The power consumption of AI GPUs has steadily increased in recent years and is expected to continue rising as AI processors incorporate more compute and HBM chiplets. Some of our sources in the industry have indicated that Nvidia is looking at 6,000W to 9,000W for thermal design power for its next-generation GPUs, but experts from KAIST, a leading Korean research institute, believe that the TDP of AI GPUs will increase all the way to 15,360W over the next 10 years. As a result, they will require rather extreme cooling methods, including immersion cooling and even embedded cooling. Until recently, high-performance air-cooling systems, which involved copper radiators and high-pressure fans, were sufficient to cool Nvidia’s H100 AI processors. However, as Nvidia’s Blackwell increased its heat dissipation to 1,200W and then Blackwell Ultra increased its TDP to 1,400W, liquid cooling solutions became almost mandatory. Things are going hotter with Rubin, which will increase its TDP to 1,800W, and with Rubin Ultra, which will double the number of GPU chiplets and HBM modules, along with a TDP that will go all the way to 3,600W. Researchers from KAIST believe that Nvidia and its partners will use direct-to-chip (D2C) liquid cooling with Rubin Ultra, but with Feynman, they will have to use something more powerful.

Full report : A look at embedded and immersion chip-cooling tech; industry sources indicate Nvidia is mulling 6,000W to 9,000W TDP for its next-gen GPUs, up from ~1,200W now.