics Processing Unit (GPU). These calculations are done faster by using a GPU and a Central Processing Unit (CPU) together to speed them up. This is done for applications that are usually done by the CPU alone.
Standing for one trillion operations per second, a TFLOP measures directly the performance of your computer.
Look after the dedicated infrastructure. Then look at the CUDA Cores. If a GPU server doesn’t offer decent performance, don’t even bother. Also look for the SSL certificate. Your VPS hosting really needs to be as good as possible.
Our GPU dedicated servers support both Linux and Windows operating systems. You can choose the operating systems according to your requirements and we will install them for you. Here is the list.
• Debian
• CentOS
• Ubuntu
• Fedora
• Windows 2019, 2022
Yes, Hapih Host allows you to upgrade/downgrade easily as and when required.
We make use of AMD EPYC processors on our GPU-based servers. AMD EPYC processors offer enterprise-level computing with high performance, scalability, and advanced security.
Typically, we will deliver our systems with an OS of your choosing and that’s it. If needed you can purchase the paid add-on such as control panel etc.
The need for GPU dedicated servers is essential to run resources-intensive tasks like video editing, and quick access to high-definition images. Such tasks require graphic cards and a high amount of server resources. Hence, GPU is used over there.