What Is an AI Networking Switch?
An AI networking switch is a high-radix Ethernet data center switch, usually 400G or 800G per port, that connects GPU servers in the AI back-end fabric and keeps RDMA traffic lossless with PFC, ECN and adaptive load balancing, because the slowest flow sets how long a training job takes. IP Infusion develops OcNOS-DC, the network operating system that runs these switches, and ships it as complete, validated systems on 51.2 Tbps Broadcom Tomahawk 5 and 25.6 and 12.8 Tbps platforms.
What makes a data center switch an AI switch
A switch earns the AI label when it carries GPU traffic at the speed, scale and loss rate a training cluster needs. Five properties set it apart. The network these switches form is covered in What is an AI fabric; this page is about the switch itself.
- Port speed and capacity. GPU NICs attach at 400G and 800G, and the switch port has to match them. A 51.2 Tbps switch provides 64 ports at 800G; a 25.6 Tbps switch provides 64 ports at 400G.
- Radix. The number of ports per switch sets how many GPUs one leaf can serve and how many leaves one spine can join, which decides how many tiers the fabric needs. Fewer tiers means fewer hops, fewer optics and less power.
- Lossless transport. GPUs exchange data with RDMA over Converged Ethernet (RoCEv2), which slows sharply when packets drop. The switch needs Priority Flow Control (PFC) to pause a queue before it overflows and Explicit Congestion Notification (ECN) to warn senders early, working with DCQCN congestion control on the NIC.
- Even load. Collective operations such as AllReduce produce a few very large flows. Static hashing can put two of them on one link while another link sits idle. Dynamic load balancing moves traffic toward less loaded paths.
- Visibility. Streaming telemetry reports queue depth, PFC pauses and ECN marks as they happen, so operators can find the one link that is slowing a job.
Where AI switches sit in an AI network fabric
An AI data center runs four networks side by side, and each asks something different of its switches. The GPU back-end fabric is what most people mean by an AI switch.
GPU back-end fabric
Connects GPU NICs across servers for training and inference. Built from rail-optimized leaves and a Clos spine at 400G or 800G and run lossless end to end. This is where port speed and radix matter most.
Storage fabric
Feeds training data to the GPU servers and writes checkpoints back. Often RoCEv2 as well, sized for sustained bandwidth rather than GPU count.
Front-end network
Connects the cluster to users, orchestration and the rest of the data center. A conventional leaf-spine, often with EVPN-VXLAN to keep tenants apart in a GPU cloud.
Out-of-band management
A separate 1G network for consoles, server management controllers and switch management, so operators can reach every device when the data planes are busy or down.
Inside the back-end fabric, the same switch model can serve as a rail leaf, a spine or a super-spine. A rail-optimized design connects each GPU NIC in a server to a different leaf, so same-rank GPU traffic stays one hop away. The topology sets the role; AI fabric topologies and rail-optimized network cover those designs.
AI switches are bought by neocloud and GPU cloud providers, large enterprise data centers and MSPs, and service providers adding GPU capacity in their own data centers.
800G or 400G: sizing an AI switch by radix
The port count of the switch decides how far a fabric grows before it needs another tier. In a non-blocking two-tier leaf-spine, each leaf splits its ports evenly between GPUs and spines, and each spine port connects one leaf. A switch with k ports then supports k squared divided by two endpoints in two tiers, and k cubed divided by four in three tiers.
| Switch capacity | Ports at full rate | Two tiers, non-blocking | Three tiers, non-blocking |
|---|---|---|---|
| 51.2 Tbps | 64 at 800G | 2,048 endpoints at 800G | 65,536 endpoints at 800G |
| 25.6 Tbps | 64 at 400G | 2,048 endpoints at 400G | 65,536 endpoints at 400G |
| 12.8 Tbps | 32 at 400G | 512 endpoints at 400G | 8,192 endpoints at 400G |
- These are arithmetic ceilings, not product scale figures. Real designs move them with oversubscription, rails per server, optics reach and rack power.
- 800G at the same radix doubles the bandwidth per GPU without adding a tier. That is why back-end fabrics built around 800G NICs use 51.2 Tbps switches.
- IP Infusion reference designs for rail-optimized and 3-stage Clos fabrics, sized in real port counts, are on AI fabric topologies. The choice between designs is walked through in how to choose an AI networking fabric.
AI data center switches validated for OcNOS-DC
OcNOS-DC is the IP Infusion network operating system for data center and AI fabrics. It runs on open switches built on Broadcom silicon, and every platform below is on the OcNOS Hardware Compatibility List, which covers 40+ validated platforms in all.
| Capacity | Broadcom ASIC | Validated platforms | Typical place in an AI data center |
|---|---|---|---|
| 51.2 Tbps | Tomahawk 5 (BCM78900) | Edgecore AIS800-64D, UfiSpace S9321-64E, UfiSpace S9321-64EO | 800G back-end leaf and spine; the S9321-64EO also carries coherent DCI between sites |
| 25.6 Tbps | Tomahawk 4 (BCM56990) | Edgecore AS9736-64D (DCS520) | 400G back-end fabric, storage or front-end |
| 12.8 Tbps | Tomahawk 3 (BCM56980) | Edgecore AS9716-32D (DCS510) | 400G spine for smaller fabrics and front-end networks |
| 12.8 Tbps | Trident 4 (BCM56880) | Edgecore AS9726-32DB (DCS240), UfiSpace S9300-32D | 400G leaf for front-end and storage; IPoDWDM capable |
What OcNOS-DC brings to the switch
- Lossless RoCEv2: PFC, including PFC over Layer 3 routed underlays, PFC deadlock detection and recovery, ECN with DCQCN tuning, and DCBX and ETS for per-class bandwidth.
