Introduction: Solving Extreme Thermal Density in AI Infrastructure
AI infrastructure managers, hyperscale data center operators, and HPC administrators face an unprecedented cooling challenge: next-generation AI accelerators (NVIDIA B200, AMD MI400, Intel Gaudi 4) consume 700-1,500W per GPU, with server-level power densities reaching 40-150kW per rack. Traditional air cooling (fans + heat sinks) becomes impractical above 500W per GPU, requiring deafening fan speeds (80-100 dBA), high air conditioning power (mechanical cooling, chillers, CRAH (computer room air handling units), CRAC (computer room air conditioners)), and limited density (max 10-20kW per rack). Without effective cooling, GPUs throttle (performance loss 20-40%), accelerate electromigration (lifespan reduction), and increase data center PUE (power usage effectiveness). The solution lies in AI liquid cooled servers—high-performance computing systems designed for AI workloads (large language model training, deep learning, generative AI inference) using liquid cooling (direct-to-chip cold plates, immersion cooling, or spray cooling) to dissipate heat from GPUs, CPUs, and memory modules efficiently. Liquid cooling handles 1,000W+ components, reduces fan noise, enables 50-150kW per rack density, and improves PUE from 1.5-1.8 (air) to 1.05-1.2 (liquid). This report provides a comprehensive forecast of adoption trends, cooling technology segmentation, deployment drivers, and hyperscale deployment schedules through 2032.
Global Leading Market Research Publisher QYResearch announces the release of its latest report “AI Liquid Cooled Servers – Global Market Share and Ranking, Overall Sales and Demand Forecast 2026-2032” . Based on current situation and impact historical analysis (2021-2025) and forecast calculations (2026-2032), this report provides a comprehensive analysis of the global AI Liquid Cooled Servers market, including market size, share, demand, industry development status, and forecasts for the next few years.
The global market for AI Liquid Cooled Servers was estimated to be worth US4,840millionin2025andisprojectedtoreachUS4,840millionin2025andisprojectedtoreachUS 29,670 million by 2032, growing at a CAGR of 30.0% from 2026 to 2032. In 2024, global AI liquid cooled servers sales reached approximately 450,000 units, with an average market price of around US$ 8,700 per unit. This updated valuation (Q2 2026 data) reflects explosive demand for generative AI model training (GPT-5, Gemini 2.0, Llama 4, Claude 4, etc.), hyperscale AI cluster buildouts (Microsoft Azure, AWS, Google Cloud, Meta, xAI, Oracle, CoreWeave, Lambda), and HPC centers upgrading to liquid cooling.
Product Definition & Key Characteristics
An AI liquid-cooled server is a high-performance computing system designed for artificial intelligence workloads (such as deep learning training, large language models, and HPC applications) that uses liquid cooling instead of traditional air cooling to dissipate heat from GPUs, CPUs, and other high-power components. Unlike standard air-cooled servers with fans and heatsinks, liquid-cooled systems employ direct-to-chip cooling plates, immersion cooling, or cold plates with dielectric fluids to manage extreme thermal loads efficiently.
Cooling Technology Comparison:
| Cooling Method | Heat Capture Efficiency | Maximum Component TDP (GPU) | Rack Density (kW/rack) | PUE (Typical) | Infrastructure Complexity | Cost Premium (vs. air) |
|---|---|---|---|---|---|---|
| Air Cooling (baseline) | Low | 350-450W (limited) | 10-20 | 1.5-1.8 | Low | Baseline |
| Cold Plate (Direct-to-Chip) | Medium-High | 700-1,200W | 30-80 | 1.1-1.3 | Medium | 20-40% |
| Immersion Cooling (Single-Phase) | High | 700-1,500W | 50-150 | 1.05-1.1 | High | 40-60% |
| Immersion Cooling (Two-Phase) | Very High | 1,000-2,000W | 80-200 | 1.02-1.05 | Very High | 60-120% |
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Technical Classification & Product Segmentation
The AI Liquid Cooled Servers market is segmented as below:
Segment by Cooling Technology
- Cold Plate Cooling (Indirect Type) – Direct-to-chip cooling plates (copper or aluminum) mounted on GPUs/ CPUs, with water/glycol or dielectric fluid circulating through manifolds. Dominant (60-65% market share). Advantages: Minimal server hardware modification (retrofits with cold plates), lower cost, proven reliability. Disadvantages: Still requires facility water/ coolant distribution (CDU, coolant distribution unit). Used by: Dell, HP, Supermicro, Lenovo, Inspur, xFusion, Nettrix, Cisco, Nor-Tech, Ingrasys, Foxconn Industrial Internet.
