GPU Servers & Clusters Now Available on OpenMetal – Powering Private AI, ML & More

Updated on April 8, 2025 by Sash Ghosh

Launch of Private GPU Servers & Clusters

We’re thrilled to announce the launch of Private GPU servers and GPU clusters on OpenMetal, purpose-built to support not only AI and machine learning workloads—but also a wide range of high-performance computing needs.

Whether you’re building models, running simulations, crunching big data, or working on video rendering, our enterprise-grade NVIDIA A100 and H100 GPUs are now available on fully dedicated, private infrastructure that delivers performance without compromise.

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Why Choose OpenMetal for Your GPU Infrastructure?

Private, Secure & Fully Yours

Unlike shared GPU offerings in the public cloud, OpenMetal gives you dedicated bare metal access to GPUs—meaning your resources are never throttled, shared, or exposed to noisy neighbors. You get full control over performance, data security, and compliance—critical for businesses handling sensitive or proprietary data.

Tailored to Your Workloads

Our infrastructure is fully customizable—from single GPU servers to large-scale clusters—so we can build them to meet your specific needs. GPU-powered use cases go far beyond AI/ML. The servers in our catalog can support:

  • Computational research
  • Financial modeling
  • Media rendering
  • Simulation & scientific workloads
  • Private inference endpoints
  • And much more.

Supported by Experts from Day One

At OpenMetal, you’re never on your own. Our team is with you from day one—consulting with you on the right architecture, supporting your deployment, and helping you optimize for success. We’re not just a provider—we’re your partner in performance.

Interested in GPU Servers and Clusters?

GPU Server Pricing

High-performance GPU hardware with detailed specs and transparent pricing.

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Schedule a Consultation

Let’s discuss your GPU or AI needs and tailor a solution that fits your goals.

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Private AI Labs

$50k in credits to accelerate your AI project in a secure, private environment.

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Explore More OpenMetal GPU and AI Content

With the new OpenMetal Private AI Labs program, you can access private GPU servers and clusters tailored for your AI projects. By joining, you’ll receive up to $50,000 in usage credits to test, build, and scale your AI workloads.

GPU Servers and Clusters are now available on OpenMetal—giving you dedicated access to enterprise-grade NVIDIA A100 and H100 GPUs on fully private, high-performance infrastructure.

Cold start latency becomes a visible and impactful factor in private environments and can slow down AI inference, especially when infrastructure is deployed on-demand to optimize resource usage or reduce costs. Learn causes, impacts, and how to reduce delay for faster, reliable performance.

Intel Advanced Matrix Extensions (AMX) is an instruction set designed to improve AI inference performance on CPUs. It enhances the execution of matrix multiplication operations—a core component of many deep learning workloads—directly on Intel Xeon processors. AMX is part of Intel’s broader move to make CPUs more viable for AI inference by introducing architectural accelerations that can significantly improve throughput without relying on GPUs.

Modern GPU technologies offer multiple methods for sharing hardware resources across workloads. Two widely used approaches are Multi-Instance GPU (MIG) and time-slicing. Both methods aim to improve utilization and reduce costs, but they differ significantly in implementation, performance, and isolation.

When comparing GPU costs between providers, the price of the GPU alone does not reflect the total cost or value of the service. The architecture of the deployment, access levels, support for GPU features, and billing models significantly affect long-term expenses and usability.