NVIDIA ConnectX-8 C8180 vs C8240: Architectural Differentiators and SuperNIC Selection for AI/HPC

As the complexity of AI and HPC computing platforms continues to grow, large-scale deployments across many nodes put more pressure on data center networks. The network infrastructure needs to evolve alongside the computing architecture to ensure efficient GPU interconnects and to reduce data movement overhead as much as possible. NVIDIA's ConnectX-8 SuperNIC is a next-generation smart network interface card (NIC) capable of delivering up to 800 Gbps of throughput, built to help alleviate the growing pains of extreme bandwidth and latency bottlenecks in modern AI clusters.

This article will analyze two ConnectX-8 network card models with the same hardware and software baseline but with different port mapping and speed options. Provides a comprehensive overview of their technical variations and application scenarios to help network architecture teams make decisions that more closely fit their real-world networking needs.

ConnectX-8 Architecture: Purpose-Built for GPU-to-GPU Scale

Given the harsh expectations of hyperscale AI and HPC clusters for extreme bandwidth, long-tail latency, and compute use, NVIDIA ConnectX-8 SuperNIC provides high-speed interconnect capabilities over InfiniBand and Ethernet protocols, up to 800 Gbps per card, creating a common, low-latency communication layer for distributed large-model training and high-density inference.

Both the C8180 and C8240 use a standard PCIe 6.0 x16 interface at the hardware level. This arrangement delivers huge host to NIC bi-directional bandwidth (up to 128GB/s) that allows the 800 G network ports to be fully saturated without any bottleneck on the host side for data transfers. All models in this series share a unified hardware acceleration engine: they fully support hardware-level RDMA and RoCE offloading, zero-copy GPUDirect RDMA, and GPUDirect Storage (GDS), and integrate a programmable congestion control mechanism based on real-time telemetry; in an InfiniBand environment, they can also perform in-network computing directly on network nodes via NVIDIA SHARP technology.

By offloading collective communication operations such as All-Reduce, barrier synchronization, and NVMe-oF storage traffic directly to the network card silicon, ConnectX-8 effectively eliminates the network processing overhead borne by the host CPU and GPU, removes packet jitter, and maximizes the cluster’s actual effective computing power. Whether in the standard PCIe card form factor or the high-density OCP specification, the ConnectX-8 family provides highly deterministic, low-jitter interconnect support for the next-generation AI computing infrastructure.

C8180 vs. C8240: Head-to-Head Comparison

Although the NVIDIA ConnectX-8 SuperNIC family shares the same underlying chip architecture, the series has evolved into a variety of specific hardware configurations to accommodate different server rack spaces and network topologies.

C8180 and C8240 are the two flagship models among these that are most widely deployed in large-scale AI and HPC clusters. The main differences between the two are in the number and speed combinations, and IP design related to the physical ports at the host-side interconnect level. Knowing these in terms of the rack density in the rack and the nature of real traffic helps you prepare for the best possible computing network.

Here is the main specs comparison of the two models as follows:

NVIDIA ConnectX-8 C8180 vs. C8240: Compare Hardware Differences and AI Fabric Selection Guide

ConnectX-8 Architecture: Silicon vs. Network Topology

When it comes to ConnectX-8 C8180 (PN: 900-9x81e-00ex-st0) vs the C8240 (PN: 900-9x81q-00cn-st0), you can largely ignore the base silicon since they are based on the same chip platform. The entire selection process is to ensure that the physical port types and speeds are compatible with the network in your data center. Their interfaces are so physically different that you need separate deployment paths. That's true whether you're talking about AI training clusters, traditional HPC supercomputers, or high-throughput enterprise Ethernet.

Port Configuration and InfiniBand Throughput (XDR vs. NDR)

The most obvious difference is in raw throughput and breakout options. The C8180 features a single OSFP cage to deliver an incredible 800 Gbps XDR InfiniBand connection out of the box. If your large-model training workloads rely heavily on cross-node collective comms, such as All-Reduce where tail latency minimization is critical, this 800G single-pipe ceiling is exactly what you need. It also has fine flexibility: With a breakout cable, you can split this single port to 2x400GbE or 8x100G based on port configuration of your downstream switch.

But C8240 has no such complications. With two QSFP112 ports, the device is out of the box ready to connect to dual 400GbE or NDR/HDR InfiniBand topologies. Even if 400G NDR is the roof for performance on InfiniBand, it is still the most straightforward plug-and-play option for ToR switches needing dual uplinks, and even eliminates the pain of custom breakout cable management.

Physical Specifications: PCB Layout and Thermal Constraints

Outside of the ports, there are physical quirks that make a big difference when you’re working with tight 1U chassis arrangements. Both cards are standard PCIe 6.0 x16 Height Half Length (HHHL) form factor and come with hardware-level Secure Boot, but different cages alter the internal PCB layout. The C8180 is marginally wider (68.50 mm vs. 66.40 mm), yet its single-cage design keeps the high-speed on-board trace extremely short — now just 75 mm (2.95 inches). To accommodate two QSFP112 cages side-by-side, the smaller C8240 expands the internal trace length to 140 mm (5.51 inches).

If you're running managing strict thermal constraints in a high-density server, those physical board differences actually make a difference. They make you rethink how air flows right up to the motherboard. Even your day-to-day front-panel O&M shifts. The C8180 offers a dedicated dual-LED design on its single port, allowing you to easily distinguish between link speeds and error alarms at a quick glance. The C8240, due to front-panel space constraints, uses a single dual-color LED per port to conserve space.

Rack Installation Scenarios: Choosing the Right SuperNIC

In the end, the decision of which SuperNIC to deploy is an easy one. You use the C8180 where your architecture requires a single-rail, ultra-high-bandwidth topology - such as 800G XDR compute fabrics or high-bandwidth RDMA storage - or you want the flexibility to be able to break out a single 800G port downstream. 

On the other hand, you pick the C8240 when you need native dual physical port networking. It is designed for architectures that require high availability, active-backup bonding, or LACP aggregation (or both) across completely independent sets of network planes. In addition, the C8240 integrates seamlessly into your current environment if your data center has a large inventory of QSFP112 optical modules and DAC cables.

Conclusion

The C8180 and C8240 are built on the same ConnectX-8 chip and support the highest levels of throughput and a full range of hardware offload capabilities required by today's AI and HPC clusters. The choice between the two is purely a matter of the network topology requirements: the absolute highest single-link bandwidth (800G XDR InfiniBand) or out-of-the-box dual physical ports for either high-availability dual-homing or native 400GbE Ethernet architectures.

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