- Immersion Cooling (Direct Type) – Server components submerged in dielectric fluid (single-phase or two-phase boiling). Second largest (30-35% share). Advantages: Highest cooling efficiency, no fans (zero noise), ultra-high density (100-200kW/rack). Disadvantages: Requires custom server chassis (no fans, no vents), fluid maintenance (filtration, periodic replacement), higher capital cost. Used by: Iceotope, Green Revolution Cooling (not in server list), LiquidStack (not in list) – OEM partners (HP, Dell, Supermicro, Lenovo, Inspur, xFusion, Nettrix, Foxconn Industrial Internet, Ingrasys).
- Spray Cooling (Direct Type) – Dielectric fluid sprayed directly onto hot components (no immersion). Niche (<5%). Used in extreme density, power (1,500W+). Limited commercial deployment.
Segment by End-User
- Internet (Cloud/Hyperscale) – Microsoft Azure, AWS (Amazon Web Services), Google Cloud, Meta, Oracle, xAI, CoreWeave, Lambda, Alibaba Cloud, Tencent Cloud, Baidu Cloud, ByteDance (TikTok). Largest segment (50-55% of market). AI training clusters (100-100,000+ H100/B200/GB200/MI400 clusters, DGX B200, HGX B200, MGX).
- Telecom Operator – 5G edge AI inference, network analytics. 15-20%.
- Government – National labs (supercomputing), defense AI, weather/climate modeling (ECMWF, NOAA, NCAR, NREL, LANL, SNL, LLNL, ORNL, ANL, PNNL, NNSA, DARPA, DoD HPC Modernization Program). 10-15%.
- Others – Enterprise (Fortune 500, pharmaceuticals, financial services, autonomous vehicles, robotics), research universities, HPC centers. 15-20%.
Key Players & Competitive Landscape
Server OEMs (traditional compute) and specialized liquid cooling integrators:
- Dell Technologies (US) – PowerEdge XE series AI servers (liquid-cooled, direct-to-chip cold plates for NVIDIA HGX B200, GB200 NVL72 racks). Leading hyperscale supplier.
- HP (US) – HPE Cray supercomputers, HPE ProLiant XL series with liquid cooling options.
- Cisco (US) – UCS (unified computing system) AI servers (UCS X-series, integrated with liquid cooling).
- Supermicro (US) – AI servers (GPU-accelerated, liquid-cooled with cold plates, immersion-ready chassis). Hyperscale OEM for Meta, AWS, Google, Microsoft (custom designs).
- Nor-Tech (US) – HPC AI system integrator (liquid-cooled custom servers).
- Iceotope (UK) – Immersion cooling specialist (liquid-cooled server chassis, not full server OEM). Partners with Dell, HP, Supermicro, Lenovo, Inspur, xFusion, Nettrix, Foxconn.
- Inspur Electronic Information Industry (China) – Chinese AI server leader (liquid-cooled for Alibaba, Tencent, Baidu, ByteDance). Domestic & export (to Norway, Iceland via Chinese-owned colos).
- xFusion Digital Technologies (China) – Chinese AI server (liquid-cooled), spun off from Huawei server division.
- Nettrix Information Industry (China) – Chinese AI server (liquid-cooled).
- Lenovo (China) – ThinkSystem AI servers (SR670, SR680, SR850, SR950, SR980, SR990) liquid cooling (Neptune). Hyperscale OEM.
- Dawning Information Industry (Sugon) (China) – Chinese HPC servers, liquid cooling for government/national labs.
- Tsinghua Unigroup (China) – Semiconductor, server OEM (UniCloud).
- Huawei (China) – FusionServer (liquid-cooled AI, GPU/NPU based). At offering. Sanctions limited western market.
- ZTE (China) – Chinese server OEM.
- Foxconn Industrial Internet (Taiwan/China) – Server OEM for hyperscalers (AWS, Google, Microsoft, Meta). Liquid-cooled AI server manufacturing.
- Sunway BlueLight MPP (China) – Sunway TaihuLight successor (HPC, liquid-cooled). Domestic.
- Ingrasys (Taiwan) – Server OEM (Foxconn subsidiary). AI liquid-cooled server manufacturing for hyperscalers.
Recent Industry Developments (Last 6 Months – March to September 2026)
- May 2026: NVIDIA announced DGX B200 (Blackwell Ultra) 8-GPU system (1,200W per GPU, 9.6kW per node) requires liquid cooling (cold plate) as standard (no air-cooled variant). Shipments Q3 2026. Dell, HP, Supermicro, Lenovo, Inspur, xFusion, Nettrix, Foxconn, Ingrasys offer liquid-cooled DGX B200 servers.
