Supermicro SuperServer SYS-741GE-TNRT 4-GPU H100 AI Server

The SYS-741GE-TNRT is Supermicro's X13 4U/tower GPU platform, and it solves a specific procurement problem: how to deploy NVIDIA H100-class compute without committing to a sealed eight-GPU HGX appliance and its capital outlay. This is a PCIe GPU server, which means you choose the GPUs, the count, and the deployment format, and you expand on your own schedule. GPU configuration and what fits. The chassis supports up to four double-width, full-length GPUs across four PCIe 5.0 x16 double-width slots, plus three additional PCIe 5.0 x16 single-width slots for networking, storage controllers, or single-slot accelerators. The validated NVIDIA GPU list includes the H100 PCIe, H100 NVL (94GB), A100, A30, L4, L40, L40S, and the RTX PRO 6000 Blackwell Max-Q Workstation Edition, along with the RTX Ada and Ampere professional cards. AMD Instinct MI210 is also validated. This breadth matters because it lets one platform serve training (H100, H100 NVL), inference (L40S, L4), and visualization (RTX PRO 6000, RTX 6000 Ada) workloads depending on which cards you install. How it differs from an HGX H100 system, and why that matters to your budget. A true HGX H100 platform uses SXM5 GPUs soldered to an NVSwitch baseboard that links eight GPUs at 900 GB/s each. It is the right tool for frontier-scale distributed training where inter-GPU bandwidth is the bottleneck, and it carries a price and infrastructure footprint to match. The 741GE-TNRT uses PCIe GPUs that communicate over PCIe 5.0, with optional NVLink bridges on supported pairs. For inference, fine-tuning, multi-tenant serving, rendering, and the large majority of enterprise AI work that does not require eight-way NVSwitch fabric, the PCIe platform delivers the same H100 compute per card at a fraction of the platform cost and complexity. You buy the GPUs you need now and add more as utilization justifies it. Compute and memory. Dual Socket E (LGA-4677) accepts 4th Gen and 5th Gen Intel Xeon Scalable processors, up to 64 cores and 128 threads per socket with up to 320MB cache per CPU. Sixteen DDR5 DIMM slots reach 4TB of ECC memory at 4800 MT/s (4th Gen) or 5600 MT/s (5th Gen). For AI workloads this CPU and memory headroom matters more than it appears: data loading, preprocessing, augmentation, and feeding four hungry GPUs without bottlenecking requires real host-side throughput, and a thin CPU pairing starves expensive accelerators. Storage and I/O. Eight hot-swap 3.5"/2.5" drive bays support NVMe, SATA, and SAS, configurable for up to eight NVMe drives for high-throughput dataset storage. Two dedicated M.2 NVMe slots handle the boot drive separately, so OS I/O never contends with training data. Onboard networking is dual 10GbE via the Intel X550-AT2 controller, with the single-width PCIe slots available for 25/100GbE or InfiniBand adapters when you need to cluster multiple nodes. Deployment, power, and management. The chassis converts between full-tower and 4U rackmount, so a research team can run it deskside and later move it into a colocation rack without buying new hardware. Redundant power supplies carry 80 PLUS Titanium efficiency (2000W to 2700W depending on configuration), the highest efficiency tier, which lowers the power overhead on a machine that may draw heavily under four-GPU load. Four removable heavy-duty fans with optimal speed control handle thermals. Management and security include IPMI 2.0 with KVM-over-LAN for remote administration, TPM 2.0, and Secure Boot. The platform is certified for Red Hat Enterprise Linux, Oracle Linux, Windows Server 2022, and Citrix Hypervisor. Where it fits in MillionMiner's catalog. For teams that want maximum GPU flexibility in a single deskside or 4U box, the 741GE-TNRT is the workhorse. For fixed eight-GPU SXM training at scale, the HGX H100 and DGX-class systems are the step up. For the absolute frontier, the DGX GB200 Blackwell platform leads. MillionMiner specifies the right configuration against your actual workload rather than selling you more platform than you need. Because GPU count, NVLink topology, storage, and networking all change the build, every order is configured and quoted individually, then tested and delivered worldwide DDP with customs handled.