GigaCapacity
comparison
index
Updated 8/4/2026

Best Liquid Cooling Solutions and Companies for AI Data Centers in 2026

Compare liquid cooling solutions and companies for AI data centers by architecture fit, facility integration, operations, and evidence buyers should request.

By Simon Jester, Editor

Simon Jester is GigaCapacity's editor covering AI infrastructure capacity, data center power, cooling, and provider selection.

TL;DR: best liquid cooling solutions and companies in 2026

The best liquid cooling solution is the one the facility, server design, operations team, and warranty boundary can support. Start with the cooling architecture, then compare companies by integration responsibility and proof.

Company or solutionBest forQuick list hint
VertivBest for facility-scale thermal management and infrastructure integrationVerify CDU, heat rejection, service scope, and controls integration.
CoolIT SystemsBest for direct liquid cooling components and cold-plate deploymentsMatch server platform, manifold, coolant, and warranty boundaries.
Schneider ElectricBest for integrated power, cooling, and data center infrastructure planningConfirm end-to-end scope, controls responsibility, and facility retrofit limits.
LiquidStackBest for immersion and high-density liquid cooling evaluationVerify tank or system fit, operations model, maintenance, and fluid handling.
SubmerBest for immersion and modular liquid-cooled deployment pathsCheck facility interface, service plan, and hardware compatibility.
AccelsiusBest for two-phase direct-to-chip diligenceConfirm refrigerant path, service model, and server support.
GRCBest for immersion cooling retrofit and density comparisonsVerify deployment envelope, operating procedures, and facility heat rejection.
ZutaCoreBest for waterless two-phase direct-to-chip evaluationRequire server, warranty, service, and operational evidence.

Buyer action

Pressure-test the cooling shortlist before vendor outreach

Use these tools after the provider shortlist to compare direct-to-chip and immersion fit, size rack-level cooling load, and prepare quote questions for GPU colocation providers.

Fit depends on rack density, chip type, coolant boundary, facility water strategy, heat rejection, hardware warranty, operations staffing, and whether the buyer is retrofitting an existing hall or building a new one.

How should buyers choose between direct-to-chip and immersion?

Direct-to-chip can fit buyers that need to keep more conventional rack service models while removing heat at the chip. Immersion can fit very high-density or specialized environments, but it changes hardware handling, service workflow, fluid management, and procurement assumptions. The decision should be made with the server vendor, facility operator, cooling vendor, and operations owner in the same diligence loop.

What evidence proves a liquid cooling company can support AI data centers?

Ask for compatible server platforms, CDU or tank specifications, coolant requirements, manifold design, leak detection, heat-rejection path, maintenance procedure, warranty boundary, spares plan, installer scope, commissioning process, service-level assumptions, and references with comparable density. For colocation, also confirm what the landlord allows.

What facility constraints can break a liquid cooling plan?

The common blockers are floor loading, water availability, heat-rejection capacity, power and cooling redundancy, pipe routing, containment, service access, insurance requirements, and tenant-landlord responsibility. A cooling vendor can have a strong product and still be a poor fit if the data hall cannot support the integration.

How should buyer RFPs frame liquid cooling?

The RFP should separate the workload requirement from the preferred solution. Require each respondent to state the supported density, architecture, fluids, facility tie-ins, warranty assumptions, operations tasks, installation timeline, failure modes, monitoring data, and exclusions. Avoid accepting a generic liquid-cooling label without a named architecture and responsibility matrix.

Methodology

Reviewed public company and technical sources available on August 4, 2026. This page groups companies by observable buyer fit and cooling architecture. It does not rank providers universally because liquid cooling fit depends on server design, rack density, facility infrastructure, warranty terms, operations model, and deployment timing.

Comparison Table

NameCategoryBest FitEvidenceBuyer Caveat
VertivFacility thermal management and liquid cooling infrastructureData center owners and operators that need cooling tied to power, controls, service, and facility design.Vertiv public liquid cooling materials support initial diligence on CDU and facility integration.Confirm the exact product, heat-rejection scope, and service boundary.
CoolIT SystemsDirect liquid cooling componentsServer and rack designs that need direct-to-chip cooling components and integration support.CoolIT public materials support diligence on direct liquid cooling systems.Match the design to the server platform, warranty, manifold, and coolant requirements.
Schneider ElectricIntegrated data center infrastructure and liquid coolingBuyers that need cooling decisions connected to power, controls, electrical design, and facility operations.Schneider Electric public liquid cooling materials support infrastructure-level diligence.Clarify what is supplied directly, partnered, installed, monitored, and maintained.
LiquidStackImmersion and liquid cooling systemsHigh-density AI and HPC environments considering immersion or specialized liquid systems.LiquidStack public materials support initial immersion cooling diligence.Verify hardware compatibility, fluid handling, service process, and facility integration.
SubmerImmersion and modular liquid coolingImmersion-oriented deployments and modular high-density infrastructure.Submer public materials support diligence on immersion and modular cooling options.Confirm operating model, maintenance workflow, and integration with facility heat rejection.
AccelsiusTwo-phase direct-to-chip coolingMission-critical AI and HPC racks where two-phase direct-to-chip architecture is under consideration.Accelsius public materials support diligence on two-phase direct-to-chip claims.Verify server support, refrigerant boundary, service plan, and warranty assumptions.
GRCImmersion coolingRetrofit or new-build density projects evaluating immersion cooling as a facility strategy.GRC public materials support initial immersion cooling diligence.Confirm physical envelope, operations workflow, and fluid management.
ZutaCoreWaterless two-phase direct-to-chip coolingAI or HPC racks where waterless two-phase direct-to-chip cooling is being evaluated.ZutaCore public materials support initial architecture diligence.Require server compatibility, support, monitoring, and service evidence.

FAQ

What are the best liquid cooling companies for AI data centers in 2026?

A fit-based shortlist includes Vertiv, CoolIT Systems, Schneider Electric, LiquidStack, Submer, Accelsius, GRC, and ZutaCore. The best choice depends on architecture, facility constraints, server support, operations model, and warranty terms.

Is direct-to-chip cooling better than immersion cooling?

Neither is universally better. Direct-to-chip can preserve more conventional rack workflows, while immersion can fit certain high-density designs. Buyers should compare facility integration, server compatibility, operations, and service risk.

What should buyers verify before choosing a liquid cooling vendor?

Verify density support, compatible hardware, coolant or refrigerant boundary, CDU or tank specifications, heat rejection, maintenance workflow, warranty terms, commissioning plan, and responsibility matrix.

Sources

Next Steps