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Rent Remote Multiple Graphics Card Servers

Diverse range of multi GPU dedicated servers delivers unparalleled computing speed and parallel processing capabilities, ideal for applications that demand massive computational power.

GPU Model	CPU	Memory	Disk	Bandwidth	Price
3 x V100	36-Core Dual E5-2697v4	256GB RAM	240GB SSD+2TB NVMe+8TB SATA	1000Mbps Unmetered	$469.00/mo	Order Now
3 x RTX A5000	36-Core Dual E5-2697v4	256GB RAM	240GB SSD+2TB NVMe+8TB SATA	1000Mbps Unmetered	$539.00/mo	Order Now
2 x RTX 4090	36-Core Dual E5-2697v4	256GB RAM	240GB SSD+2TB NVMe+8TB SATA	1000Mbps Unmetered	$729.00/mo	Order Now
2 x RTX 5090	44-core Dual E5-2699v4	256GB RAM	240GB SSD+2TB NVMe+8TB SATA	1000Mbps Unmetered	$859.00/mo	Order Now
3 x RTX A6000	36-Core Dual E5-2697v4	256GB RAM	240GB SSD+2TB NVMe+8TB SATA	1000Mbps Unmetered	$899.00/mo	Order Now
4 x RTX A6000	44-core Dual E5-2699v4	512GB RAM	240GB SSD+4TB NVMe+16TB SATA	1000Mbps Unmetered	$1199.00/mo	Order Now
4 x A100	44-core Dual E5-2699v4	512GB RAM	240GB SSD+4TB NVMe+16TB SATA	1000Mbps Unmetered	$1249.50/mo	Order Now

Addons for Multi GPU Servers

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Additional Memory	16GB: $5.00/month 32GB: $9.00/month 64GB: $19.00/month 128GB: $29.00/month 256GB: $49.00/month	A $39 one-time setup fee applies.
Additional SSD Drives	240GB SSD: $5.00/month 960GB SSD: $9.00/month 2TB SSD: $19.00/month 4TB SSD: $29.00/month	A $39 one-time setup fee applies.
Additional SATA Drives	2TB SATA: $9.00/month 4TB SATA: $19.00/month 8TB SATA: $29.00/month 16TB SATA (3.5’ Only): $39.00/month	A $39 one-time setup fee applies.
Additional Dedicated IP	$2.00/month/IPv4 or IPv6	IP purpose required. Maximum 8 per package.
Bandwidth Upgrade	Upgrade to 200Mbps(Shared): $10.00/month Upgrade to 1Gbps(Shared): $20.00/month	The bandwidth of your server represents the maximum available bandwidth. Real-time bandwidth usage depends on the current situation in the rack where your server is located and the shared bandwidth with other servers. The speed you experience may also be influenced by your local network and geographical distance from the server.
Private Network	1Gbps Internal Port: $10/month 10Gbps Internal Port: $20/month	A $39 one-time setup fee applies.
Dedicated Hardware Firewall	$99.00/month. A $39 one-time setup fee applies.	Dedicated firewall allocates one user to a Cisco ASA 5520/5525 firewall, providing superuser access for independent and personalized configurations, such as firewall rules and VPN settings.
Shared Hardware Firewall	$29.00/month. A $39 one-time setup fee applies.	Shared firewall is used by 2-7 users who share a single Cisco ASA 5520 firewall, including shared bandwidth. It does not have superuser privileges.
Remote Data Center Backup(Windows Only)	40GB Disk Space: $30.00/month 80GB Disk Space: $60.00/month 120GB Disk Space: $90.00/month 160GB Disk Space: $120.00/month	We will use Backup For Workgroups to backup your server data (C: partition only) to our remote data center servers twice per week. You can restore the backup files in your server at any time by yourself.
HDMI Dummy	$15 setup fee per server	A one-time setup fee is charged for each server and cannot be transferred to other servers.
NVLink for GPU Server	2xNVLink for 4xA6000 cards: $60/month 3xNVLink for 6xA6000 cards: $90/month 4xNVLink for 8xA6000 cards: $120/month 6xNVLinks for 4xA100 cards: $180/month A $39 one-time setup fee applies.	NVLink is a high-speed interconnect technology developed by NVIDIA that allows GPUs to communicate with each other and share data at much faster rates than traditional PCIe connections. For an accurate quote, please contact us.

