Dell PowerEdge R7625 AMD EPYC 2U Rack Server

The Dell PowerEdge R7625 is a 2U rack server built around the dual AMD EPYC 9004 series processor architecture, delivering exceptional core density, memory bandwidth, and I/O throughput in a space-efficient form factor. Supporting two AMD EPYC 9004 (Genoa) processors with up to 96 cores each, the R7625 provides up to 192 total cores per system, making it one of the most compute-dense 2U platforms available for enterprise data center deployment. The platform leverages AMD's Zen 4 microarchitecture and PCIe 5.0 connectivity, enabling high-speed data movement between processors, memory, storage, and accelerators.

The R7625 supports up to 24 DDR5 DIMM slots delivering substantial memory capacity and bandwidth to feed compute-intensive workloads. With support for multiple PCIe 5.0 expansion slots and a flexible storage backplane accommodating NVMe, SAS, and SATA drives, the system adapts readily to diverse infrastructure requirements. Dell's integrated iDRAC9 with Lifecycle Controller provides comprehensive out-of-band management, automated deployment, and telemetry capabilities aligned with modern IT operations practices.

Designed for virtualization consolidation, database hosting, in-memory analytics, and high-performance computing, the PowerEdge R7625 suits enterprise environments requiring maximum core count and memory throughput within a standard 2U footprint. Its balanced architecture addresses the demands of large-scale virtual machine estates, OLTP and OLAP database engines, AI/ML inference workloads, and cloud-native containerized applications where CPU parallelism and memory bandwidth are primary performance constraints.

Ideal for

• Large-scale VMware vSphere or Red Hat OpenShift virtualization consolidation requiring high vCPU density per rack unit
• Oracle, SAP HANA, and Microsoft SQL Server database hosting benefiting from high core counts and DDR5 memory bandwidth
• AI and machine learning inference pipelines leveraging PCIe 5.0 GPU or accelerator attachment alongside high core parallelism
• High-performance computing (HPC) workloads such as computational fluid dynamics, financial modeling, and genomics analysis
• Cloud-native Kubernetes cluster nodes where per-node CPU and memory capacity directly affects pod scheduling density
• Enterprise data analytics and in-memory caching platforms requiring sustained memory throughput across large working data sets

Technical specifications

Available from Omnixon Global. Submit an RFQ and our team will confirm configuration and availability for your order.