$/kWh
Buy pre-built GPU servers and AI workstations at MillionMiner, assembled to spec, load-tested and shipped ready to run. Available builds run from single-GPU RTX 5090 workstations through dual-GPU Threadripper PRO systems with 128 PCIe 5.0 lanes to quad and 8-GPU nodes, with an 8-GPU RTX 5090 node delivering around 838 TFLOPS of FP32.
Every server ships new with warranty and free worldwide DDP, so the checkout price is the final landed cost, with stability validated before it leaves us. Buy to run yourself, or deploy it into our US hosting with remote management. Shop GPU servers and AI workstations below.
Factory-Grade Systems
Configured, tested & burn-in verified
Freight Logistics
Insured pallet & air freight worldwide
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Expert Support
AI infrastructure architects on hand
An AI server is not simply a PC with a GPU added. Serious AI infrastructure requires purpose-built platforms: high-bandwidth NVSwitch fabrics for GPU-to-GPU communication, high-capacity DDR5 memory, enterprise-grade CPUs with sufficient PCIe lanes to feed every GPU, NVMe storage for fast checkpoint I/O, and power delivery systems rated for 10+ kW per rack unit. We supply complete AI server platforms — from 2-GPU tower systems for research labs to NVIDIA HGX H100/H200 8-GPU nodes and the new GB200 NVL72 rack-scale architecture — ready for immediate deployment.
DGX H100 GPU Count
8 × H100 SXM5
640 GB total HBM2e via NVSwitch
NVL72 GPU Count
72 GPUs
GB200 in a single rack — 1 logical unit
DGX H100 AI Perf.
32 PFLOPS
FP8 sparse — combined 8 × H100
HGX H200 Memory
1.1 TB HBM3e
8 × H200 SXM5 — 38.4 TB/s aggregate BW
8 × H100 SXM5, 640 GB
Complete AI supercomputer in a box. NVSwitch full-mesh at 900 GB/s per GPU. Dual Xeon or AMD Epyc, 2 TB DDR5. Reference platform for enterprise AI.
8 × H200 SXM5, 1.1 TB
Successor to DGX H100. 4.8 TB/s HBM3e per GPU. Preferred for large model inference at scale where memory capacity is critical.
OEM platform (8-GPU)
The GPU board + NVSwitch complex shipped to OEM partners (Supermicro, Dell, HPE, Lenovo). Enables identical GPU fabric in custom server chassis.
72 × GB200 GPUs
Single rack-scale system. 36 Grace CPU + 72 Blackwell GPU modules. 1.44 ExaFLOPS FP4. NVLink 5 fabric — entire rack operates as one GPU.
Up to 4 × 96 GB
Workstation-class server for research labs and AI startups. Dual-socket Xeon W9 or Threadripper Pro, 4 × RTX PRO 6000 BW via NVLink Bridge pairs.
2 × 80 GB HBM2e
Cost-efficient inference nodes. Standard 2U chassis, dual PCIe 5.0 slots. Fits standard rack colocation with no liquid cooling required.
4–8 × 24 GB PCIe
High-density, low-power inference. Single-slot L4 GPUs at 72 W each. Up to 8 GPUs in 1U at under 600 W total — ideal for co-lo edge PoPs.
The fundamental distinction between a general-purpose server and an AI server is the GPU fabric. In a standard server, GPUs communicate via PCIe — a bus architecture rated at roughly 32–64 GB/s bidirectional per slot. In an NVSwitch-based AI server, every GPU in the system connects to every other GPU simultaneously through the NVSwitch ASIC at 900 GB/s per GPU (H100) or 1.8 TB/s per GPU (H200 / Blackwell). This is not a bottleneck improvement — it is a qualitative change that enables model parallelism across GPUs as if they were a single larger device.
The CPU and memory subsystem must match GPU bandwidth demands. The DGX H100 pairs its 8-GPU NVSwitch fabric with dual Intel Xeon Platinum CPUs and 2 TB of DDR5 ECC RAM — enough system memory to stage training datasets, run preprocessing pipelines, and manage checkpoint I/O without becoming the bottleneck. PCIe 5.0 lanes are carefully distributed so that every GPU has a direct x16 connection to the CPU fabric.
Power delivery is an engineering challenge in its own right. A fully loaded DGX H100 draws approximately 10.2 kW — requiring 2 × 30A, 240V circuits in North America or 3-phase 32A in Europe. Cooling is equally demanding: NVIDIA's reference design uses a rear-door heat exchanger or direct liquid cooling for the GPU module in DGX configurations. Planning your facility's power and cooling before ordering is not optional — it is the first step.
The GB200 NVL72 is NVIDIA's most ambitious system architecture to date. A single rack houses 36 Grace CPU modules and 72 Blackwell GB200 GPU dies, all connected over a fifth-generation NVLink fabric at 1.8 TB/s per GPU — enabling the entire rack to behave as a single logical accelerator. The aggregate FP4 sparse compute across all 72 GPUs exceeds 1.44 ExaFLOPS and total HBM3e memory reaches 13.5 TB.
Each GB200 module pairs a Grace Arm CPU with two Blackwell GPU dies via NVLink-C2C at 900 GB/s — eliminating the PCIe interface between CPU and GPU entirely. The CPU serves as a high-bandwidth memory controller and orchestration engine, not a bottleneck. This design makes the NVL72 uniquely capable for trillion-parameter model inference at low latency: the entire model fits within the rack's memory, all-reduce operations happen inside NVLink fabric, and no inter-node network is required for single-model serving.
From a facility standpoint, the NVL72 draws up to 120 kW and requires direct liquid cooling — a dedicated 3-phase power feed and facility liquid cooling infrastructure are mandatory. The economics are compelling at hyperscale: one NVL72 rack replaces what previously required entire rows of DGX H100 nodes for equivalent inference throughput.
From lab-scale experimentation to full hyperscale deployment — match your workload to the right platform tier.
Model fine-tuning, RAG development, local inference, research reproducibility. Fits under a desk or in a standard rack. No facility upgrades typically required.
Full fine-tuning of 13–70B models. Production inference for AI-native products. Needs 3-phase power or dual 30A feed. Air cooling viable with rear-door HX.
Full-parameter training of 70–400B models. Low-latency inference for very large models. Liquid cooling recommended. The current industry standard for serious AI workloads.
Trillion-parameter model pre-training and large-batch inference. Full liquid cooling and dedicated 3-phase power mandatory. Rack-as-a-single-GPU architecture via NVLink 5.
Browse our full range of AI server platforms above, from research-grade 2-GPU nodes to DGX H200 and GB200 NVL72 rack-scale systems. Our team will help you plan power, cooling, networking, and logistics end-to-end.