- July 2026: Meta (Facebook) announced AI Research SuperCluster (RSC) Phase 5 (2027) to deploy immersion-cooled racks (Iceotope liquid cooling) for Llama 4 training (16,000 H200/B200 GB200 NVL72 racks). 150kW per rack, PUE 1.07.
- Technical challenge identified by QYResearch field surveys (August 2026): Fluid conductivity and galvanic corrosion in mixed-metal cold plates (copper cold plate + aluminum radiator + water/glycol coolant). Field data from 15,000 liquid-cooled AI servers (2024-2025):
- Deionized water + ethylene glycol coolant: corrosion rates in copper cold plates <0.5 mil/year acceptable)
- Tap water or insufficient water treatment → elevated pH, dissolved solids → cold plate pitting, leak failures (0.5-2% of systems over 2 years)
- Dielectric fluids (immersion, single-phase immersion cooling, fluorocarbons, synthetic esters): corrosion negligible, but fluid degradation after 3-5 years requires replacement, fluid maintenance, filtration.
Industry Layering: Cold Plate (Direct-to-Chip) vs. Immersion Cooling for AI Servers
| Parameter | Cold Plate (Direct-to-Chip) | Immersion Cooling (Single-Phase) |
|---|---|---|
| Server Chassis Modifications | Moderate (cold plates, manifolds, fluid connectors) | High (custom chassis, no fans, sealed enclosure, blind-mate connectors) |
| Rack Density (kW) | 30-80 kW/rack | 50-150 kW/rack |
| Coolant | Water/glycol, or dielectric fluid (deionized water + additives) | Dielectric fluid (synthetic oil, fluorocarbon) |
| Facility Infrastructure | CDU (coolant distribution unit), facility water (cooling tower/ chiller), dry cooler | Larger CDU, fluid storage, filtration, fluid handling system |
| PUE (Typical) | 1.08-1.2 | 1.02-1.08 |
| Maintenance | Moderate (leak-testing, quick-disconnect (QDC) fittings, periodic fluid chemistry, water treatment) | High (fluid analysis, dielectric fluid replacement, fluid compatibility, wetted materials compatibility, non-conductive testing) |
| Adoption Rate (Hyperscale AI) | 70-80% | 20-30% (growing for hot climates, megawatt-scale AI clusters) |
Exclusive Observation: “Rack-Level CDU (Coolant Distribution Unit) Integration for AI Clusters”
In a proprietary QYSearch analysis of 24 hyperscale data center AI clusters (2025-2026), 92% use distributed CDUs (per rack, 2-4 CDUs per rack) vs. central CDU (room-level, single large CDU). Distributed CDU reduces pipe runs, improves fault tolerance (1 CDU fails, rest continue), and allows mixed cooling technologies (cold plate + immersion within same row). Dell PowerEdge XE, HP Cray, Supermicro AI servers integrate rack-level CDUs. Quick-disconnect (QDC) fittings (dry-break, tool-less) for server-to-rack fluid connection.
Policy & Regional Dynamics
- EU: EU Code of Conduct for Data Centre Energy Efficiency (v12, 2025) – requires PUE <1.3 for new data centers; liquid cooling necessary for high-density AI. Member states may offer tax incentives for PUE <1.1 (immersion).
- US: DOE Better Buildings Data Center Accelerator – recognition for liquid-cooled AI clusters; no federal mandate. Some states (California Title 24, energy code) encourage liquid cooling for existing building retrofits.
- China: MIIT “Data Center Green Low-Carbon Technology Adoption Catalogue” (2025) lists immersion liquid cooling as “recommended technology”. New Chinese data centers (Shenzhen, Beijing, Shanghai, Hangzhou) require PUE <1.3, cool-climate; immersion may get faster approval.
Conclusion & Outlook
The AI liquid cooled servers market is positioned for explosive 30%+ CAGR growth (2026-2032), driven by 1,000W+ GPU TDPs, 150kW+ rack densities, and hyperscale AI training cluster buildouts required for LLM scaling (compute demand doubling every 6-9 months). Cold plate cooling dominates (70-80%, proven, lower barrier); immersion cooling grows fastest (ultra-high density, zero fan noise, lower PUE). The next frontier is two-phase immersion cooling (dielectric fluid boiling, 100-200kW/rack, PUE <1.03) for exascale AI clusters (100,000+ GPUs). Manufacturers investing in leak-proof quick-disconnect fittings (QDC, 10,000+ connect/disconnect cycles), mixed-metal corrosion inhibitors (water/glycol for cold plates), and software-defined cooling (CDU flow rate modulation by GPU temperature) will lead AI liquid cooling infrastructure for hyperscale and HPC.
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