Quietly signalling a major push into next-generation AI infrastructure, Cisco has introduced its Silicon One G300 chip, designed to support massive AI clusters and handle training, inference, and real-time workloads at high speed. The new chip is scheduled to enter the market in late 2026.
The Silicon One G300 delivers a switching capacity of 102.4 Tbps and powers Cisco’s new liquid-cooled Ethernet systems. Cisco said the design offers nearly 70% better energy efficiency, making it suitable for data centres managing heavy AI workloads.
The G300 is built with 512 high-speed 200 Gbps SerDes. These can be combined in an 8×200 Gbps configuration to support port speeds of up to 1.6 Tbps, allowing 64 ports of 1.6 Tbps on a single chip. This setup significantly reduces infrastructure needs. Using the G300, up to 128,000 GPUs can be connected with around 750 switches, compared with about 2,500 switches required earlier.
To maintain performance during heavy traffic, the chip includes advanced networking features such as fast hardware-based load balancing and shared packet buffers. These capabilities help ensure smooth operations even when data flows spike sharply.
Cisco has also focused on reducing power consumption. The G300 supports new 800 Gbps linear pluggable optics that remove the need for onboard DSP and retimers. This approach cuts power usage and reduces switch energy requirements by nearly 30%.
While the chip’s raw speed is comparable to offerings from Broadcom and NVIDIA, Cisco claims the G300 can complete workloads faster. According to the company, improved buffering and hardware-driven traffic management give it an edge in handling demanding AI tasks more efficiently.
The launch highlights Cisco’s strategy to build energy-efficient, high-performance networking hardware tailored for the growing scale of AI-driven data centres.
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