Cisco Nexus 9364E-SG2 Switch

The Cisco Nexus 9364E-SG2 is a purpose-engineered spine-layer switch designed to anchor next-generation AI/ML training and inference fabrics, high-performance computing clusters, and hyperscale data center interconnects. Built on the Cisco Silicon One G200 ASIC, the switch delivers a non-blocking 51.2 Tbps forwarding capacity across 64 ports of native 800GbE, enabling rack-scale GPU clusters and distributed AI workloads to operate without throughput bottlenecks. The Silicon One architecture provides a unified programmable pipeline that supports both Ethernet and advanced telemetry natively, eliminating the need for separate monitoring infrastructure while maintaining wire-rate performance at all packet sizes.

The 9364E-SG2 is engineered with deep, flexible packet buffers that are essential for absorbing the bursty, all-to-all traffic patterns inherent in large-scale transformer model training, collective communication operations such as AllReduce, and lossless RDMA over Converged Ethernet (RoCEv2) workloads. Its high port radix allows network architects to build fat-tree and dragonfly topologies with fewer tiers, reducing hop count, latency, and capital expenditure on intermediate switching layers. The switch integrates fully with Cisco NX-OS and supports EVPN, BGP, OSPF, IS-IS, and segment routing, making it immediately deployable in both greenfield AI fabrics and brownfield enterprise spine-leaf architectures.

As a 2025-Q3 platform, the Nexus 9364E-SG2 addresses the explosive bandwidth demands introduced by 800G GPU-to-GPU connectivity requirements from NVIDIA NVLink-connected SuperPods, AMD Instinct MI300X clusters, and InfiniBand-alternative Ethernet fabrics advocated by the Ultra Ethernet Consortium. The switch supports 800GbE, 400GbE, and 2x400GbE breakout configurations, providing operational flexibility as installed base GPU nodes transition from 400G to 800G host interfaces. Cisco's Nexus Dashboard and Network Insights provide closed-loop analytics and anomaly detection tuned specifically for AI fabric traffic patterns, enabling proactive congestion management and rapid fault isolation at scale.

Ideal for

• Spine layer for large-scale AI/ML GPU training clusters requiring lossless RoCEv2 fabric with deep buffers and sub-microsecond latency
• Hyperscale data center east-west fabric backbone interconnecting thousands of compute nodes across multi-rack GPU SuperPods
• High-performance computing (HPC) environments demanding non-blocking 800G switching for MPI-based scientific workloads
• Ultra Ethernet Consortium-compliant AI networking deployments replacing InfiniBand with high-radix Ethernet spine architecture
• Multi-tenant cloud infrastructure spine switching supporting segment routing and EVPN-VXLAN overlays at 51.2 Tbps aggregate throughput
• Distributed inference serving platforms requiring consistent low-latency connectivity between disaggregated prefill and decode compute nodes

Technical specifications

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