NVIDIA Vera Rubin and the 100% Liquid-Cooled AI Data Center

Introduction: AI Infrastructure Is Entering the Full Liquid-Cooling Era

The rapid growth of generative AI, agentic AI, large-scale model training, and high-performance inference is pushing data center power density beyond the limits of conventional air cooling.

NVIDIA’s Vera Rubin platform represents a major shift in this transition. NVIDIA has confirmed that the Rubin generation is designed around a 100% liquid-cooled infrastructure model, where chips, networking components, and supporting systems are cooled through a closed-loop liquid-cooling architecture rather than relying on server fans or traditional air-conditioning systems.

According to NVIDIA, the Vera Rubin platform can operate with coolant temperatures up to 45°C (113°F). This high-temperature liquid-cooling approach enables more efficient AI factory design, reduces dependence on mechanical chillers, and creates new opportunities for heat reuse and natural cooling.

NVIDIA announced in May 2026 that Vera Rubin is ramping into full production, with production shipments expected to begin in the second half of 2026. The platform is supported by a global supply chain spanning more than 350 factories across over 30 countries.

For AI data center developers, server manufacturers, and liquid-cooling solution providers, this transition means that liquid cooling is no longer an optional upgrade. It is becoming a core infrastructure requirement.

1. From Hybrid Cooling to 100% Liquid Cooling

Earlier generations of AI servers often used hybrid cooling architectures. GPUs were cooled with cold plates, while CPUs, NVLink switches, network devices, optical modules, power systems, and other components continued to rely on air cooling.

This architecture still required high-speed fans, hot and cold aisle containment, air-handling systems, and regular maintenance of filters and fan modules.

The Vera Rubin generation changes this model. NVIDIA describes Rubin as the first AI infrastructure platform designed for 100% liquid cooling, with every chip and networking component cooled through a closed liquid loop and no fans inside the system.

This is a significant architectural shift because it removes air as the primary heat-transfer medium inside the rack.

The move toward full liquid cooling allows AI racks to operate at significantly higher power density while reducing noise, fan energy consumption, and mechanical maintenance requirements.

2. Why 45°C Warm-Water Cooling Matters

One of the most important features of the Vera Rubin cooling architecture is its ability to operate with coolant temperatures up to 45°C.

Traditional liquid-cooling systems often require supply water temperatures between 30°C and 35°C. These lower temperatures can require mechanical chillers, which consume significant energy and increase operating costs.

A 45°C warm-water cooling system changes the energy model of the AI data center.

At higher supply temperatures, data centers can use outdoor dry coolers, closed-loop heat exchangers, and ambient air more effectively. In suitable climates, mechanical chillers can be reduced, bypassed, or used only during peak environmental conditions.

This approach delivers several important benefits:

Lower cooling energy consumption

Reduced dependence on chilled-water systems

More operating hours using natural cooling

Lower water consumption compared with evaporative cooling towers

Higher return-water temperature for heat recovery applications

Improved Power Usage Effectiveness (PUE) potential

NVIDIA notes that Rubin systems can run cooling liquid at temperatures hotter than a typical hot tub. This is possible because liquid transfers heat much more efficiently than air and can remove heat directly from high-power chips and networking components.

3. Vera Rubin Liquid-Cooling Architecture: Four Critical Layers

Chip and Tray Level: Integrated Cold Plates

At the server and tray level, the cooling system must remove heat from GPUs, CPUs, memory, switches, and other high-power components.

As chip thermal design power continues to increase, traditional single-chip cold plates are evolving into larger, integrated cooling assemblies.

Future Rubin-compatible cold plate systems are expected to feature:

Multi-chip cold plate integration

High-density microchannel flow paths

Copper or copper-alloy thermal structures

Advanced brazing and sealing processes

Reduced thermal resistance

Lower pressure drop across the cooling loop

Compatibility with high-temperature coolant operation

Integration with GPU, CPU, networking, and optical module layouts

The value of the cold plate is increasing because it is no longer a simple heat sink. It is becoming a precision thermal-management component that directly affects AI system performance, reliability, and deployment density.

