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GPU Dedicated Servers for AI training, rendering, and compute-heavy workloads.
Enterprise GPU Dedicated Servers with isolated hardware, high-speed networking, full administrative access, and optional management for artificial intelligence, machine learning, deep learning, rendering, scientific computing, analytics, simulations, video processing, and other parallel workloads.
GPU servers should be matched to the workload before ordering.
Tell us whether you are training models, rendering frames, encoding video, running simulations, or testing inference pipelines. GPU choice, GPU memory, storage, OS, drivers, and management scope should be confirmed before deployment.
Dedicated acceleration for workloads that need more than CPU-only infrastructure.
GPU dedicated servers are built for businesses, developers, studios, research teams, and production environments that need stronger parallel processing for AI, machine learning, rendering, analytics, simulation, and graphics-heavy workloads.
Use this page when comparing managed dedicated servers, NVMe dedicated servers, managed server services, server monitoring, and server security services.
Servers Managed
Real Linux, cPanel, VPS, dedicated, and production server experience.
Years Experience
Long-term infrastructure operations and hosting support background.
HostAdvice Rating
Based on expert ratings and 23 user reviews.
GPU Dedicated Server Configurations
Base pricing includes GPU hardware, network, IP allocation, and infrastructure access. Management, monitoring, security, panels, driver stack work, and migrations are optional add-ons.
GPU plans are quote-sensitive by nature
Because GPU availability, driver requirements, OS choice, and workload expectations vary, plans with incomplete WHMCS links are routed to contact instead of a broken checkout link.
EliteCore G-3090
A practical single-GPU server for rendering, blockchain processing, graphics-heavy work, and entry compute acceleration.
- 1x NVIDIA GeForce RTX 3090
- Xeon Gold 5218R • 20 Cores / 40 Threads
- 64 GB DDR4 RAM
- 960 GB SSD Storage
- Unlimited bandwidth @ 2 Gbps
- 1 dedicated IPv4 address
- Region: Netherlands
EliteCore G-4000 Ada
A balanced professional GPU server for AI development, visualization, inference testing, and compute workflows.
- 1x NVIDIA RTX 4000 SFF Ada
- Xeon Silver 4410T • 10 Cores / 20 Threads
- 128 GB DDR5 RAM
- 1 TB SSD Storage
- Unlimited bandwidth @ 2 Gbps
- 1 dedicated IPv4 address
- 20 GB GDDR6 ECC Memory
EliteCore G-6000 Ada
A higher-performance GPU server for AI, visualization, rendering, simulations, and heavier graphics workloads.
- 1x NVIDIA RTX 6000 Ada
- Xeon Silver 4410T • 10 Cores / 20 Threads
- 128 GB DDR5 RAM
- 1 TB SSD Storage
- Unlimited bandwidth @ 2 Gbps
- 1 dedicated IPv4 address
- 48 GB GDDR6 ECC Memory
EliteCore G-6000 Blackwell
A stronger enterprise GPU dedicated server for next-generation AI and visual computing workloads.
- 1x NVIDIA RTX PRO 6000 Blackwell
- Xeon Silver 4410T • 10 Cores / 20 Threads
- 128 GB DDR5 RAM
- 1 TB SSD Storage
- Unlimited bandwidth @ 2 Gbps
- 1 dedicated IPv4 address
- 96 GB GDDR7 ECC Memory
Advanced RTX 3090 GPU Configurations
Use these options for workloads that need more GPU density, higher concurrency, or a virtualized GPU path with clear resource allocation.
EliteCore V-G3090 Standard
Virtualized RTX 3090 access in a lower-entry GPU configuration.
- 1x GeForce RTX 3090
- 5x vCPU Xeon Silver 4210R
- 16 GB DDR4 RAM
- 480 GB SSD Storage
- 10 TB bandwidth @ 1 Gbps
- 1 dedicated IPv4 address
- Region: Netherlands
EliteCore V-G3090 Dual GPU
Dual-GPU configuration for heavier rendering, training, and parallel compute tasks.
- 2x GeForce RTX 3090
- 5x vCPU Xeon Silver 4210R
- 16 GB DDR4 RAM
- 480 GB SSD Storage
- 10 TB bandwidth @ 1 Gbps
- 1 dedicated IPv4 address
- Region: Netherlands
EliteCore V-G3090 Pro
A more balanced CPU and memory combination for GPU compute environments.
- 1x GeForce RTX 3090
- 10x vCPU Xeon Silver 4210R
- 32 GB DDR4 RAM
- 480 GB SSD Storage
- 10 TB bandwidth @ 1 Gbps
- 1 dedicated IPv4 address
- Region: Netherlands
EliteCore V-G3090 Dual Pro
Higher-end dual-GPU virtualized option for demanding parallel compute and rendering.
- 2x GeForce RTX 3090
- 10x vCPU Xeon Silver 4210R
- 32 GB DDR4 RAM
- 480 GB SSD Storage
- 10 TB bandwidth @ 1 Gbps
- 1 dedicated IPv4 address
- Region: Netherlands
Dedicated Parallel Processing for Advanced Business and Research Workloads
GPU Dedicated Servers are physical servers equipped with powerful graphics processors that can execute thousands of parallel operations. Unlike shared GPU environments, dedicated GPU infrastructure gives your applications exclusive access to the allocated compute, memory, storage, and network resources.
