GPU Server
Raw power for AI, ML and Rendering.
AI training, inference, 3D rendering and scientific computing with NVIDIA A100, H100, L40S and RTX 4090. Bare metal or cloud, hourly or monthly billing.
CUDA & cuDNN optimized · NVLink & NVSwitch support · PyTorch / TensorFlow ready
Why GPU Server?
When CPU isn't enough, GPU steps in. Accelerate your workloads exponentially with parallel computing power.
Massive Parallel Processing
Millions of operations simultaneously with thousands of CUDA cores. Deep learning training times drop from hours to minutes.
High Memory Bandwidth
2+ TB/s bandwidth with HBM2e / HBM3 memory. Large model weights and datasets processed seamlessly.
Multi-GPU Scaling
Ultra-low latency between GPUs with NVLink and NVSwitch. Up to 8 GPUs in a single server configuration.
Ready ML Environment
Pre-installed images with PyTorch, TensorFlow, CUDA toolkit, cuDNN. Start training in minutes.
GPU Models
Choose the GPU that fits your workload. Each model is optimized for different use cases.
GPU Server Stock
The configurations below are ready in our data center. Order and go live within hours.
Free setup
GPU Server Use Cases
Industries and workloads that benefit from GPU's parallel computing power.
LLM & Language Models
Training and fine-tuning large language models like GPT, LLaMA, Mistral. Multi-GPU cluster support.
Computer Vision
Object detection, segmentation, OCR. Fast training and inference on millions of images.
3D Rendering & VFX
Cinema-quality rendering with Blender, V-Ray, Arnold. 10-50× CPU acceleration per GPU.
Scientific Computing
Molecular simulation, climate modeling, genome analysis. CUDA-supported scientific software.
Autonomous Vehicles
LIDAR data processing, real-time object detection. Model optimization for edge inference.
Inference API
High throughput inference with low latency. Model serving, batch processing, real-time API.
Technical Infrastructure
Hardware and connectivity standards used in our GPU servers.
GPU Connectivity
PCIe Gen4/Gen5, NVLink 4.0, NVSwitch. Up to 900 GB/s bandwidth between GPUs.
Processors
AMD EPYC 7003/9004 & Intel Xeon Gold. CPU pairing optimized for GPU workloads.
Memory
DDR4/DDR5 ECC Registered. Adequate host memory ratio per GPU to prevent bottlenecks.
Storage
NVMe SSD RAID arrays. High IOPS and throughput for large datasets.
Network
10–100 Gbps Ethernet, optional InfiniBand. Low latency for distributed training.
Cooling
Liquid cooling supported cabinets (H100). Thermal design optimized for 700W+ TDP GPUs.
Frequently Asked Questions
Find answers to common questions about our GPU server service below.
Need a custom GPU configuration?
If you can't find what you're looking for in the stock list, contact us for a configuration tailored to your AI/ML workload.