Rack Level: Metal Manifolds and Quick Disconnects

As rack density increases, cooling distribution inside the rack becomes more complex.

Traditional liquid-cooling systems often use flexible hoses to connect servers, cold plates, and distribution systems. While flexible hoses are widely used, they can introduce maintenance challenges related to aging, vibration, leakage risk, and inconsistent flow resistance.

The next generation of AI liquid-cooling systems is moving toward more standardized rack-level fluid distribution.

Key trends include:

Rigid metal manifolds

Integrated rack fluid channels

Low-leakage quick disconnect couplings

Self-sealing connection systems

Reduced hose length

Standardized liquid-cooling interfaces

Improved flow balancing across multiple trays

Lower system pressure drop

As AI racks move toward 100kW, 200kW, and eventually higher power levels, rack-level manifolds will become one of the most important reliability components in the entire liquid-cooling system.

CDU Level: From Cooling Accessory to Thermal Control Center

The Coolant Distribution Unit (CDU) is becoming the central control point for AI data center liquid cooling.

In lower-density systems, a CDU may simply provide heat exchange and coolant circulation. In high-density AI infrastructure, the CDU must manage large flow volumes, pressure stability, temperature control, water quality, and multiple rack cooling loops.

Future high-power CDUs will require:

Large-capacity heat exchange capability

High-flow and high-pressure pump systems

Multi-loop intelligent flow control

45°C warm-water supply temperature management

Real-time temperature and pressure monitoring

Automatic leakage detection

Water-quality monitoring

Redundant pump and control architecture

Modular expansion for multiple AI racks

Integration with BMS and DCIM platforms

For large AI clusters, the CDU will no longer be a supporting device. It will become a critical infrastructure platform that directly determines rack availability and operational reliability.

Facility Level: Dry Cooling, Closed Loops, and Heat Reuse

The adoption of 45°C supply water also changes how AI data centers are designed at the facility level.

Instead of relying primarily on chilled-water plants and air-conditioning systems, next-generation AI facilities can use:

Dry coolers

Closed-loop water systems

Plate heat exchangers

High-temperature water loops

Outdoor natural cooling

Heat-recovery systems

Intelligent environmental monitoring

Digital-twin-based cooling optimization

The higher return-water temperature can also improve heat-reuse potential. Heat from AI data centers may be used for district heating, industrial preheating, hot-water systems, greenhouse heating, or thermal energy storage.

4.New Technical Requirements for Liquid-Cooling Components

The Rubin generation will raise technical requirements across the entire liquid-cooling supply chain.

Microchannel Cold Plates

High-power AI chips require cold plates with greater heat-transfer efficiency and more consistent manufacturing quality.

Key technical requirements include:

Cold plate suppliers must improve not only thermal performance but also brazing yield, inspection capability, material compatibility, and long-term reliability testing.

Manifolds, Quick Connectors, and Fluid Distribution

For full liquid-cooled AI racks, fluid distribution components must support continuous 24/7 operation under high power density.

Important requirements include:

Long-life quick disconnect cycles

Low-drip or zero-drip connection design

Self-sealing mechanisms

Low pressure loss

Corrosion-resistant metal materials

High-temperature sealing performance

Standardized interfaces

Leak detection compatibility

Easy tray replacement and maintenance

The shift from flexible hoses to metal manifolds and integrated fluid pathways will increase the importance of precision machining, welding, sealing technology, and quality control.

Cooling Fluids and Water Quality Management

In a high-temperature closed-loop liquid-cooling environment, coolant quality becomes a major reliability factor.

The cooling fluid must protect cold plates, manifolds, pumps, valves, seals, and heat exchangers over many years of operation.

