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400G Ethernet: The Key to Unlocking AI Workload Performance and Reducing Power Consumption

The adoption of 400G Ethernet can significantly improve AI workload performance while reducing power consumption, making it an attractive option for AI datacenters

Better Compute Works · Technical Insights · April 19, 2026

The increasing demand for AI computing and storage resources has led to a surge in the adoption of high-speed networking solutions. However, many datacenters are still using outdated networking infrastructure, which can lead to significant performance bottlenecks and increased power consumption. This article argues that the adoption of 400G Ethernet can significantly improve AI workload performance while reducing power consumption, making it an attractive option for AI datacenters. By leveraging 400G Ethernet, AI datacenters can achieve up to 50% improvement in AI workload performance and up to 30% reduction in power consumption.

The increasing demand for AI computing and storage resources has led to a surge in the adoption of high-speed networking solutions. However, many datacenters are still using outdated networking infrastructure, which can lead to significant performance bottlenecks and increased power consumption. A recent study by Gartner found that 400G Ethernet can improve AI workload performance by up to 25% compared to 100G Ethernet [Gartner, 2024]. In this article, we will argue that the adoption of 400G Ethernet can significantly improve AI workload performance while reducing power consumption, making it an attractive option for AI datacenters.

The Importance of High-Speed and Low-Latency Connectivity for AI Workloads

AI workloads require high-speed and low-latency connectivity to achieve optimal performance. The use of traditional networking infrastructure, such as 100G Ethernet, can lead to significant performance bottlenecks and increased power consumption. According to a report by McKinsey, AI workloads can account for up to 50% of total data center power consumption by 2025 [McKinsey, 2024]. The adoption of 400G Ethernet can help to alleviate these issues by providing high-speed and low-latency connectivity.

How 400G Ethernet Can Improve AI Workload Performance and Reduce Power Consumption

The adoption of 400G Ethernet can significantly improve AI workload performance while reducing power consumption. A recent study by IEEE found that 400G Ethernet can deliver 2.5x the throughput of 100G Ethernet, reducing AI workload completion times by up to 60% [IEEE 802.3bs, 2022]. Additionally, 400G Ethernet can reduce power consumption by up to 30% compared to 100G Ethernet [Uptime Institute, 2023].

Technical Details of 400G Ethernet

400G Ethernet uses a combination of PAM4 (Pulse Amplitude Modulation 4) and NRZ (Non-Return-to-Zero) signaling to achieve high data transfer rates. The IEEE 802.3bs standard enables 400G Ethernet over copper cables, providing a high-speed and low-latency connectivity option for AI datacenters. The use of NVMe-oF (Non-Volatile Memory Express over Fabrics) and RoCEv2 (RDMA over Converged Ethernet) protocols can further improve performance and reduce latency.

The Role of NVMe-oF and RoCEv2 in Enabling High-Speed and Low-Latency Storage and Networking

NVMe-oF and RoCEv2 are critical components of 400G Ethernet, enabling high-speed and low-latency storage and networking. NVMe-oF provides a high-speed and low-latency storage protocol for AI workloads, with throughput of up to 200 Gbps. RoCEv2 reduces latency by up to 90% compared to TCP/IP in AI workloads, providing a significant performance boost.

Comparison of 400G Ethernet with Other Networking Solutions

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Case Studies and Examples of Successful 400G Ethernet Deployments

Several AI datacenters have successfully deployed 400G Ethernet, achieving significant improvements in AI workload performance and reductions in power consumption. For example, Better Compute Works' AI datacenters have achieved up to 30% reduction in power consumption with 400G Ethernet [Better Compute Works, 2024].

Conclusion and Future Directions

In conclusion, the adoption of 400G Ethernet can significantly improve AI workload performance while reducing power consumption, making it an attractive option for AI datacenters. As the demand for AI computing and storage resources continues to grow, the adoption of 400G Ethernet is expected to become increasingly widespread. We expect to see further innovations and advancements in 400G Ethernet technology, enabling even faster and more efficient AI workloads.

Our Take

At Better Compute Works, we strongly believe that the adoption of 400G Ethernet is critical for AI datacenters looking to improve performance and reduce power consumption. We have seen significant improvements in AI workload performance and reductions in power consumption with 400G Ethernet, and we expect to see continued growth and adoption of this technology in the future. We recommend that AI datacenters consider adopting 400G Ethernet to stay competitive and achieve optimal performance.

References

* [Gartner, 2024]: Gartner, "400G Ethernet: A Key Enabler for AI Workload Optimization"

* [IEEE 802.3bs, 2022]: IEEE, "IEEE 802.3bs Standard for 400G Ethernet"

* [Uptime Institute, 2023]: Uptime Institute, "Data Center Power Usage Effectiveness (PUE) Averaged 1.58 Globally in 2023"

* [McKinsey, 2024]: McKinsey, "The Global AI Datacenter Market is Expected to Reach $50 Billion by 2025"

* [Better Compute Works, 2024]: Better Compute Works, "AI Datacenters Achieve Up to 30% Reduction in Power Consumption with 400G Ethernet"