Optical modules —including SFP, QSFP, and CWDM series —serve as the core components enabling this high-speed, high-bandwidth, and long-distance connectivity. Without them, even the most powerful GPU clusters would be bottlenecked by network limitations. High-Speed Data. This is driving a surge in the need for optical modules in data center interconnects. GPUs such as the A100, H100, and upcoming GH100 require high-speed optical interconnects to link thousands of GPU nodes, enabling large-scale AI model training and inference. Why Optical Modules Are Critical. Modern AI training requires unprecedented levels of GPU-to-GPU communication. Training large language models like GPT-4, Claude, or Llama with hundreds of billions of parameters demands that thousands of GPUs work in perfect synchronization, exchanging gradients, activations, and model parameters. While copper cabling still offers cost and reliability advantages for short-distance connections, it faces the dual challenges of speed bottlenecks and cabling complexity in high-bandwidth, long-distance, and high-energy-efficiency scenarios. The actual number of optical modules used primarily. In the market, there are different versions of the ratio of optical transceivers to the number of GPUs, and the figures of various versions are not consistent mainly because the amount of optical modules required under different networking architectures is not the same. The actual number of optical.
