The latest articles on Forem by INGATE GmbH (@ingate). https://forem.com/ingate https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F3852322%2F70522937-d818-48eb-9504-336fb82f4384.png https://forem.com/ingate en INGATE GmbH Tue, 31 Mar 2026 07:58:50 +0000 https://forem.com/ingate/gpu-server-for-ai-inference-bare-metal-vs-cloud-vgpu-4o3a https://forem.com/ingate/gpu-server-for-ai-inference-bare-metal-vs-cloud-vgpu-4o3a <p>The demand for GPU computing power for AI is growing rapidly. Whether training custom models, fine-tuning foundation models, or running inference in production — dedicated GPU servers have become critical<br> infrastructure.</p> <h2> Bare Metal vs. Cloud vGPU </h2> <p>There are two approaches, each with distinct advantages:</p> <p><strong>Bare Metal GPU Servers</strong> give you exclusive access to physical hardware — no shared resources, no noisy neighbors. Ideal for consistent, high-performance workloads like LLM training and fine-tuning.</p> <p><strong>Cloud vGPU Instances</strong> offer flexible virtual GPU resources with dedicated VRAM — granularly configurable without long-term hardware commitment. Perfect for inference, rendering, and variable workloads.</p> <h2> The Hidden Cost of Hyperscalers </h2> <p>GPU instances at major cloud providers are notoriously expensive. A quick comparison:</p> <ul> <li> <strong>AWS p5.48xlarge (8x H100):</strong> ~€25,000/month on-demand</li> <li> <strong>Dedicated bare metal GPU server:</strong> significantly less with fixed monthly pricing</li> </ul> <p>The difference adds up fast. With dedicated hardware, there are no surprise egress fees, no spot instance interruptions, and no waiting lists.</p> <h2> Why Data Sovereignty Matters for AI </h2> <p>Training AI models often involves sensitive business data. Running these workloads on infrastructure subject to the US Cloud Act creates compliance risks for European companies.</p> <p>An alternative: GPU servers hosted in German data centers, operated by a German company under EU jurisdiction. No extraterritorial access, full GDPR compliance by design.</p> <h2> Available GPU Tiers </h2> <p><strong>Bare Metal (dedicated hardware):</strong></p> <ul> <li>NVIDIA RTX 4000 SFF Ada (20 GB GDDR6) — inference &amp; light ML</li> <li>NVIDIA RTX PRO 6000 Blackwell (96 GB GDDR7) — LLM training, up to 4 GPUs</li> <li>NVIDIA H100 SXM5 (80 GB HBM3) — large-scale training</li> </ul> <p><strong>Cloud vGPU (flexible instances):</strong></p> <ul> <li>Tesla T4 (16 GB) — cost-efficient inference</li> <li>A10 (24 GB) — ML training &amp; rendering</li> <li>A100 (80 GB) — LLM training with MIG support</li> <li>H200 (141 GB HBM3e) — maximum performance</li> </ul> <p>All hosted in ISO 27001 / DIN EN 50600 certified data centers in Munich, powered by 100% renewable hydroelectric energy.</p> <h2> Getting Started </h2> <p>Whether you need a single vGPU for initial experiments or a multi-GPU cluster for production training — the key is choosing infrastructure that matches your workload, budget, and compliance requirements.</p> <p>→ <a href="https://www.ingate.de/bare-metal/gpu-server/" rel="noopener noreferrer">Learn more about GPU Server hosting</a><br> → <a href="https://www.ingate.de/cloud/gpu/" rel="noopener noreferrer">Cloud GPU instances with vGPU</a><br> → <a href="https://www.ingate.de/bare-metal/konfigurator/rtx-pro-6000-bse/" rel="noopener noreferrer">Compare configurations</a></p> ai gpu cloudcomputing infrastructure