Exceptional Processing Power
GPU acceleration processes large datasets and highly parallel tasks more efficiently than CPU-only infrastructure for compatible applications.
Faster Project Completion
Parallel processing can reduce training, rendering, simulation, encoding, and analytics time, helping teams complete complex projects sooner.
Dedicated Resources
Physical GPU plans provide exclusive access to the configured GPU, CPU, RAM, storage, network, and IP resources without shared-hosting contention.
Scalable GPU Paths
Choose single-GPU, larger-memory professional GPU, Blackwell, or multi-GPU configurations as workload size and concurrency grow.
Enterprise Hardware
NVIDIA GPU configurations are paired with Intel Xeon processors, ECC-capable professional GPU memory, SSD storage, and high-speed network options.
Flexible Customization
Confirm operating system, drivers, CUDA or framework requirements, storage, bandwidth, security, and deployment scope before provisioning.
Secure Infrastructure
Combine isolated hardware with server hardening, security operations, monitoring, access controls, and backup planning for sensitive workloads.
Expert Administration
Add managed server support for setup, monitoring, optimization, updates, troubleshooting, migration, and technical consultation.
Workloads That Benefit From GPU Dedicated Servers
Modern computing requirements extend beyond ordinary website hosting. GPU-powered infrastructure is designed for applications that can use parallel processing, high GPU memory, and accelerated visual or numerical computation.
AI & Machine Learning
Train, fine-tune, and run inference for machine learning and deep learning models.
Scientific Research
Accelerate scientific simulations, numerical models, and research computing.
Video & Media
Support video rendering, encoding, transcoding, animation, and media processing.
Data Analytics
Process large datasets, big-data operations, and GPU-compatible analytics workflows.
High-Performance Computing
Run compute-intensive and parallel workloads that exceed standard CPU-only environments.
CAD & Visualization
Power computer-aided design, 3D visualization, animation, and graphics applications.
Financial Modeling
Support simulations, forecasting, risk analysis, and GPU-compatible financial computations.
Enterprise Applications
Accelerate business applications that support GPU compute or visual processing.
Development & Testing
Build and validate CUDA, AI, rendering, container, and inference pipelines.
Innovation Projects
Process data faster, improve productivity, and explore new GPU-enabled products and services.
Choose how much GPU server management you want — before deployment.
Select the GPU hardware first, then choose the administration depth needed for OS, drivers, monitoring, security, and production support expectations.
Unmanaged
Included in base priceGPU server hardware, network, root/admin access, IP allocation, and hardware/network support. Customer manages OS, drivers, CUDA stack, services, software, security, backups, and troubleshooting.
Managed Server Care
+$49/moBasic recurring server administration, initial service review, OS-level help, common service troubleshooting, basic update guidance, and monthly health-check style support.
Managed Server Care Plus
+$99/moMore active production support with deeper troubleshooting, recurring service review, performance guidance, backup visibility checks, security review, and stronger admin involvement.
Premium Managed
+$149/mo+High-touch and priority support for critical workloads, proactive review, escalation handling, architecture guidance, priority response, and expanded operational ownership.
Which GPU path fits your workload?
GPU buyers usually need clarity before checkout. Match the plan to the application, not just the biggest GPU name.
AI / ML
Choose RTX 6000 Ada or Blackwell when model size, GPU memory, and training speed matter.
Rendering
RTX 3090 and RTX 6000 Ada are strong options for 3D rendering, animation, and visual pipelines.
Analytics / Simulation
Pick based on GPU memory, CPU pairing, concurrency, and dataset size.
Testing / Dev
Start with a smaller GPU tier when experimentation matters more than production throughput.
What Every GPU Dedicated Server Buyer Should Confirm
GPU deployments depend on more than the accelerator model. Before ordering, confirm the complete hardware, software, network, security, and operational scope required by the workload.
GPU server add-ons to set expectations early
Keep the base GPU price clean, then add support, monitoring, security, migration, and extra IPs only when needed.
Managed Server Care
From +$49/moRecurring OS-level support and basic server administration for teams that do not want to manage everything alone.
Advanced Monitoring
From +$29/moUptime, services, disk, load, resource, and alert monitoring for production GPU environments.
Security Operations
From +$49/moRecurring security review, firewall checks, brute-force review, and risk checks after the server is online.
Extra IPv4 Address
+$4/moAdditional IPv4 addresses when justified by application, SSL, nameserver, or client isolation needs.
Infrastructure services GPU buyers review next
GPU servers are often part of a wider infrastructure decision involving storage, monitoring, security, migration, and managed support.
GPU Dedicated Server FAQs
Buyer-focused answers for teams comparing GPU infrastructure, management levels, OS support, and deployment expectations.
Choose GPU infrastructure based on the workload, not just the GPU name.
Tell us about your model size, dataset, rendering pipeline, simulation, operating system, driver or CUDA requirements, GPU memory, storage, network, security, and management expectations. We’ll help you choose a GPU Dedicated Server that accelerates processing, improves productivity, and supports long-term growth.
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