Optical transceiver power matters in AI data centers because it multiplies. A per-module figure applies to every port in the fabric, then again to the cooling required to remove that heat, and again to the power that could otherwise have gone to GPUs. In a large AI fabric, front-panel optics represent a meaningful share of non-compute power, and the difference between technology choices is large enough to change rack density.

The multiplication effect

A single transceiver drawing a few watts is not interesting. The same module in every port of a 64-port switch, across every switch in a fabric, is a different proposition.

There is a second multiplier behind it. Every watt drawn at the front panel is a watt that has to be removed by the cooling system, and cooling is itself not free. In facilities where power and cooling are the binding constraint on how many GPUs can be installed, network power directly reduces sellable or usable compute capacity.

This is why the copper-versus-optics decision at short reach carries more weight in AI clusters than it ever did in general enterprise networks.

Where the power actually goes

Module power is dominated by two things: the DSP that conditions the electrical signal, and the optical components including the laser and its driver. Reach class drives both, because longer reach needs more launch power and more sophisticated signal conditioning.

That gives a rough ordering. Passive copper draws essentially nothing. Active copper adds a small amount for equalisation. Active electrical cables add slightly more for retiming. Optical modules draw the most, with power rising as reach class increases from SR through DR to FR.

As a reference point on the optical side, ATOP's 800G OSFP 2xFR4 module is specified at 11 W typical for a 2 km single-mode link.

Heat is the second half of the problem

Module power figures are usually quoted at nominal conditions. Real switches in real AI racks run hotter than that, and transceiver power rises with case temperature.

The consequence is a feedback loop. Hotter modules draw more power, which produces more heat, which raises the temperature further. In a poorly cooled rack this can push a module towards thermal throttling or towards degraded optical performance, both of which show up as link instability rather than as an obvious thermal alarm.

Mechanical design is part of the answer. OSFP riding heat sink designs move the thermal interface into the cage, while integrated heat sink variants in closed top and open top forms manage it within the module body. The right choice depends on the switch mechanical design and the airflow available.

Using copper is the largest single saving available

The most effective power reduction in an AI fabric is not a more efficient optical module. It is not using an optical module at all where the link does not require one.

Passive DAC covers the shortest intra-rack links at essentially zero added power. ACC extends to around 5 m and AEC to around 7 to 10 m at 400G and 800G. In a GPU cluster, a substantial proportion of links fall inside those distances, and every one carried on copper rather than optics is a direct saving on both power and cooling.

ATOP builds DAC, ACC and AEC alongside its optical range at 400G and 800G, which means a fabric can be designed link by link rather than standardised on optics for convenience.

LPO and silicon photonics reduce power where optics are required

Where distance requires optics, module architecture is the lever. Linear pluggable optics remove the DSP from the module and rely on the host SerDes to condition the signal, which removes a significant power block. Silicon photonics integrates optical functions onto a silicon substrate, improving efficiency and manufacturability at scale.

ATOP builds an 800G DR8 LPO silicon photonics variant alongside conventional DSP-based designs, so the trade can be evaluated against a directly comparable product.

The trade-off is worth stating plainly. LPO shifts responsibility for signal conditioning to the host, so it demands a well-characterised host SerDes and a tighter link budget. It is an excellent fit for short, controlled links inside a fabric and a poorer fit where the link environment is uncertain.

How to compare power figures honestly

• Compare at the same case temperature, since a figure quoted at 25 C and one quoted at 55 C are not comparable
• Use typical figures for capacity planning and maximum figures for thermal design, not the other way round
• Model at switch level and fabric level, not per module
• Include the cooling multiplier appropriate to the facility
• Count the links that could move to copper before comparing optical modules at all

The measurement that matters

The useful figure is watts per rack of network overhead, and how that number changes when the link map is optimised. In most AI clusters, moving eligible links from optics to copper and selecting appropriate architectures for the remainder produces a larger saving than any single product substitution.

ATOP tracks carbon data at product level and maintains component-level traceability, so the environmental figures behind a deployment can be reported from records rather than estimated.