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Composable GPU · CXL memory · NVMe pooling

Liqid composable infrastructure
Pool GPUs and memory across the servers you already run

Liqid moves GPUs, CXL memory and NVMe out of individual servers into shared, fabric-attached chassis. LIQID Matrix software then assigns those devices to bare-metal hosts in seconds. One 1U or 2U server can run up to 30 GPUs, and a GPU sitting idle on one host can move to another without anyone opening a chassis. We can supply and quote the full Liqid range, sized against the servers you run.
GPUS COMPOSED TO ONE HOST
HOSTS SHARING ONE SMARTSTACK
600 W[src]
GPU SLOTS, 10 PER EX-5410P
20 TB[src]
CXL MEMORY PER CHASSIS
100 TB[src]
MEMORY COMPOSED TO ONE SERVER
128 GB/s[src]
PER GEN5 X16 HOST LINK
How it works

Disaggregate the devices, then compose the server you need

In a conventional server the GPUs, memory and NVMe are fixed at purchase. Slot count, power supplies and airflow decide what fits, and whatever you install stays there for the life of the box. Liqid calls its alternative composable disaggregated infrastructure (CDI)[src]: devices live in external chassis, connect to standard servers over a PCIe Gen5 or CXL 2.0 fabric, and are attached to whichever host needs them by software.

Four pieces make it work[src]. Expansion chassis hold the devices: the EX-5410P takes ten 600 W double-wide PCIe cards. Gen5 fabric switches connect the chassis to the hosts. A host bus adapter goes in each server. LIQID Matrix decides which device belongs to which host. Liqid states that composed GPUs appear to the host as native bare-metal PCIe devices[src], and its host bus adapter needs no additional software[src].

Liqid PCIe Gen5 fabric: three hosts, two device chassisIllustrative layout. Host models are from Liqid's compatibility list.LIQID Matrix softwareCompose · scale · reassign via UI, CLI or REST APImanagement networkHOST SERVERSDell PowerEdge R760HX-5160P-1C Gen5 HBACisco UCS C240 M8HX-5160P-1C Gen5 HBAPRIMERGY RX2540 M8CDI model · Gen5 HBAFX-5016-216 ports · 115 nsGen5 x16 · up to 128 GB/s per portEX-5410P · GPUs10 slots, 600 W cardsEX-5410P · NVMe + DPUNVMe AIC, FPGA, DPUIllustrative layout. Host models are from Liqid's compatibility list.
A three-host Liqid PCIe fabric. GPUs and NVMe sit in EX-5410P chassis; the switch and HBAs carry Gen5 x16 links; Matrix assigns each slot to a host. Memory pooling uses its own CXL 2.0 switch and chassis, covered on the CXL memory page. Port figures from Liqid's FX-5016-2, EX-5410P and HX-5160P-1C datasheets.
Why pool

The same GPUs do more work when they are not locked in one box

Fixed GPU servers strand capacity in two ways. A busy host hits its slot limit while its neighbour's GPUs sit idle, and a job that needs more GPUs than any single server holds cannot run at all. A pool removes both limits, because demand is matched against the total rather than against each box.
Fixed GPU servers versus one composable GPU poolIllustrative arithmetic on four 4-GPU servers; your own demand profile decides the real gain.Fixed: GPUs locked inside each serverComposable: one shared poolBar = installed · fill = in use · red outline = demand it cannot meetSame 16 GPUs, assigned where the demand isInference hostneeds 7 GPUsVDI hostneeds 2 GPUsDev/test hostneeds 1 GPUsRender hostneeds 4 GPUsInference 7 · VDI 2 · Dev/test 1 · Render 469%In use, fixed88%In use, pooled3 → 0Unmet GPUsIllustrative arithmetic on four 4-GPU servers; your own demand profile decides the real gain.
Worked example, not a Liqid benchmark: four servers with four GPUs each (16 GPUs) against a demand of 14. Fixed, 11 GPUs do work (69%) and 3 GPUs of demand go unmet, because the inference job needs seven and no box has more than four. Pooled, the same 16 GPUs serve all 14 (88%).

Liqid publishes bigger numbers for this effect: up to 75% fewer servers for the same GPU throughput and infrastructure costs cut by up to 50%, plus, separately, up to 3.5× greater MLPerf performance from direct GPU-to-GPU communication[src]. Treat them as the vendor's best cases. On its MI350P datasheet Liqid labels its own efficiency figures “targets, not measurements”[src]. The useful number is yours: put your teams' GPU counts and peak times into the GPU & CXL memory pooling calculator, or send them to us and we'll model the pooled estate against the fixed one before you buy.

