Nvidia MCX713104AS-ADAT ConnectX7 4-Port 25/50GbE SFP56 PCIe 4.0 x16 HHHL Adapter Card

Shop Nvidia MCX713104AS-ADAT As enterprise networking continues to evolve, organizations require network adapters capable of delivering exceptional bandwidth, low latency, and reliable performance for demanding workloads. The ConnectX-7 4-Port Network Adapter Card is engineered to support next-generation data center networking, cloud computing, virtualization, and high-performance computing (HPC) environments. With its advanced architecture and four high-speed Ethernet ports, this adapter provides the scalability and efficiency required to handle today's data-intensive applications. Why Choose Featuring four SFP56 Ethernet ports, and supporting 25GbE and 50GbE connectivity, the adapter enables businesses to increase network throughput while optimizing bandwidth utilization across multiple workloads. Designed with a PCI Express Gen4 x16 interface, the provides the bandwidth necessary to support high-speed networking without creating bottlenecks. Built in a Half-Height, Half-Length (HHHL) form factor, the is designed for broad compatibility with modern rack servers and enterprise systems. Future-Proof Your Network Infrastructure For businesses building modern network infrastructure, the ConnectX7 delivers the bandwidth, port density, and acceleration features needed to support cloud, storage, and compute-heavy environments. At Compu Devices, we provide a vast range of high-performance network adapters to help you build a faster, more reliable, and future-ready enterprise network. Order now and transform your network advanced ethernet technology for reliable performance and efficient IT solutions.

Technical Specifications:

Manufacturer: NVIDIA
Part Number: MCX713104AS-ADAT
Product Type: Network Adapter Card
Interface: PCIe 5.0 x16
Ports: 4 x Network Ports
Network Speed: Up to 100GbE per port
Connector Type: QSFP112
Features: RDMA over Converged Ethernet (RoCE), GPUDirect RDMA, SR-IOV, advanced hardware acceleration
Compatibility: Enterprise servers and high-performance computing systems
Use Case: AI clusters, cloud computing, data centers, and HPC environments