A complete water-quality management strategy should include:

Conductivity monitoring

pH monitoring

Turbidity monitoring

Corrosion inhibitor monitoring

Particle filtration

Microbial control

Automatic bypass filtration

Coolant replacement planning

Leak detection and alarm systems

Cooling fluids, sealing materials, and thermal interface materials must also withstand long-term operation at temperatures between 45°C and 55°C without swelling, degradation, corrosion, or chemical precipitation.

5. Impact on the AI Data Center Industry

The adoption of full liquid cooling will reshape the AI infrastructure market in three major ways.

Liquid Cooling Becomes a Deployment Requirement

For the next generation of high-density AI infrastructure, liquid cooling will increasingly become a prerequisite rather than an optional upgrade.

Data center operators planning to deploy Rubin-based systems will need to prepare:

Liquid-cooling-ready server halls

CDU capacity

Primary and secondary water loops

Dry cooling or heat-rejection systems

Rack-level manifolds

Leak detection systems

Water-quality management

Maintenance and service procedures

This will accelerate the transition from conventional enterprise data centers to AI factory infrastructure.

High-Value Liquid-Cooling Components Gain Importance

The most valuable parts of the liquid-cooling supply chain will include:

Microchannel cold plates

Integrated cooling trays

Rack-level manifolds

Quick disconnect couplings

Liquid-cooled busbars

High-power CDUs

Heat exchangers

Dry coolers

Intelligent monitoring systems

Water-quality control equipment

The competitive advantage will increasingly depend on thermal design, manufacturing precision, reliability validation, system integration, and global delivery capability.

Standardization Will Accelerate

NVIDIA’s MGX modular architecture and DSX AI factory reference design are expected to support broader ecosystem standardization.

In the future, AI liquid-cooling systems will likely move toward more standardized interfaces for:

Cold plates

Server trays

Rack manifolds

Quick connectors

CDU interfaces

Monitoring protocols

Facility water loops

Digital-twin simulation models

Standardization will help reduce deployment time, improve interoperability, and lower maintenance complexity.

6. Future Technology Roadmap

In the near term, direct-to-chip cold plate liquid cooling will remain the primary solution for high-density AI servers.

From 2026 to 2028, the market is expected to focus on:

45°C warm-water cooling

100% liquid-cooled rack architectures

Fanless server systems

High-capacity CDUs

Metal manifold systems

Liquid-cooled power distribution

Standardized rack-level cooling interfaces

Heat-recovery-ready data center design

In the longer term, as rack power density moves toward 300kW, 500kW, or even higher levels, immersion cooling may become an additional option for ultra-high-density workloads.

Lianli’s One-Stop Liquid Cooling Solution for NVIDIA:
Lianli is a provider of liquid cooling solutions for AI data centers, offering customized systems perfectly compatible with NVIDIA’s GB200/GB300 and H100/H200 series. Its products achieve a PUE of below 1.15 and an overall energy-saving rate exceeding 30%, positioning the company at the forefront of the industry in terms of technical capability.

Conclusion

NVIDIA Vera Rubin marks an important milestone in the evolution of AI infrastructure.

The platform’s 100% liquid-cooled architecture, 45°C warm-water cooling capability, fanless system design, and AI factory reference model are accelerating the transition toward high-density, high-efficiency liquid-cooled data centers.

For AI data center operators, the question is no longer whether to adopt liquid cooling. The real question is whether their infrastructure is ready for high-temperature water, 100kW+ rack density, intelligent CDU control, long-term water-quality management, and large-scale liquid-cooling operations.

For liquid-cooling equipment manufacturers, Rubin creates new opportunities in high-performance cold plates, precision metal manifolds, quick connectors, liquid-cooled busbars, high-capacity CDUs, dry cooling systems, and integrated AI data center solutions.

As chip power continues to rise and energy-efficiency requirements become stricter, full liquid cooling will become one of the defining technologies of the next generation of AI factories.