Empower your most demanding computational projects with Cloud Acropolis GPU Services. Whether you are training massive neural networks or deploying agile AI applications, our infrastructure provides the raw power and scalability you need to innovate without the capital expense of hardware.

We offer two distinct tiers tailored to your specific workload requirements:

Maximum Power

Dedicated Bare Metal GPU Servers

Heavy-Duty Workloads

For enterprises requiring ultimate performance and zero resource contention, our Dedicated Bare Metal servers offer a high-density GPU environment.

  • Configuration: Up to 4x NVIDIA V100 or A100 GPUs per physical machine
  • Best For: Large-scale Deep Learning training, complex 3D rendering, scientific simulations, big data analytics
  • Key Advantage: Full control over hardware stack with 100% dedicated resources, ensuring maximum throughput and lowest latency

Email us your needed configuration to [email protected] and we will send you a quote within 48 hours

Request Bare Metal Quote

Why Choose Cloud Acropolis for GPUaaS?

Enterprise-Grade Hardware

Access industry-leading NVIDIA V100 and A100 Tensor Core GPUs for maximum AI/ML performance.

Data Sovereignty

Process your sensitive AI workloads internally on our secure infrastructure within the EU.

Scalability

Start with a single VM and transition to dedicated clusters as your data needs grow.

Local Support

Benefit from Cloud Acropolis's expertise in high-availability hosting and cloud management.

Feature Comparison

Feature Dedicated Bare Metal Server GPU-Accelerated VM
GPU Models NVIDIA V100 / A100 NVIDIA V100 / A100
Max GPUs Up to 4 GPUs Up to 2 GPUs
Environment Physical (Single-tenant) Virtualized (Shared Host)
Performance Maximum; no virtualization overhead High; optimized for agility
Best Use Case Massive training & 3D rendering LLM Inference & Internal AI tools
Control Full hardware/BIOS access OS-level control

Which One is Right for You?

Choose Dedicated Bare Metal if:

  • You are running long-term, high-intensity training sessions where every second of compute time matters
  • You need to utilize the maximum memory bandwidth of 4 interconnected GPUs
  • You require a "quiet neighborhood" with no other users sharing the physical hardware

Choose GPU VMs if:

  • You are deploying Large Language Models (LLMs) for internal company use
  • You need to quickly spin up an environment for testing or short-term AI inference projects
  • You want a cost-effective way to integrate AI acceleration into your existing cloud architecture

Ready to Accelerate Your Innovation?

Contact our team today to find the right GPU configuration for your project.

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