With the rapid development of AI technologies, especially the rise of large language models (such as the GPT series) and generative AI, data centers are facing unprecedented data transmission pressure. As high-speed optical transmission devices, 800G optical modules support transmission rates of 800 gigabits per second (Gbps) and have become a core component in upgrading AI data center networks. Their necessity lies mainly in meeting AI computing demands for high bandwidth, low latency, and high energy efficiency, thereby preventing traditional network bottlenecks from limiting the efficiency of AI training and inference.
Unlike traditional data centers, AI data centers handle massive parallel data processing, real-time GPU cluster synchronization, and large-scale distributed training. For example, in AI back-end networks, data transmission can reach terabytes per second, making 400G modules insufficient and resulting in higher latency and inefficiency.
800G optical modules, leveraging PAM4 modulation and silicon photonics integration, deliver higher bandwidth and lower power consumption (typically <15W). This enables node-to-node synchronization times to be reduced to the microsecond level—critical for accelerating AI model training. Specifically:
Compared with 400G modules, 800G is far more essential in AI scenarios, as AI workloads grow at an exponential—not linear—rate. While 400G modules are suitable for mid-sized data centers, ultra-large AI clusters (such as training Meta’s Llama models) must handle petabyte-level data, where 400G quickly becomes a bottleneck.
800G modules deliver double the bandwidth with only a 10–20% increase in power consumption, offering a much better performance-to-cost ratio. Looking ahead, 800G will also serve as a bridge to 1.6T networks, meeting the demands of emerging technologies such as 6G and quantum computing.
The 800G optical module is a high-speed optical transmission device that supports a data transmission rate of 800 gigabits per second (Gbps), primarily based on technologies such as silicon photonics or EML (Electro-absorption Modulated Laser). It serves as a core component for data center network upgrades, especially in the AI era, where the explosive growth in bandwidth demands for large model training and inference has made the 800G module a key infrastructure for connecting servers, GPU clusters, and switches.
Compared to the previous-generation 400G module, it offers higher transmission speeds, lower latency, and reduced power consumption, making it suitable for short-distance applications (such as intra-data center interconnections) and medium-to-long-distance transmissions.
AI computing scenarios—such as model training, inference, and data processing—place extremely high demands on network bandwidth and low latency. 800G optical modules are mainly applied in the following areas:
Data Center Interconnect (DCI) and GPU Cluster Connectivity:
In AI supercomputing centers, 800G modules are used for interconnections between servers, switches, and GPU nodes, supporting large-scale distributed training. For example, in Microsoft’s Azure Maia AI cluster, 800G modules with Linear Pluggable Optics (LPO) solutions enable ultra-low-latency connections to meet the data synchronization needs of large language models (such as the GPT series). This significantly shortens data transmission time and improves overall computing efficiency.
High-Performance Computing (HPC) and Intelligent Computing Centers:
Used for transmitting massive datasets, such as in scientific research, financial analysis, and weather forecasting. The 800G module ensures stability and high throughput for complex computing tasks, avoiding bottlenecks. In the AI training process, it supports rapid synchronization between nodes, reducing latency-sensitive issues.
Expansion to Emerging Applications:
Such as autonomous driving, metaverse, and edge computing, these scenarios require ultra-low latency networks. The 800G module supports real-time data processing through high bandwidth, driving the transformation from traditional data centers to AI-dedicated centers. Additionally, in operator networks, it is used for front-end and back-end transmissions, supporting the expansion of AI cloud services.
The core technologies of the 800G optical module include single-channel 100Gbps PAM4 modulation and silicon photonics integration. The LPO innovative solution further reduces power consumption and costs by removing the DSP (Digital Signal Processor) to achieve linear drive, particularly suitable for AI short-distance interconnections. In AI computing centers, the typical distance is within tens of kilometers, mainly used for server-switch connections.
In conclusion, 800G optical modules are not just a technological upgrade for AI data centers but a fundamental infrastructure component. They significantly enhance computing efficiency and support the growth of future AI ecosystems. Without their deployment, data centers will face performance bottlenecks and fail to meet the increasing demands of AI applications.