Reasons to Choose our Multiple GPU Servers

Our state-of-the-art Multi- GPU Servers are designed to meet the most demanding computational needs of modern businesses and research institutions.

Parallel Computing with Multi-GPU Interconnect

High-speed GPU interconnect enables efficient data and model parallelism across multiple GPUs, significantly improving compute utilization and scaling efficiency for AI training, inference, and HPC workloads.

Distributed Training with NVLink

Optional NVLink support delivers high-bandwidth, low-latency GPU-to-GPU communication, reducing synchronization overhead and accelerating distributed training for large-scale AI models and multi-GPU workloads.

Best Cost-Performance

Achieve the lowest cost per GPU and per GB of memory/disk with fully dedicated hardware. No virtualization overhead and no hidden fees, maximizing value for every dollar spent.

High-Speed Storage & RAM

Large RAM and high-capacity NVMe SSDs are included by default, ensuring fast data throughput and stable performance for LLM inference, AI training, and data-intensive workloads.

Reliable and Secure

Backed by 7 years of GPU server operation experience and premium components. Enjoy 99.9% uptime, data integrity, and optional firewall protection.

Expert Support and Maintenance

Our GPU specialists provide 24/7 support from deployment to ongoing maintenance. Professional assistance is always included at no extra cost.

Unlock the Potential of Multi-GPU Servers

Multi GPU servers are designed for workloads that demand scale, parallelism, and sustained performance — from LLM training and inference to enterprise-grade AI and HPC applications.

AI Model Training & Inference

Scientific Computing & HPC

3D Rendering & Visual Effects

Multi-Tenant & Virtualization

AI Model Training & Inference

Large language models (7B–70B) and multi-task deep learning workloads require massive GPU compute and VRAM capacity. Multi-GPU dedicated servers enable data and model parallelism, faster parameter synchronization, and stable long-running training without resource contention. Fully compatible with TensorFlow, PyTorch, Hugging Face, and other major frameworks.

Explore Stable Diffusion Multiple GPU, Ollama Multiple GPU, , and AI Image Generator Multiple GPU.

Scientific Computing & HPC

Scientific simulations, matrix operations, and numerical modeling demand parallel compute performance and low-latency inter-GPU communication. Multi-GPU physical servers provide predictable scaling, high compute density, and stable throughput, making them ideal for HPC workloads that cannot tolerate virtualization overhead or shared resources.

3D Rendering & Visual Effects

Professional 3D rendering and visual effects pipelines rely on large VRAM capacity and parallel GPU processing. Multi-GPU dedicated servers accelerate frame rendering, scene compilation, and high-resolution output, significantly reducing render times and improving workflow efficiency for studios and creative teams.

Explore Rendering GPU Hosting

Multi-Tenant & Virtualization

Multi-GPU physical servers support GPU partitioning and virtualization for isolated workloads while maintaining consistent performance. Dedicated hardware ensures predictable resource allocation across tenants, making it suitable for internal platforms, managed services, and environments requiring strict performance isolation.

Multi-GPU Server AI Model Selection

Our multi-GPU servers are tailored to different model sizes and workloads. Refer to the tables below to find the recommended GPU setup based on your model requirements. Sample test data for some of our configurations are shown in the figure.

Use Case:

This 2×RTX 4090 dual GPU setup is ideal for medium-sized models (7B–16B), model fine-tuning, and high-concurrency inference. It delivers excellent performance while maintaining cost efficiency.
The 2×A100 multi-GPU configuration is perfect for large models (14B–32B) requiring multi-task concurrent inference or model training. It ensures stable performance and high throughput.
The 4×A6000 multi-GPU server is best for extra-large models (32B–72B), enterprise-scale training, and high-load inference. It maximizes performance for demanding workloads.

Multi GPU Server Architecture & Key Features

Predictable Performance

Stable throughput under sustained high-load workloads. PCIe passthrough ensures direct GPU access, with optional NVLink for higher inter-GPU bandwidth.

Production-Ready Environment

Pre-optimized GPU drivers and CUDA stack enable faster deployment from testing to production.

