High-Performance GPU Hosting & Rental for AI, Rendering, and Cloud Compute

Deploy dedicated GPU servers or flexible GPU rentals in minutes. Built for AI inference, 3D rendering, and high-performance applications on cloud that demand consistent compute power. From short-term GPU rental to fully dedicated GPU servers, run your projects on a stable environment with a reliable and trustworthy GPU hosting provider.

18K+

GPU Servers Delivered

3.1K+

Active Graphics Cards

7Year

GPU Hosting Expertise

25+

Nvidia GPU Models

Enterprise-Grade Nvidia GPU Servers for Demanding Workloads

Each GPU is deployed in a dedicated server environment with high-core CPUs, large-capacity ECC memory, NVMe storage, and high-bandwidth network connectivity — delivering stable performance for AI, rendering, and data-intensive workloads.
Nvidia GPUsGPU MemoryCPUStorageNetworkBest ForOrder
RTX PRO 6000 (Blackwell) 🔥96GB32Cores400GB SSD1GbpsLarge AI models, LLM inference, High workloads
RTX PRO 5000 (Blackwell) 🔥48GB24Cores320GB SSD500MbpsAI Inference, simulation, advanced rendering
RTX PRO 4000 (Blackwell) 🔥24GB24Cores320GB SSD500MbpsMid-scale AI workloads, 3D rendering, visual computing
RTX PRO 2000 (Blackwell) 🔥16GB16Cores240GB SSD300MbpsEntry AI development, lightweight rendering, GPU acceleration
RTX 5090 🔥32GB32Cores400GB SSD500MbpsAI experimentation, creative workloads, GPU compute tasks
RTX 5060 🔥8GB16Cores240GB SSD200MbpsLight AI inference, development, GPU-accelerated apps
RTX 409024GB36Cores240GB SSD + 2TB NVMe + 8TB SATA100M-1Gbps Shared, UpgradableDeep learning, Stable Diffusion, GPU rendering
NVIDIA H10080GB HBM36Cores240GB SSD + 2TB NVMe + 8TB SATA1GbpsLarge-scale AI training, transformer models, HPC
NVIDIA A10080GB HBM36Cores240GB SSD + 2TB NVMe + 8TB SATA1GbpsAI training, inference clusters, data analytics
RTX A600048GB36Cores240GB SSD + 2TB NVMe + 8TB SATA1GbpsRendering, simulation, AI model training
RTX A500024GB24Cores240GB SSD + 2TB SSD100M-1Gbps Shared, UpgradableAI development, content creation, visualization
RTX A400016GB24Cores320GB SSD500MbpsLightweight AI tasks, CAD, GPU rendering
RTX A4048GB36Cores240GB SSD + 2TB NVMe + 8TB SATA100M-1Gbps Shared, UpgradableVirtual workstations, rendering farms, AI inference
Details of GPU Server Plansarrow_circle_right

Keys Features of GPU Hosting & Rental

GPU server with stable operation and continuous performance in enterprise-class environments.
Consistent GPU Performance

Consistent GPU Performance

No resource throttling or shared GPU contention. Designed for sustained workloads like AI training and long render jobs.
Dedicated Server Environment

Dedicated Server Environment

GPU resources run in isolated server environments to ensure predictable compute behavior.

✨ Optimized for Long-Running Tasks

Ideal for AI model training, large inference jobs, simulations, and rendering that run for days or weeks.
Data Center Infrastructure

Data Center Infrastructure

Hosted in professional US data center facilities with redundant power and cooling systems.
Blackwell Architecture

Blackwell Architecture

The new Blackwell architecture is designed specifically for AI training and inference.

✨ Enterprise Hardware Foundation

High-core CPUs, ECC memory, and NVMe storage built for continuous high-load operation.
24/7 Technical Support

24/7 Technical Support

Experienced engineers available to assist with system, network, and deployment issues.
Proactive Infrastructure Monitoring

Proactive Infrastructure Monitoring

Server and network health are continuously monitored to maintain operational stability.

✨ Operational Reliability

Infrastructure designed for continuous uptime and dependable resource access.
Low-Latency Remote Access

Low-Latency Remote Access

Smooth remote desktop, SSH, and development access.
Public IP & Full Port Control

Public IP & Full Port Control

Flexible network configuration with configurable firewall and port management.

