As AI clusters grow in computational power, heat management becomes critical. Traditional air cooling can’t handle modern AI hardware’s extreme heat loads, making liquid cooling essential. Choosing between immersion and cold plate cooling depends on your cluster’s needs, budget, and goals.
This guide breaks down their key differences, performance, and use cases to help you select the right solution for your AI infrastructure.
What Are Immersion and Cold Plate Liquid Cooling?
Both use liquid for heat transfer but differ in their approach to heat removal.
Cold Plate Liquid Cooling: Targeted, Indirect
Cold plate cooling cools high-heat components (CPUs, GPUs) with metal plates attached directly to hardware. Coolant flows through sealed channels, absorbing heat and circulating to a heat exchanger. Coolant never touches electronics, and other server parts use air cooling.
Immersion Liquid Cooling: Full-System, Direct
Immersion cooling submerges entire servers in non-conductive coolant, which directly contacts all components to absorb heat uniformly. Heated coolant is pumped to a heat exchanger, and no fans or AC are needed.
Immersion vs. Cold Plate: Key Performance Comparison
Critical performance metrics for AI clusters include heat dissipation, energy efficiency, and temperature uniformity. Here’s how the two solutions compare:
