Typical configuration
Supermicro 4Γ GPU AI Node
- chassis
- Supermicro AS-4125GS-TNRT
- cpu
- AMD EPYC 9554
- gpu
- 4Γ NVIDIA H100 (PCIe)
- ram
- 512GB DDR5 ECC
- storage
- 4Γ NVMe U.3 (3.84TB)
- network
- 2Γ 100GbE
Enterprise rack servers
High-performance rack servers from Supermicro β GPU-ready, storage-dense, built to spec.
Supermicro's server portfolio spans GPU-dense AI systems, high-IOPS NVMe storage nodes, and general-purpose AMD EPYC compute β all configurable online with compatibility-validated components.

Experts in configuring Supermicro Servers

Supports Up to 8Γ datacenter GPUs (PCIe or SXM) for AI training & fine-tuning, Inference & model serving to keep GPUs fed and raise throughput.
Validated Up to 8Γ datacenter GPUs (PCIe or SXM) against power and thermal envelopes for sustained utilisation.
Optimised NVMe U.2 / U.3 storage for AI training & fine-tuning, Inference & model serving to cut staging latency and keep accelerators compute-bound.
Aligns DDR5 ECC memory with batch throughput to avoid CPU bottlenecks during AI training & fine-tuning, Inference & model serving.
Engineered Redundant platinum-rated PSUs to hold thermal and electrical margins under sustained load.
GPU-dense Supermicro systems sustain high utilisation during multi-GPU training with validated power and cooling headroom.
Low-latency inference at scale with 4β8 GPU configurations and high-bandwidth NVMe model storage.
NVMe-dense Supermicro nodes deliver consistent IOPS for databases, analytics pipelines, and object storage.
High core-count AMD EPYC systems with broad memory bandwidth for parallel and simulation workloads.
Our team will spec the right platform for your workload, validate compatibility, and turn it around fast.
PCIe bandwidth & expansion
Supports Up to 8Γ datacenter GPUs (PCIe or SXM) lanes and slot topology to minimise interconnect stalls and raise throughput.
GPU support & density
Provides Up to 8Γ datacenter GPUs (PCIe or SXM) expansion with sufficient power and thermal headroom for sustained utilisation.
Storage architecture (NVMe)
Uses NVMe U.2 / U.3 storage to reduce staging latency and improve checkpoint write bandwidth.
Cooling & power considerations
Engineered Redundant platinum-rated PSUs for stable thermal and electrical margins under sustained load.
Representative configurations β every build is tailored to your workload and environment.
Typical configuration
Typical configuration
4β and 8βGPU systems (AS-4125GS-TNRT, AS-8125GS-TNHR) for AI training and HPC.
High-density NVMe nodes (AS-1115SV-WTNRT) for databases and data-intensive workloads.
General-purpose AMD EPYC platforms (AS-2025HS-TNR) for virtualization and enterprise compute.
Purpose-built 8-GPU HGX nodes (AS-8125GS-TNHR) for LLM training with H100 / H200.
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UK Headquarters
Built, tested, and shipped from the UK
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