Huawei Network Equipment Cloudengine Xh9230 128dq Lc 51 2t Huawei Switch 400ge Liquid

Product Overview

The CloudEngine XH9230-128DQ-LC delivers 128×400GE QSFP112 ports, 51.2 Tbps switching capacity, 100% liquid‑cooled main chip and optical modules, NPLB/NSLB load balancing, and AI Fabric 2.0 compatibility – doubling rack utilization for AI training clusters and intelligent computing centers.

Key Differentiators (Bulleted for Buyer Focus)

• Ultra‑High Density 400GE – 128×400GE QSFP112 ports in 4U – industry‑leading port count for spine‑leaf fabrics in large‑scale AI clusters.

• Full Liquid Cooling – Main chip + optical modules 100% liquid‑cooled; liquid cooling ratio ≥65% – reduces cooling power consumption by 50% compared to air‑cooled alternatives.

• Patented Thermal Conductive Medium – Huawei proprietary coolant ensures long‑term reliability and maintenance‑free operation in dense deployments.

• Double Rack Utilization – One rack accommodates 8 servers (industry standard is 4 servers per rack) – doubles compute density for AI training farms.

• NPLB/NSLB Load Balancing – Network‑level and path‑level load balancing algorithms eliminate congestion, ensuring optimal GPU‑to‑GPU communication for distributed training.

• AI Fabric 2.0 Compatible – Native integration with Galaxy AI Fabric 2.0 for zero‑touch provisioning, intelligent path selection, and real‑time telemetry.

• VXLAN Ready – Full VXLAN BGP EVPN support for network virtualization and multi‑tenant isolation in large‑scale data centers.

• Massive Forwarding Capacity – 51.2 Tbps switching, 19,000 Mpps forwarding rate – handles 128 ports of full‑rate 400GE traffic non‑blocking.

• Redundant Power – 2000W AC/240V DC hot‑swappable redundant power supplies for carrier‑grade reliability.

• 4U Compact Design – High port density per rack U, reducing spine switch count and inter‑rack cabling complexity.

Technical Specifications

Typical Deployments – Large‑scale AI training cluster spine/leaf fabric with 400GE GPU‑to‑GPU connectivity, intelligent computing center core layer, hyperscale data center spine‑leaf architectures, AI networking for thousands to tens of thousands of servers.