GPU Infrastructure

GPU Dedicated Servers

Bare-metal servers with NVIDIA GPUs dedicated entirely to your workloads. No shared resources, no noisy neighbors. Full root access and NVLink interconnects for serious ML training, inference, and HPC.

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GPU Models Available

141GB

Max GPU Memory

Multi-GPU Configs

24/7

Expert Support

Available GPU Models

Every GPU dedicated server comes with full root access, pre-installed ML frameworks, and enterprise-grade hardware.

NVIDIA H200 SXM

Flagship

70B+ parameter models, multi-modal AI, large-scale training

Memory

141GB HBM3e

Bandwidth

4.8 TB/s

FP16 Perf

989 TFLOPS

On-Demand

$4.50/hr

Reserved Monthly

$2,699/mo

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NVIDIA H100 SXM

LLM training, fine-tuning, distributed deep learning

Memory

80GB HBM3

Bandwidth

3.35 TB/s

FP16 Perf

990 TFLOPS

On-Demand

$3.75/hr

Reserved Monthly

$2,249/mo

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NVIDIA A100 SXM

NVIDIA L40S

Production inference, video AI, model serving at scale

Memory

48GB GDDR6

Bandwidth

864 GB/s

FP16 Perf

733 TFLOPS (FP8)

On-Demand

$2.25/hr

Reserved Monthly

$1,349/mo

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NVIDIA L4

Best Value

7B model inference, prototyping, edge AI development

Memory

24GB GDDR6

Bandwidth

300 GB/s

FP16 Perf

121 TFLOPS

On-Demand

$0.75/hr

Reserved Monthly

$449/mo

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Server Hardware Specifications

Enterprise-grade components paired with your choice of GPU.

CPU

Dual AMD EPYC 9004 / Intel Xeon Scalable

System RAM

Up to 2TB DDR5 ECC

Storage

NVMe SSD arrays, up to 30TB per node

Network

25GbE / 100GbE with RDMA support

GPU Interconnect

NVLink 4.0, NVSwitch (up to 900 GB/s)

Power & Cooling

Liquid-cooled racks, N+1 redundancy

Built for Demanding Workloads

GPU dedicated servers give you the raw power and consistency that shared environments cannot.

ML Model Training

Train foundation models, fine-tune LLMs, and run distributed deep learning jobs across multi-GPU clusters with NVLink interconnects.

AI Inference at Scale

Serve production AI models with consistent low latency. Auto-scaling GPU pools handle traffic spikes without over-provisioning.

Video Rendering & Processing

Real-time video encoding, transcoding, VFX rendering, and post-production workflows on dedicated GPU hardware.

Scientific Computing

Run molecular dynamics, climate simulations, genomics pipelines, and other HPC workloads on CUDA-optimized hardware.

Explore GPU Options

All GPU Cloud Options | Bare Metal Servers

Frequently Asked Questions

What is a GPU dedicated server? +

A GPU dedicated server is a bare-metal server with one or more NVIDIA GPUs allocated exclusively to you. Unlike shared GPU cloud instances, you get the full hardware with no noisy neighbors, consistent performance, and root access to the entire machine.

How do I pick the right GPU for my workload? +

For training large models (70B+ parameters), choose H200 for its 141GB memory. For general training and fine-tuning, H100 or A100 work well. For production inference, L40S offers excellent price-performance. L4 is ideal for smaller models and development work.

Can I configure multi-GPU servers? +

Yes. We offer 1x, 2x, 4x, and 8x GPU configurations. Multi-GPU servers use NVLink interconnects for high-speed GPU-to-GPU communication, critical for distributed training workloads.

What software comes pre-installed? +

Every GPU dedicated server ships with CUDA, cuDNN, PyTorch, TensorFlow, and Docker pre-installed. You get full root access to install anything else you need. We also support custom images.

Is there a minimum commitment? +

On-demand servers are billed hourly with no minimum. Monthly reserved servers require a 1-month minimum and save 15-17% compared to on-demand. Longer commitments of 3+ months unlock additional savings.

What support is included? +

All GPU dedicated servers include 24/7 hardware monitoring, replacement SLA, and access to our infrastructure support team. Managed GPU plans add OS-level support, driver updates, and help with ML environment setup.

Get Your GPU Dedicated Server Today

Talk directly with our GPU team. We will help you pick the right model, configure multi-GPU clusters, and get your environment running within hours.

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