SK Hynix AI100 CXL 2.0 128GB Memory Expansion Module

The SK Hynix AI100 CXL 2.0 128GB Memory Expansion Module is a high-capacity, standards-compliant memory expansion device built on the CXL (Compute Express Link) 2.0 protocol, delivering host-managed memory pooling and disaggregation over a PCIe 5.0 physical interface. Designed to extend the addressable memory capacity of CXL-enabled servers beyond traditional DIMM slot limitations, the AI100 enables compute nodes to access large memory pools with coherent, low-latency interconnects — a critical requirement in modern AI inference, in-memory analytics, and data-intensive enterprise workloads. The module carries the manufacturer part number HMCT22BFFFA-N4A and is built around SK Hynix DRAM die technology optimized for sustained bandwidth and capacity efficiency.

The AI100 integrates a CXL 2.0 Type 3 device architecture, which supports memory expansion without requiring a processor-side cache agent, making it compatible with platforms such as Intel Sapphire Rapids and future CXL 2.0-capable server CPUs. Operating in the PCIe 5.0 x8 form factor delivered via an E3.S or equivalent carrier, the module exposes 128 GB of DRAM capacity to the host memory controller, participating in the system's physical address space and enabling software-transparent memory tiering. This architecture allows system architects to deploy cost-effective, large-memory configurations without increasing DIMM slot counts or CPU socket count.

Targeted at datacenter operators, AI infrastructure teams, and HPC platform architects across UAE, GCC, EMEA, and APAC regions, the SK Hynix AI100 is engineered for continuous 24/7 operation under enterprise thermal and reliability requirements. Its role in memory tiering stacks — where it sits as a capacity tier beneath local DDR5 DIMMs — makes it directly applicable to large language model (LLM) inference serving, real-time database acceleration, and virtualized environments requiring expansive per-node memory footprints. Omnixon Global supports procurement of the AI100 for enterprise IT and datacenter buyers across these regions.

Ideal for

• Large language model (LLM) inference serving where expanded per-node memory capacity reduces model sharding and inter-node communication overhead
• In-memory database acceleration for platforms such as SAP HANA, Redis, or Oracle In-Memory, where working dataset size exceeds standard DIMM configurations
• AI training and data preprocessing pipelines requiring large memory-resident feature stores or embedding tables on a single compute node
• Virtualized and cloud-native environments needing high-density per-VM memory allocation without scaling physical CPU socket count
• High-performance analytics and real-time business intelligence workloads that benefit from memory-resident columnar data at scale
• CXL memory pooling architectures in composable infrastructure deployments, enabling dynamic memory allocation across disaggregated server nodes

Technical specifications

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