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Single-GPU power has crossed 1kW and single-rack heat density can exceed 100kW, exhausting air cooling headroom and making liquid cooling the default for high-density AI data centers. In this architecture, the data center liquid cooling CDU (Coolant Distribution Unit) moves chip heat from the secondary loop to the primary cooling system, using pumps, heat exchangers, valves and controls to keep circulation stable while monitoring leaks and temperature in real time. Its reliability decides whether compute runs steady and efficient. Since NVIDIA's influence largely defines the core supply base, this article decodes its officially recognized CDU vendor and model list (September 2, 2026 version): 19 vendors, 28 models, plus selection guidance for 100MW-class GB200/GB300 data centers.

Inside a data center liquid cooling system, the CDU (Coolant Distribution Unit) is not an ordinary heat exchanger but the boundary point and hub of the whole architecture. It divides the loop into two independent circuits: the primary side, with outdoor cold sources, pumps and piping that reject heat to the atmosphere, and the secondary side, with the CDU, manifolds, quick connectors, cold plates and racks that sit on the chips and carry heat away. The two fluids never mix; heat is exchanged through a plate heat exchanger inside the CDU. It accounts for roughly 25% to 30% of a cold-plate liquid cooling system's cost and close to half the value of the part nearest the servers, making it the most valuable and technically demanding link in the chain.

Compute demand is growing at an exponential pace, from ChatGPT to domestic large models, from autonomous driving to AI inference servers, and data center rack power is climbing from 4 to 6kW to 20kW, 50kW and a future of 100kW and beyond. Air cooling has hit its ceiling, and liquid cooling has turned from an option into a necessity. In the liquid-cooled data center, the CDU (Coolant Distribution Unit) is the key hub connecting IT equipment with the outdoor cold source, and the liquid cooling piping that runs through it, especially high-purity stainless steel tubing, carries the core mission of delivering coolant safely, precisely and leak-free to every chip. That mission is the yardstick by which a CDU liquid cooling manufacturer is judged today.

As liquid cooling becomes the mainstream thermal solution for high-density data centers, the CDU, the liquid cooling distribution unit that acts as the "heart" of the loop, has seen market demand climb steadily. But behind the booming market, price chaos has followed. We often hear the same question from industry peers: CDU products with identical nominal flow, heat exchange capacity and supply and return temperatures can differ by up to half in quoted price across vendors. A batch of low-price CDUs far below the industry average looks complete on paper and nearly identical on the outside, making the price advantage very tempting. So can a low-price CDU really be bought? Many project owners are easily won over by beautiful paper specs during comparison. But after six months or a year in operation, failures surface one after another: insufficient heat exchange, corroded piping, clogged cold plates, unexpected leaks and server overheat shutdowns. Only then do they realize that the hundred thousand yuan saved in procurement turned into hundreds of thousands or even millions in operations losses and downtime compensation. The real traps are mostly not in the shell you can see, but in the hidden positions that only appear after opening it. This article dissects the six most common cost-cutting points to help you see the risks and avoid the pitfalls.

To most people, Vera Rubin means 3.6 ExaFLOPS of compute and seven new chips, but to the industry chain the real game changer is the cooling: the Vera Rubin rack is 100% liquid cooled, rewriting every rule for cold plates, piping, connectors, seals and inspection. Among them sits one unassuming part that decides whether the rack can run safely at all: the data center liquid cooling manifold. A single leak costs not one board but one server, one rack, or an entire machine room, and the pace of Rubin's mass production may well be held up by it.

The IT team's heartbeat rises and falls with data center temperatures, but this year Lao Zhang has stayed calm: the machine room is cool, the patrol found nothing wrong, and it even feels a bit cold. The CFO, Lao Jia, is anything but. Summer pushed temperatures past 40°C, server cooling costs kept climbing, and the cold air is literally money. The company added GPU accelerators for AI, which raised power consumption along with compute. Going full liquid would mean overhauling the data center, and with heart willing but budget unwilling, even the turnkey offerings of a GPU cabinet air liquid CDU manufacturer are out of reach. Staying with air cooling keeps PUE high and costs stuck, a real dilemma.

Trillion-parameter AI models are exploding compute density, and air cooling has hit its physical limit. NVIDIA's GB200/GB300 NVL72 racks peak at 120kW to 140kW, making 100% liquid cooling the only viable path for ultra-high-density data centers. In the secondary loop, the manifold is the core hub, connecting the liquid distribution unit CDU above to each server cold plate below, distributing coolant precisely to every GPU node while keeping pressure balanced and flow controlled. With AI chips and boards so costly, micro-leaks, pressure imbalance or uneven flow can burn out racks and stop business, so the manifold demands extreme pressure resistance, zero-leak precision, weld air-tightness, corrosion resistance and flow balance, one of the highest barriers in the AI liquid cooling chain.

When single-rack power crosses 60kW and AI model clusters run at full load around the clock, traditional air cooling has hit its physical ceiling, and cold-plate liquid cooling has become the standard for high-density compute, supercomputing centers and large data centers. Inside this system that decides whether compute can "output cool," one part is often overlooked yet life-deciding: the Manifold, or fluid distributor and header. The data center liquid cooling manifold connects the room-level CDU on one side and every server cold plate in the rack on the other, and is called the fluid heart of the liquid cooling rack. Flow balance, pressure drop, leakage and maintenance convenience all depend on it. This article explains its design logic, technical details and future trends in plain terms.

In the 2026 AI industry, NVIDIA Vera Rubin is the anchor no one can ignore, and what truly tenses the supply chain is its 100% liquid cooling, not the 3.6 ExaFLOPS headline. At GTC in March 2026, NVIDIA launched Vera Rubin with seven chips in mass production and five rack-scale systems; the flagship NVL72 packs 72 Rubin GPUs and 36 Vera CPUs in a fully liquid-cooled rack, with no cables, no fans and no exposed hoses, and a 45°C inlet that lets data centers skip chillers. Supermicro's NVL72 solution alone needs 16 vertical manifolds and 576 copper cold plates per rack. In the data center liquid cooling manifold system, dozens of coolant circuits depend on these metal parts to feed every chip evenly and collect the return flow, moving the manifold from an option to a mandatory mass-production question. TrendForce sees AI chip liquid cooling penetration rising from 33% in 2025 to 53% in 2026 and near 60% in 2027; Soochow sizes the global market at about RMB 94.2 billion in 2026 and RMB 147.8 billion in 2027.

The Manifold is more than piping; in high-end industrial fluid systems it is the core hub. Often reduced to "a pipe with branches," its real value lies in precision fluid distribution, collection and pressure stabilization, and it is widely used in data center liquid cooling, aerospace and new energy storage, where its performance decides system stability, heat exchange efficiency and equipment safety. In the liquid cooling loop, the liquid cooling CDU manifold is the precise control core between the cooling distribution unit and every branch, and the part that makes or breaks an entire high-end installation. This article breaks down its core uses, application scenarios, working principle and the four core processes of material selection, machining, surface treatment and quality inspection, grounded in industry standards, measured data and engineering cases.