✨ Network & Access

Supports large dataset transfers, remote workflows, and distributed training.
Full Root / Administrator Access

Full Root / Administrator Access

Install and configure your own drivers, frameworks, and software stack.
Persistent Storage Environment

Persistent Storage Environment

Your data and environments remain intact for long-term projects.

✨ System Flexibility

Windows & Linux OS are Compatible with major AI frameworks, rendering engines, and development tools.
No Preemption or Forced Reclaims

No Preemption or Forced Reclaims

Resources are not reclaimed unexpectedly, ensuring training and rendering jobs complete without interruption.
Ideal for Continuous AI Training

Ideal for Continuous AI Training

Designed for workloads that run 24/7 over extended periods.

✨ Built for Long-Term Workloads

Suitable for teams and businesses running ongoing AI and compute services.

What Can You Do with GPU Servers?

DBM offers various GPU Hosting for AI, ML, DL & LLMs. The versatility and powerful functions of GPU server hosting make it a valuable resource for a wide range of applications, especially those that need a lot of parallel processing capabilities.
Machine Learning and AI

Machine Learning and AI

GPU servers are commonly used to train and run machine learning models and deep learning algorithms. GPUs can handle the massively parallel computations involved in these applications, reducing training time and improving accuracy. GPU servers can be used in a variety of machine learning and artificial intelligence applications, such as image and speech recognition, natural language processing, and recommender systems.
Scientific Simulations

Scientific Simulations

Many scientific simulations, such as those used in weather forecasting, fluid dynamics, and materials science, require significant computing power. GPUs can speed up these simulations by processing the large amounts of data involved in parallel. GPU servers are also commonly used for simulation-based optimization and machine learning-based data analysis in scientific research.
Video Rendering and Transcoding

Video Rendering and Transcoding

Video rendering and transcoding involve processing large amounts of data to create high-quality video content. GPUs dedicated servers can speed up this process by parallelizing the video encoding and decoding process. This makes GPU servers ideal for video production, streaming, and editing applications.
Gaming and Virtual Reality

Gaming and Virtual Reality

High-performance dedicated GPU servers are used to support online gaming and virtual reality applications that require massive processing power and high frame rates. This enables players to experience a more realistic and immersive gaming experience. Cloud gaming providers typically use GPU servers to deliver gaming services accessible from any device.
OBS Streaming

OBS Streaming

GPU dedicated Servers can provide significant advantages in streaming, such as improving performance, accelerating rendering, enabling customization, and allowing you to multitask. Especially when you use software such as OBS (Open Broadcast Software), the powerful GPU also allows you to perform multiple tasks at the same time when streaming.
Emulators

Android Emulators

GPU Dedicated Servers can be a great option for running Android emulators, especially if you're running multiple instances at once or need high-performance and customization options. By providing fast processing, improved performance, and the ability to customize your settings, a GPU Dedicated Server can help you to create a stable and efficient environment for your Android emulator.

What People Say About DatabaseMart GPU Hosting Solutions

Our commitment to integrity and caring service has earned DatabaseMart countless positive reviews and recommendations from customers.

User Case Studies

Leveraging Database Mart for High-Performance Computing Solutions
AI Researcher
Game Developer
Live Streaming Company
stories
AI Researcher

Background

Ellery is an AI researcher working on training deep learning models for image classification tasks. She requires high-performance computing resources with GPU capabilities to train and optimize her AI models.

Challenges

Need for powerful servers with multiple GPUs to accelerate the training process and handle large datasets.

Requirement for reliable and responsive technical support to troubleshoot issues and optimize model training algorithms.

Desire for cost-effective hosting solutions to minimize expenses while maximizing computing power.

Solution

Ellery chose GPU Mart for its dedicated GPU servers optimized for AI model training. With GPU Mart's state-of-the-art hardware and expert technical support, she could efficiently train and optimize her deep learning models for image classification tasks. The cost-effective pricing of GPU Mart's hosting solutions allowed her to maximize her computing budget without compromising performance.

