Arista 7800R4 AI Spine Modular Switch

The Arista 7800R4 AI Spine Modular Switch represents Arista's fourth-generation 7800 series chassis, engineered specifically for the demanding requirements of large-scale AI training and inference back-end networks. Built on a fully non-blocking, orthogonal crossbar switch fabric, the 16-slot chassis accommodates high-density 800G line cards based on the latest Jericho3-AI and Ramon3 silicon, delivering aggregate switching capacity measured in the tens of petabits per second. The architecture is purpose-designed to eliminate congestion in all-to-all communication patterns characteristic of GPU collective operations such as AllReduce, AllGather, and ReduceScatter, which are foundational to distributed deep learning workloads at scale.

At the heart of the 7800R4's differentiation is its massive per-port deep buffer capability, enabling the switch to absorb the synchronized, bursty traffic patterns that emerge when thousands of GPUs simultaneously exchange gradient updates. Unlike shallow-buffer merchant-silicon designs, the deep buffer architecture prevents packet drops that would otherwise trigger TCP retransmissions and degrade GPU utilization. The chassis supports a combination of 800GbE, 400GbE, and 100GbE port densities through mixed line-card configurations, providing investment flexibility as AI cluster infrastructures evolve from current-generation to next-generation GPU nodes.

Running Arista EOS (Extensible Operating System), the 7800R4 integrates seamlessly with Arista CloudVision for network-wide telemetry, automated topology validation, and AI workload visibility. Native support for RDMA over Converged Ethernet (RoCEv2) with advanced ECN, PFC, and congestion-control tuning makes the platform a complete lossless fabric solution. The modular design with redundant supervisor modules, power supplies, and fan trays ensures the five-nines availability required for production AI infrastructure, while the chassis form factor supports incremental capacity expansion without forklift upgrades.

Ideal for

• AI/ML GPU cluster spine layer interconnecting thousands of NVIDIA H100, H200, or GB200 GPU nodes in large-scale distributed training fabrics requiring lossless RoCEv2 transport
• HPC research center back-end network providing non-blocking 800G bandwidth for tightly coupled parallel simulations and scientific computing workloads across petascale compute clusters
• Hyperscale and cloud provider AI-as-a-service infrastructure requiring a spine switch capable of sustaining high-throughput AllReduce collective communications at rack-scale and pod-scale
• Multi-tenant AI infrastructure platforms deploying Rail-Optimized or Fat-Tree topologies where per-port deep buffers are critical to maintaining predictable latency and throughput SLAs
• Financial services AI inference clusters processing real-time risk analytics and large language model inference at ultra-low latency, leveraging the chassis's advanced congestion management and telemetry
• Enterprise AI data center modernization projects migrating from 100G/400G fabrics to 800G spine-and-leaf architectures to support next-generation GPU server deployments

Technical specifications

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