Dell 128GB DDR5 4800MHz RDIMM Quad Rank

The Dell 128GB DDR5 4800MHz RDIMM Quad Rank (SNPH8PGNC/128G) is a high-capacity registered dual in-line memory module engineered for Dell PowerEdge servers operating on the Intel Xeon Scalable (Sapphire Rapids and successor) platform. Built on the DDR5 architecture, this module operates at a native speed of 4800MHz with a 64-bit wide data bus and ECC (Error-Correcting Code) support, delivering substantially improved bandwidth and per-DIMM capacity over DDR4 predecessors. The quad-rank configuration maximises memory density per slot, enabling server configurations to reach their maximum addressable memory ceilings with fewer populated slots while maintaining full ECC reliability for mission-critical environments.

As a Dell-branded RDIMM, the module incorporates a registered (buffered) command interface that isolates the memory controller from the electrical load of the DRAM chips, a design essential for stabilising signal integrity at high speeds across large multi-DIMM populations. The 1.1V operating voltage aligns with DDR5 specifications, contributing to improved power efficiency per gigabyte relative to DDR4 at equivalent speeds. On-die ECC within the DDR5 DRAM devices provides an additional layer of error correction before data reaches the system's end-to-end ECC logic, enhancing data integrity under sustained high-throughput workloads.

This module is targeted at enterprises deploying compute-intensive and memory-intensive infrastructure, including in-memory databases, large language model inference and training nodes, virtualisation hosts, and high-performance analytics platforms. Its 128GB capacity per DIMM makes it particularly well-suited for maximising usable memory in Dell PowerEdge servers with limited DIMM slots, supporting configurations that reduce inter-node data movement latency in scale-up AI and HPC architectures. Omnixon Global supplies this module to enterprise customers across the UAE, GCC, EMEA, and APAC regions.

Ideal for

• In-memory database servers (SAP HANA, Oracle TimesTen) requiring large contiguous memory pools for real-time transactional and analytical processing
• AI and machine learning inference nodes where large model parameter sets must reside entirely in system memory to minimise latency
• High-density VMware vSphere or Microsoft Hyper-V virtualisation hosts consolidating large numbers of memory-intensive virtual machines per physical server
• High-performance computing clusters running simulation, computational fluid dynamics, or genomics workloads that demand high memory bandwidth and capacity
• Enterprise Kubernetes and container orchestration nodes requiring substantial memory headroom for stateful workloads and large container images
• Big data analytics platforms (Apache Spark, Hadoop in-memory mode) that benefit from reduced spill-to-disk events through expanded RAM capacity

Technical specifications

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