New White Paper

Chip to Chiller

The Thermal Stack's Impact on AI Factory Efficiency

New research examining how thermal design decisions influence AI Factory efficiency, Tokens/Watt performance, and infrastructure economics.

Executive Summary

AI Factories are increasingly constrained by power availability. As energy becomes the limiting factor for AI infrastructure growth, maximizing Tokens/Watt is emerging as one of the most important measures of AI Factory performance.

The output of an AI Factory is Tokens. As a result, AI Factories should be optimized to the system-level metric of Tokens/Watt.

This research introduces the Thermal Stack and demonstrates how thermal infrastructure influences GPU die max junction temperature, compute efficiency, and the overall economics of AI Factories.

The findings show that thermal infrastructure is increasingly becoming a performance system rather than simply support infrastructure.

30%+

AI Factory Tokens/Watt Improvement​

A well-engineered Thermal Stack can improve AI Factory Tokens/Watt efficiency by more than 30%.​

15%

Tokens/Watt Gain Per 10°C Lower Die Temperature​

Cooler GPUs generate more Tokens/Watt.​

35%

More Tokens/Watt due to Package Architecture Improvement​

GPU package design can significantly improve Tokens/Watt efficiency.​

10–25%

Tokens/Watt Improvement due to Coldplate Innovation

Advanced coldplate designs can materially improve AI Factory Tokens/Watt efficiency.​

LiquidJet® Coldplate improves AI Factory Tokens/Watt efficiency by 10-25%

Read the Full White Paper

Explore the complete analysis, engineering tradeoffs, efficiency calculations, and recommendations behind the Thermal Stack framework.

No registration required.