Outcome

Ellery's AI research projects progressed rapidly with GPU Mart's high-performance servers. She achieved significant improvements in model accuracy and training efficiency, thanks to GPU Mart's reliable infrastructure and responsive technical support. With GPU Mart's scalable hosting solutions, Ellery could easily adjust server resources to meet changing research requirements and accommodate growing datasets.

FAQs of GPU Dedicated Server Hosting

Find answers to the most frequently asked questions about GPU dedicated server hosting.

What is hosting with GPU?

GPU hosting is a hosting for servers packed with graphics cards, designed to harness this raw processing power. Using an offloading process, the CPU can hand specific tasks to the GPUs, increasing performance.

What is GPU Dedicated Server?

A GPU dedicated server is a physical server dedicated to a user or organization and equipped with one or more GPUs (graphics processing units). These servers are usually used for high-performance computing tasks that require a lot of parallel processing capabilities, such as scientific simulation, machine learning, and video rendering.
Compared with CPU-based servers, GPU servers are usually much faster for tasks that can be processed in parallel across multiple cores. This is because GPUs have much more cores than CPUs, which makes them very suitable for decomposing into many small computing tasks that can be executed at the same time. GPU dedicated servers can be purchased or leased from various hosting providers. They differ in GPU type, GPU quantity, available memory and storage. These servers can be managed remotely, allowing users to access their computing resources from anywhere through Internet connections.

What is dedicated server with GPU Rental?

A dedicated server with GPU rental is a service offered by hosting providers that allows users to rent a dedicated physical server equipped with one or more GPUs (graphics processing units) for a specified period of time. This service can be particularly useful for tasks that require high-performance computing resources, such as machine learningientific simulations, and video rendering.
Unlike virtualized GPU instances, dedicated servers with GPU rental offer users full access to the physical hardware, providing more control and customization options. Users can install their own software and configure the server to meet their specific requirements. Additionally, dedicated servers with GPU rental can offer more consistent performance and higher throughput compared to shared resources. When renting a dedicated server with GPU, users can typically choose from a range of specifications, including the type and number of GPUs, the amount of memory and storage, and the processing power of the CPU. The cost of the service will depend on the specifications selected and the duration of the rental.

How do I choose the right GPU instance for my needs?

When choosing a GPU instance, you should consider factors such as the type and complexity of the applications you will be running, the amount of memory and storage you need, and the level of support and customization you require.

Can I use a GPU dedicated server for streaming or running Android emulators?

Yes, a GPU dedicated server can be used for streaming and running Android emulators. By providing improved performance, faster processing, multi-tasking, and customization options, a GPU dedicated server can help you to create a stable and efficient environment for these applications.

What are some common GPUs used in hosting environments?

Some common GPUs used in hosting environments include Nvidia GeForce, Quadro, Tesla, and RTX Server. The specific GPU you choose will depend on your needs and the applications you will be running.

Why put a GPU in a server?

Putting a GPU in a server can significantly increase its computing power, making it capable of handling more complex and demanding tasks. GPUs, or graphics processing units, are highly specialized processors that are designed to handle parallel computing tasks, such as those required for machine learning, scientific simulations, and gaming.
Compared to traditional central processing units (CPUs), GPUs are more efficient at handling compute-intensive workloads because they can perform multiple calculations simultaneously. This is due to the fact that GPUs have many more cores than CPUs, which allows them to process data much faster and in parallel.
By adding a GPU to a server, you can accelerate compute-intensive applications and reduce processing times, leading to improved performance, reduced latency, and increased efficiency. This is particularly important for applications that require real-time processing, such as video rendering, transcoding, and streaming, or for tasks that involve large datasets, such as machine learning and data analytics.

How to get a free trial for GPU server?

We’re excited to offer a 24-hour free trial for new clients to test our servers. To request a trial, please follow these steps:

1. Choose a plan and click 'Order Now'.
2. Enter ‘24-hour free trial’ in the notes section and click “Check Out”.
3. Click 'Submit Trial Request' at the top right corner, and complete your personal information as instructed; no payment is required.

Once we receive your trial request, we’ll send you the login details within 30 minutes to 2 hours. If your request cannot be approved, you will be notified via email.