NVIDIA DSX Platform Targets Near-Zero Cooling Water Use Across European AI Factories

NVIDIA announced on October 21, 2026 that European ecosystem partners are adopting its DSX AI Factory Platform to build AI factories that minimize cooling water consumption and use less power for the same AI output. The company said the platform's closed-loop cooling can save 54 million liters of water a day at 2-gigawatt scale, and DSX MaxLPS can reduce power use by up to 30% for the same AI output.

How NVIDIA DSX Cools AI Factories

NVIDIA DSX is a full-stack AI factory reference architecture in which compute, networking, storage, software, power and cooling are codesigned as one system. Conventional cooling towers remove heat by evaporating water, requiring a continual supply of replacement water. DSX reference designs connect liquid-cooled computing with dry-cooler-based heat rejection that avoids evaporation: cooling liquid absorbs heat from computing equipment and circulates in a closed loop, while outdoor dry coolers release that heat into the air without evaporating water.

NVIDIA Vera Rubin infrastructure supports 100% liquid cooling with coolant temperatures of up to 45 degrees Celsius. With dry-cooler-based designs, this architecture can reduce facility cooling water consumption to near zero. At 2-gigawatt scale, NVIDIA DSX can save 54 million liters of water a day compared with conventional cooling-tower-based systems, equivalent to the daily water use of 180,000 households. Local climate determines whether supplemental mechanical cooling is needed during the hottest periods.

"Europe's technology leadership depends on how efficiently we turn power and infrastructure into intelligence," said Warren Barkley, vice president of DSX product management at NVIDIA. "NVIDIA DSX brings together the technologies and ecosystem expertise operators need to build responsibly, operate efficiently at scale and bring intelligence to the market faster."

IREN Among Operators Exploring DSX MaxLPS

CoreWeave, Firmus, Google Cloud, IREN, Lambda, Nebius, Nscale and Sharon AI are exploring DSX MaxLPS, which dynamically allocates power within an AI factory's provisioned budget. In a proof of concept across NVIDIA HGX B200 systems with DSX MaxLPS, Lambda demonstrated 24% more cluster token throughput and 19% more GPU capacity within a fixed power budget. IREN, an AI cloud computing firm, agreed its first soccer sponsorship deal with Real Madrid on October 19, 2026, becoming a global sponsor and official AI cloud partner, according to Sportcal.

NVIDIA's Scale Behind the DSX Rollout

According to akta.pro company records, NVIDIA reported Q1 fiscal 2027 revenue of $81.6 billion, up 85% year over year, with data center revenue of $75.2 billion, up 92% year over year. The same records list Q2 fiscal 2027 guidance of about $91.7 billion and a June 2026 funding round of $25 billion in high-grade bonds. NVIDIA was founded in 1993 and is headquartered in Santa Clara.

Earlier DSX and Partner Moves

On October 21, 2026, NVIDIA introduced DSX POD, a reference design for modular containerized Vera Rubin AI factories that reduces deployment time from six months to as little as 14 days, GlobeNewswire reported. Cisco and NVIDIA announced the Ultra-Dense Small Form Factor Pluggable module for AI factories, supporting 400Gb/s per lane and achieving 12.8Tb/s capacity, Prtimes reported. Iore began accepting orders for NVIDIA HGX B300 servers with Blackwell Ultra GPUs, partnering with Digital Dynamic for data center deployment, with 96 units planned for operation by 2026, Prtimes reported.

DSX OS Components in Developer Preview

NVIDIA is expanding its modular, open source DSX OS portfolio with three components in developer preview: NVIDIA Config Manager, NVIDIA Rack Management Service and NVIDIA Cluster Readiness Engine. Cloud partners including Aleria, Cassava, CoreWeave, Crusoe, Firmus, Firebird, G42, GMI Cloud, IREN, Lambda, Nebius, Nscale, Radiant, Sharon AI and Volta are exploring the latest components to automate infrastructure lifecycle management and improve resiliency and reliability.