The range

Liqid products we supply and quote

Liqid sells software, fabric hardware and validated bundles that combine them. Each family has its own page with full specifications and sources.
GPU pooling

Liqid GPU pooling: SmartStack & UltraStack

Up to 30 GPUs to one server, or shared across up to 16. Specs and options →
UltraStack MI350P

UltraStack with AMD Instinct MI350P

4 to 30 MI350P GPUs on one AMD EPYC host. Specs and options →
CXL memory

Liqid CXL memory pooling

Up to 20 TB per chassis; up to 100 TB composed to one server. Specs and options →
Matrix software

LIQID Matrix software

One UI and API for composing GPUs, memory and storage. Specs and options →
Fabric hardware

Liqid PCIe & CXL fabric hardware

EX-5410P/C chassis, FX switches and Gen5 HBAs. Specs and options →
IO Accelerator

Liqid LQD4500 IO Accelerator

Up to 32 TB NVMe on one PCIe Gen4 x16 card. Specs and options →
Compatibility

Liqid server & GPU compatibility

Which servers and GPUs Liqid has tested, by vendor. Specs and options →
Liqid GPU bundles: GPUs versus host serversHost counts are maximums per bundle; larger fabrics are built from multiple switches.Max GPUsMax host serversUltraStack 10scale-up101UltraStack 20scale-up201UltraStack 30scale-up301SmartStack 10shared pool104SmartStack 20shared pool208SmartStack 30shared pool306SmartStack 30+shared pool3016Host counts are maximums per bundle; larger fabrics are built from multiple switches.
Liqid's UltraStack and SmartStack GPU bundles by GPU count and host count. UltraStack puts all GPUs on one server; SmartStack spreads them across up to 16. Source: Liqid GPU pooling page and EX-5410P SmartStack datasheet.
Choosing

Which Liqid product fits the problem?

Start from the constraint you are hitting, not from the product list.
If you need…Start withWhy
More GPUs in one server than its chassis allowsUltraStack 10 / 20 / 30Up to 30 GPUs composed to a single host
A GPU pool shared between teams or shiftsSmartStack 10 to 30+10 to 30 GPUs across 4 to 16 hosts
Private, multi-model AI inference on one serverUltraStack with AMD MI350P4 to 30 MI350P, 144 GB HBM3E each
Memory-bound databases, RAG or KV cacheEX-5410C CXL SmartStack10 to 40 TB SmartStacks; up to 100 TB per server on a larger fabric
GPUs for Dell PowerEdge MX bladesSmartStack MXUp to 20 GPUs per MX compute sled
600 W GPUs on Cisco UCS C-SeriesCisco reference design30 GPUs pooled across up to 8 UCS servers
Very fast local NVMe for a GPU hostLQD4500 IO AcceleratorUp to 32 TB and 4M read IOPS per card

Sources: GPU pooling page, SmartStack, MI350P, EX-5410C, SmartStack MX and LQD4500 datasheets, and Liqid's Cisco UCS brief. Bundles are fixed, validated configurations; we confirm the current revision on quote.

Fit

Where composability pays, and where it doesn't

Liqid is not the answer to every GPU purchase. This is how we advise on it.
Good fit

Expensive GPUs with uneven demand

Several teams, one budget. Inference spikes in the day, batch jobs at night, a research group that needs 12 GPUs for a fortnight. A pool lets you buy for the combined peak rather than every team's peak. See the day/night example on the Matrix page.
Good fit

Many models, one server

Liqid's MI350P system runs one model per GPU, up to 30 on one host, with no network hops between GPUs[src]. That suits private inference estates that serve many small and mid-size models. UltraStack MI350P →
Good fit

Memory-bound data

Vector and graph databases, RAG indexes and KV cache often run out of DRAM before they run out of compute. CXL pooling adds up to 20 TB per chassis[src]. CXL memory pooling →
Good fit

Refreshing servers, keeping GPUs

Liqid's own example: buy a new 1U server with new CPUs and RAM, then compose the existing GPUs and storage to it instead of replacing the whole box[src].
Look elsewhere

One big, tightly coupled training job

Liqid composes PCIe cards. Eight SXM GPUs on an NVLink baseboard are purpose-built for that job: compare NVIDIA DGX and Dell PowerEdge XE.
Look elsewhere

One GPU per server, busy all day

If every GPU is already fully used where it sits, there is nothing to pool. A conventional GPU server from our server configuration service is simpler.
Facility and support

