No. Let's speak the hardware reality. The consumer RTX 3090 supports 2-Way NVLink ONLY. It does not have an NVSwitch fabric. This means in an 8x GPU server, the cards pool memory in physical pairs (GPU 0-1, 2-3, etc., creating 48GB blocks). Communication beyond these pairs must travel across the PCIe bus, which is why choosing a server with PCIe Gen 4.0 is critical for multi-GPU training.
It depends strictly on your workload. For 3D Rendering (V-Ray/Octane) or basic inference, the older E5 v4 (PCIe 3.0) servers are highly cost-effective and perform perfectly. However, if you are doing LLM Training using FSDP or DeepSpeed ZeRO-3, PCIe 3.0 will severely bottleneck data transfer between GPUs. For heavy AI training, you MUST select our modern AMD EPYC or Intel Xeon Scalable nodes to unlock true PCIe 4.0 x16 throughput.
Yes. Competitors frequently use "GPU Passthrough" inside shared KVM Virtual Machines (VPS) and market it as a dedicated server. This hypervisor overhead introduces a 10% to 15% latency penalty during deep learning epochs and rendering frames. ServerMO exclusively provisions 100% Bare Metal hardware, ensuring zero noisy neighbors and direct OS-to-Silicon execution.
SECURITY WARNING: Training proprietary corporate data or healthcare models on shared public clouds (AWS/GCP) or P2P networks exposes you to severe data leakage risks. Additionally, leaving APIs like vLLM (Port 8000) open invites ransomware bots. ServerMO Bare Metal ensures 100% Data Sovereignty via Private VPC isolation. Your data never leaves your physical node.
With public clouds, yes—you pay per GB (Egress Tax). With ServerMO, absolutely zero. We provide flat-rate, unmetered 1Gbps to 10Gbps uplinks with built-in Edge DDoS mitigation. Whether you generate 1,000 tokens or transfer a petabyte of video renders, your monthly bill never changes.
