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Lenovo 32GB DDR5-4800/PC5-38400 SDRAM Memory Module

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Product details

Management number 241241985 Release Date 2026/07/17 List Price US$1,816.50 Model Number 241241985
Category
Overview

The Lenovo 4X77A77031 is a 32 GB TruDDR5 memory module designed to enhance the performance of Lenovo ThinkSystem SD650 V3 Neptune DWC servers. Operating at a DDR5-4800 data rate, it provides the high bandwidth needed for demanding workloads such as large in-memory databases, dense virtualization, and high-performance computing. This module supports enterprise environments where reliability and efficiency are critical.

Key features
  • 32 GB TruDDR5 capacity that supports data-intensive applications and large-scale memory demands
  • DDR5-4800 speed to increase memory bandwidth and improve overall system responsiveness
  • Registered ECC design actively detects and corrects memory errors, ensuring data integrity and system stability
  • Low 1.10 V operating voltage reduces power consumption, helping to lower data center energy costs
  • Dual-rank layout and 288-pin DIMM form factor allow easy installation alongside existing memory modules without complex reconfiguration
  • Validated compatibility with Lenovo ThinkSystem SD650 V3 Neptune DWC servers for seamless integration
Key specs
  • Memory capacity: 32 GB
  • Memory type: TruDDR5 SDRAM
  • Speed: DDR5-4800 (PC5-38400)
  • Voltage: 1.10 V
  • Form factor: 288-pin DIMM
  • Rank: Dual-rank
  • Error correction: Registered ECC
  • Compatible with: Lenovo ThinkSystem SD650 V3 Neptune DWC servers
Performance and reliability

This memory module is engineered to maintain high reliability in enterprise server environments. The registered ECC technology continuously monitors and corrects errors, preventing data corruption and minimizing downtime. Its efficient power usage supports servers running 24/7, making it a practical choice for IT administrators focused on both performance and operational costs.

Ideal uses and environments

The Lenovo 4X77A77031 fits well in data centers and enterprise setups that require robust memory performance for virtualization, AI model training, and real-time analytics. It is particularly suited for workloads that demand large memory capacity and fast data access, helping organizations scale their infrastructure without sacrificing stability or efficiency.


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