- Load balancing: Dynamic Load Balancing (DLB) for flowlet-aware adaptive routing, and Global Load Balancing (GLB) for fabric-wide path optimization in OcNOS 7.1.
- Multi-tenant GPU clouds: EVPN-VXLAN keeps tenants apart on a shared fabric. On Trident 3 X4, X5 and X7 and Trident 4 platforms, ECN and PFC over VXLAN also signal congestion across the overlay.
- Operations: streaming telemetry over gNMI and OpenConfig, plus NETCONF, YANG and zero-touch provisioning.
- Licensing and platform support: DLB, PFC deadlock detection and recovery, and ECN over VXLAN are OcNOS-DC PLUS tier features, and support varies by platform. The OcNOS Feature Matrix lists 700+ features by platform and tier.
- Management network: 1G Trident 3 X2 platforms (Edgecore AS4625-54T, Celestica DS1000 and UfiSpace S6301-56ST, 120 Gbps each) run the out-of-band network on the same NOS.
What open AI switches give you, and what they ask of you
Open switches with a separate network operating system change where the choices sit and where the work sits.
What you gain
- Hardware choice. OcNOS-DC runs on switches from more than one hardware maker, so each plane can be chosen on capacity, optics and lead time.
- One NOS across planes. Back-end, storage, front-end and management networks run one operating system, one CLI and one automation model.
- Standard Ethernet. A RoCEv2 fabric uses the same optics, cabling and tooling as the rest of the data center, and the GPU NIC is chosen separately from the switch.
- A path to new silicon. Moving from 25.6 to 51.2 Tbps changes the switch, not the operating model.
What it asks of you
- Integration. Lossless Ethernet only works when switch buffers, PFC, ECN and the NIC's congestion control are tuned together. Someone has to do that tuning and own it.
- Support model. With hardware and software from different companies, the operator needs one clear owner when a fault crosses the line between them.
- Validation burden. Optics, cables, NIC firmware and NOS releases each change over time, and every combination needs testing before production.
OcNOS Systems address these three points by shipping the switch and OcNOS-DC as one complete, validated system, ready to deploy, with the supported platform and feature combinations published in the Hardware Compatibility List and the Feature Matrix.
Three ways to buy AI data center switches
The switch silicon is often the same across the options. What differs is who picks the software, who integrates the pieces, and who carries the testing.
| Question | Integrated switch and NOS from one maker | Self-integrated open switch | Validated open system |
|---|---|---|---|
| Hardware choice | The maker's own models | Any open switch the buyer selects | Open switches on the OcNOS HCL |
| Network operating system | Tied to the hardware | Chosen and installed by the buyer | OcNOS-DC, validated on that platform |
| Who integrates and tests | The maker | The buyer | IP Infusion validates the platform and NOS combination |
| GPU NIC choice | Varies by maker | Any NIC that supports RoCEv2 | Any NIC that supports RoCEv2 |
| Where the effort sits | Low integration effort, narrower choice | Highest integration effort, widest choice | Integration done up front, choice within the HCL |
| Moving to new silicon | When the maker releases it | When the buyer has validated it | When the platform is added to the HCL |
AI Networking Switches FAQ
What is an AI switch?
What is the best switch for AI?
Do I need 800G switches for AI, or is 400G enough?
What is a GPU fabric switch?
Do AI switches need deep buffers?
Can an AI network fabric use Ethernet instead of InfiniBand?
Which switches does OcNOS support for AI fabrics?
Keep reading on AI fabrics and open networking
What is a network operating system?
The software that turns silicon into a fabric.
What is network disaggregation?
Buying the switch and its software separately.
Choosing switches for a GPU cluster? Start from the GPU count.
Tell us the GPU count, the NIC speed and the oversubscription you can accept. An IP Infusion engineer will size the leaf, spine and super-spine stages on validated switches running OcNOS-DC.
Go deeper. Take it with you.
Two short, technical downloads that go further than this page: the full OcNOS-DC datasheet and the lossless 800G AI fabric architecture.
OcNOS-DC Datasheet
Full OcNOS-DC specification: the EVPN-VXLAN and Ethernet for AI feature set, software SKUs, supported hardware platforms, and the solution ordering guide.
Get the datasheetOcNOS 800G Lossless AI Fabric
Non-blocking RoCEv2 fabric on Broadcom Tomahawk 4/5 spines: SKU tiers, validated platforms, and deployment architecture.
Get the briefOcNOS-DC Datasheet
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OcNOS 800G Lossless AI Fabric
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