Unleash Sustainable AI Performance with Enterprise-Grade GPU Infrastructure

Transform your AI and machine learning capabilities while reducing your carbon footprint. Our SXM GPU servers deliver maximum computing power with minimal environmental impact.

Power your most demanding workloads with our 8-GPU and 16-GPU NVIDIA servers, designed for enterprise-scale AI and machine learning applications.

Multi-GPU Servers for AI & ML

Cato's GPU servers are a cost-effective solution for organizations requiring extreme computational power to solve complex problems in AI, HPC, and data analytics while reducing infrastructure complexity.
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AI and Deep Learning

Fine-Tuning SLMs: The DGX-2 can train complex neural networks with your private data up to four times faster than traditional architectures.

Real-Time Inference: Suitable for high-speed inference tasks in applications like autonomous vehicles, healthcare diagnostics, and financial modeling.

Natural Language Processing (NLP): Ideal for training large-scale language models for sentiment analysis, machine translation, and conversational AI.

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High-Performance Computing (HPC)

Scientific Simulations: Performs advanced simulations in physics, climate modeling, and molecular dynamics.

Data Analytics: Processes massive datasets for insights in industries like genomics and weather forecasting.

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Virtualization

Multi-Tenant GPU Virtualization: Using NVIDIA KVM, the DGX-2 can securely host multiple virtual machines (VMs), allowing different users or departments to run isolated deep learning or HPC workloads simultaneously.

Private AI Cloud: Enables enterprises to build scalable AI clouds for shared resources across teams.

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Image and Video Processing

Handles object detection, image classification, video segmentation, and real-time analytics for media production or surveillance systems.

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Healthcare and Biomedical Research

Accelerates drug discovery, personalized medicine development, and diagnostic tools by processing large medical datasets efficiently.


g2.large g2.medium g2.xlarge
Processor: 2 x Intel Xeon 8168 2 x Intel Xeon E5-2680v4 2 x Intel Xeon 8174
vCores: 96 56 96
Processor Speed: 2.7GHz 3.3GHz 3.1GHz
On Demand1: $11.1990 $6.6290 $26.9520
Monthly2: $4,905.16 $2,903.50 $11,804.98
SLA: 99.5% 99.5% 99.5%
Memory: 512GB 512GB 1536GB
Network Speed: 100Gbps 25Gbps 100Gbps
Data Transfer3: $0.0025/GiB $0.0025/GiB $0.0025/GiB
Data Transfer Included: 1TiB/month 1TiB/month 1TiB/month
Local Storage: 6x 2TB SATA SSD 1x 1TB SATA SSD 2x 1TB NVMe, 2x 4TB NVMe
Attached Storage: 2x 2TB NVMe
GPU: 8x Nvidia V100 (32GB) 8x Nvidia V100 (16GB) 16x Nvidia V100 (32GB)
GPU Memory: 256GB 128GB 512GB
Cuda Cores: 40,960 40,960 81,920
Tensor Cores: 5,120 5,120 10,240
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Subject to availiability; subject to change;
1prices shown in USD;
2shown with annual prepayment and calculated as a 30 day month;
3for egress/ingress from Pod

Frequently Asked Questions

What types of workloads are best suited for V100 GPUs?
Our V100 servers excel at deep learning, machine learning, high-performance computing, and data analytics workloads. They're particularly effective for training large language models and processing complex datasets.
How quickly can I scale my infrastructure?
Additional GPU servers can be deployed within 4 hours during business hours, with emergency deployment available 24/7 for enterprise customers.
What support is included?
All plans include 24/7 technical support, hardware monitoring, and access to our GPU computing experts. Enterprise plans include dedicated support engineers.
How do you ensure environmental sustainability?
We combine renewable energy sources, advanced cooling systems, and optimal server utilization to maintain a zero-carbon footprint while delivering maximum performance.
What Operating Systems does Cato offer?
Cato's GPU servers may be provisioned with ... operating systems.

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