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Home » Semtech Pushes Toward 3.2T With 400G-Per-Channel PMD Work

Semtech Pushes Toward 3.2T With 400G-Per-Channel PMD Work

April 1, 2025
in All, Optical
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Semtech introduced 200G per channel PMD (Physical Medium Dependent) ICs for 1.6T modules and developing 400G per channel solutions for upcoming 3.2T connectivity. These advancements respond to the growing demand for higher speed, lower latency, and improved power efficiency driven by AI, ML, and LLM workloads.

The new 200G FiberEdge™ components include 112GBd PAM4 transimpedance amplifiers (TIAs) and laser drivers, offering a path to energy-efficient 800G and 1.6T optical modules. Designed to meet stringent power and footprint requirements in hyperscale environments, these components support various pitch formats and mounting techniques. Semtech is also preparing 400G per channel solutions aimed at 3.2T module designs, with early samples now in customer hands.

Semtech’s portfolio reflects a broader strategy to enable scalable data center fabrics for AI infrastructure, where exponential model growth demands high-throughput, power-aware connectivity. The company is positioning its 200G and 400G per channel architectures as foundational to future deployments across hyperscale and enterprise AI environments.

• 200G per channel PMD ICs support 1.6T modules, targeting AI and LLM clusters.

• 112GBd PAM4 TIAs include GN1832, GN1834, GN1834D, and GN1836, supporting multiple pitches and 2.5D mounting.

• 112GBd PAM4 laser drivers include GN1873 (EML) and GN1878 (VCSEL).

• 400G per channel technology is in development for 3.2T connectivity.

• Semtech emphasizes speed, power efficiency, and density as core to scaling next-gen data centers.

“Our 200G and 400G per channel innovations represent critical building blocks that enable the next generation of data center fabric,” said Amit Thakar, vice president of signal integrity product marketing at Semtech.

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Jim Carroll

Jim Carroll

Editor and Publisher, Converge! Network Digest, Optical Networks Daily - Covering the full stack of network convergence from Silicon Valley

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