• Nxera’s 58MW DC Tuas achieves 1.25 PUE using Singapore’s largest liquid cooling data centre deployment.
• Comes with proviso that tropical climates can support AI workloads.
• Over 90% pre-committed capacity signals demand in market where vacancy rates sit below 2%.

When Singapore imposed its data centre moratorium in 2019, the message was that the city-state’s 735 square kilometres couldn’t sustain endless rows of power-hungry facilities consuming 7% of national electricity.

Six years later, Nxera has opened DC Tuas with a solution that challenges the assumption that AI infrastructure and sustainability are mutually exclusive – by deploying Singapore’s largest liquid cooling data centre infrastructure at commercial scale.

The 58MW facility, which brings Nxera’s total Singapore capacity to 120MW, was over 90% committed before it opened. That’s not surprising in a market where vacancy rates hover below 2%.

What’s remarkable is how DC Tuas achieves a power use effectiveness (PUE) of 1.25 in a tropical climate – better than the 1.4-1.6 range that most regional facilities struggle to break.

The difference lies almost entirely in its cooling architecture. DC Tuas hosts what Nxera describes as Singapore’s largest direct-to-chip liquid cooling deployment in a multi-tenanted facility. The technology has rapidly evolved from experimental to essential as AI workloads have exploded in density and power consumption.

Why can’t air cooling keep up with AI?

The physics are straightforward: NVIDIA’s H100 GPUs consume around 700W per chip, while the newer Blackwell architecture pushes past 1,000W. Multiply that in entire racks running at 40kW to 120kW, and traditional air cooling simply runs out of thermal capacity. Air would need to be either sub-zero in temperature or moving at gale-force speeds to extract that much heat – neither practical nor efficient.

Water’s thermal conductivity is approximately 23 times higher than air’s. Direct-to-chip liquid cooling uses this by circulating coolant through cold plates mounted directly onto CPUs and GPUs, absorbing heat at the source. Research from Florida Atlantic University, recently highlighted by NVIDIA, demonstrates that liquid-cooled GPU systems deliver up to 17% higher computational throughput and reduce node-level power consumption by 16% compared to air-cooled equivalents.

For DC Tuas, this translates to practical advantages: higher rack densities without thermal throttling, reduced reliance on energy-intensive chillers, and the ability to operate with warmer facility water temperatures – important in Singapore’s tropical environment where ambient temperatures make conventional cooling more expensive.

Engineering for constraints

Bill Chang, CEO of Nxera and Singtel’s Digital InfraCo unit, frames DC Tuas as a response to Singapore’s unique constraints. “The ability to deploy higher-density, compute-intensive AI workloads sustainably is increasingly critical for a market where data centre capacity is constrained,” he noted at the launch.

Beyond liquid cooling, DC Tuas incorporates multiple systems designed specifically for tropical efficiency: smart thermal features, high-efficiency electrical systems, solar power generation, rainwater harvesting, condensate reuse, and blow-down recovery.

The facility holds Green Mark Platinum certification from Singapore’s Building and Construction Authority and IMDA, meeting the sustainability requirements that now govern new data centre capacity in Singapore.

The 120,000-square-foot, eight-storey facility is Singapore’s only hyper-connected data centre integrated with a cable landing station, providing customers direct access to international and domestic networks, considered essential for latency-sensitive inference workloads.

The regional calculation

Singapore’s December 2025 call for applications (DC-CFA2) sets out the trade-offs: Operators seeking 200MW of new capacity must demonstrate at least 50% green energy sourcing, best-in-class PUE ratings, and “contributions” to Singapore’s economic objectives.

The March 2026 application deadline will reveal which operators believe they can meet these requirements.

Nxera is already looking beyond Singapore’s borders. Additional AI-ready capacity is scheduled for Batam and Johor in the second half of 2026, part of a strategy to more than double operational and pipeline capacity from 200MW in 2026 to over 400MW mid-term.

While Singapore’s regulatory framework creates high barriers to entry, it creates pricing power and competitive moats for operators who can meet the technical requirements.

The broader question is whether other land-constrained markets facing similar resource pressures can replicate Singapore’s model. DC Tuas suggests the answer depends heavily on operators’ willingness to deploy advanced cooling technologies at a commercial scale and accept the capital costs that come with them.

For enterprises and hyperscalers betting on AI while facing pressure to reduce environmental footprints, facilities like DC Tuas may demonstrate that infrastructure exists to support both goals.

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