Simplified Multi-GPU Management

Unified architecture makes multi-GPU workloads easier to monitor, and manage.

Secure Network

Optional firewall and network isolation protect GPU workloads from unauthorized access. Custom rules allow clients to manage network access and secure their data.

FAQs of Multiple GPU Servers

What is multiple GPU server?

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A multiple GPU server is a high-performance computing system equipped with more than one graphics processing unit (GPU). These servers are designed to handle complex tasks such as artificial intelligence training, deep learning, rendering, and scientific simulations by leveraging the parallel processing power of multiple GPUs. They offer enhanced performance, scalability, and efficiency compared to single-GPU systems, making them essential for demanding computational workloads.

What are the rentable operating systems GPU servers?

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Our GPU servers offer a choice of operating systems, including popular Linux distributions like Ubuntu, CentOS, Debian, and more. Additionally, Windows Server and Windows 10 is available to suit diverse needs and preferences.

Is your GPU card shared or dedicated?

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Multiple GPU server comes equipped with dedicated multiple GPU cards, CPU, and other resources. As a user, you have full access and management permissions over these resources, ensuring optimal control and utilization for your specific tasks and applications.

Do you support hourly billing for multiple GPU dedicated server?

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All of our multiple GPU rental plans default to monthly billing.
If you need GPU services with hourly billing for flexible, short-term usage, please contact our sales team to check available plans.

Can I add or replace GPUs on my multi-GPU dedicated server?

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Our multi-GPU dedicated servers come with fixed hardware configurations per machine. Currently, you cannot add or replace GPUs on the same server after deployment. If you need a higher GPU count, a different GPU model, you can upgrade to a server with the desired configuration or contact us for customization.

What's the difference between Nvidia Ampere, Volta, and Ada Lovelace?

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Nvidia Ampere, Volta, and Ada Lovelace are all generations of graphics processing units (GPUs) developed by Nvidia.

1. Nvidia Ampere: GPU architecture published in 2020, focused on gaming and AI, with advanced ray tracing and AI capabilities.
2. Nvidia Volta: Previous GPU architecture (2017), optimized for high-performance computing (HPC) and AI, featuring Tensor Core technology for deep learning tasks.
3. Ampere succeedes both the Volta and Turing architectures. It is designed to address the most critical scientific, industrial, and business challenges by accelerating AI and high-performance computing (HPC) tasks. It excels at visualizing complex content for creating innovative products, immersive narratives, and futuristic cityscapes. With a focus on elastic computing, Ampere delivers unmatched acceleration for extracting insights from massive datasets across all scales.

What data centers can I choose for multi-GPU servers?

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Usually, customers can choose servers with multiple GPU in Dallas, Texas and Kansas City, Missouri of the USA. Due to stock limitations, we suggest you contact us via a ticket to confirm first.

What common applications can I run on multi-GPU servers?

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You can run all kinds of legal applications on the multiple GPU desktops, such as popular AI app: Stable Diffussion, LLaMA; rendering app: Octane; OBS, Cudo Mine, etc.

Contact Us for Custom GPU Solutions

Still can’t find the multiple GPU rental plan that fits your needs? Contact us for personalized recommendations and alternative solutions.

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Multiple GPU Dedicated Server Rental

Rent Remote Multiple Graphics Card Servers

Reasons to Choose our Multiple GPU Servers

Unlock the Potential of Multi-GPU Servers

AI Model Training & Inference

Scientific Computing & HPC

3D Rendering & Visual Effects

Multi-Tenant & Virtualization

Multi-GPU Server AI Model Selection

Multi GPU Server Architecture & Key Features

Predictable Performance

Production-Ready Environment

Simplified Multi-GPU Management

Secure Network

FAQs of Multiple GPU Servers

What is multiple GPU server?

What are the rentable operating systems GPU servers?

Is your GPU card shared or dedicated?

Do you support hourly billing for multiple GPU dedicated server?

Can I add or replace GPUs on my multi-GPU dedicated server?

What's the difference between Nvidia Ampere, Volta, and Ada Lovelace?

What data centers can I choose for multi-GPU servers?

What common applications can I run on multi-GPU servers?

Contact Us for Custom GPU Solutions