What to check before a Liqid system arrives

CheckWhat Liqid publishesWhy it matters
GPU chassis powerEX-5410P: 4 × 3000 W Titanium PSUs, Saf-D-Grid 400 V connectors, 100–277 VAC[src]Your PDUs need matching inlets and circuits per chassis.
Operating temperatureEX-5410P: 0–27 °C[src]. EX-5410C and the FX switches: 0–35 °C[src][src]The GPU chassis has a lower ceiling than most servers. Check your inlet temperature.
Whole-system powerUltraStack MI350P: about 22 kW at 30 GPUs, air-cooled[src]Plan rack density with our rack power planner.
Host operating systemHBA hot-plug on Windows and Linux; Windows Server 2012 R2 or later, no desktop editions[src]Desktop editions of Windows are not supported, and the BIOS must support PCIe native mode.
Warranty and supportSmartStack: 36- or 60-month software and hardware[src]Two terms are offered, covering Liqid software and hardware; we quote both.
Support hoursStandard support Mon–Fri 8am–5pm US Mountain time, with no holiday or after-hours cover. The same sheet sets a 1-hour Sev 1 response target and on-call paging by phone for outages[src]Standard hours are roughly 3pm to midnight UK time for most of the year. We confirm which support tier applies on your quote.

Turn the kilowatts into cooling with the server room cooling calculator, and size the GPUs themselves with the AI GPU calculator.

Supply & quote

Get a Liqid system sized and quoted

  • We check your servers and GPUs against Liqid’s current compatibility list, including the riser, BIOS and enclosure footnotes.
  • We size the bundle against your workload: UltraStack, SmartStack, MI350P or CXL memory.
  • We quote the whole build: Liqid hardware and Matrix, plus host servers, GPUs and networking.
  • We confirm lead time, warranty term and support path on every quote.

Get a Liqid quote

Tell us what you want to pool and which servers you run. We size it against Liqid's hardware compatibility list and quote the complete build.

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FAQs

Liqid composable infrastructure: common questions

What is Liqid?

Liqid is a composable infrastructure company founded in the greater Denver area. It makes LIQID Matrix software and the PCIe Gen5 and CXL 2.0 fabric hardware (expansion chassis, switches and host bus adapters) that pool GPUs, memory and NVMe storage outside the server and assign them to bare-metal hosts in software. It also sells validated bundles, SmartStack and UltraStack, built around that hardware.

What is composable infrastructure?

Composable infrastructure separates the expensive devices in a server (GPUs, memory, NVMe, DPUs) from the server itself, puts them in shared pools on a fast fabric, and lets software attach them to whichever host needs them. Instead of buying a server sized for its peak, you buy hosts and pools separately and recompose as demand moves. Liqid calls its version composable disaggregated infrastructure (CDI). For how it differs from blade-frame composability, see our HPE Synergy page.

How many GPUs can one server use with Liqid?

Up to 30. The UltraStack bundles compose 10, 20 or 30 GPUs to a single host server, using one, two or three Liqid 10-slot expansion chassis. Liqid’s Cisco brief applies the same limit to 1U and 2U UCS C-Series servers. See Liqid GPU pooling for the full SmartStack and UltraStack tables.

What is the difference between SmartStack and UltraStack?

UltraStack puts every GPU in the bundle on one host, for scale-up jobs that want 10 to 30 GPUs in a single operating system. SmartStack shares the pool across several hosts: from 10 GPUs and 4 hosts (SmartStack 10) up to 30 GPUs and 16 hosts (SmartStack 30+), so GPUs move between servers as demand shifts. Both run on LIQID Matrix and Liqid’s 10-slot expansion chassis; the current SmartStack is specified with the Gen5 EX-5410P.

Will Liqid work with the servers we already own?

Often, yes. Liqid’s hardware compatibility list (August 2026) includes 21 Dell PowerEdge models, Cisco UCS C-Series, Fsas Technologies PRIMERGY, HPE ProLiant DL380 Gen10, Lenovo SR655 and Supermicro systems, but several entries carry conditions such as a specific riser, BIOS or enclosure generation. Each host needs a Liqid host bus adapter in a free x16 slot: the Gen5 HX-5160P-1C for current bundles, or Liqid’s earlier-generation adapters for older Gen3 and Gen4 hosts on the list. We check your exact models before quoting; see Liqid compatibility.

Which GPUs can be pooled?

PCIe cards up to full-height, full-length, double-wide and 600 W. Liqid’s compatibility list includes NVIDIA H100, H100 NVL, H200 NVL, L40S, L4 and RTX PRO 6000, AMD Instinct MI100 and MI210, and Intel Flex and Max GPUs, among others. The UltraStack MI350P system uses AMD Instinct MI350P. SXM-module GPUs on HGX baseboards are not PCIe cards, so they are not pooled this way.

Is a pooled GPU slower than one inside the server?

A composed GPU sits behind Liqid’s switch silicon rather than on the motherboard. Liqid rates each switch port at 115 ns, its Abaco brief puts the chassis path at roughly 500 ns, and each host link is PCIe Gen5 x16 at up to 128 GB/s. Liqid supports direct GPU-to-GPU (peer-to-peer) traffic inside the fabric. In our view that overhead matters least for inference, VDI and rendering, where each GPU largely works on its own. For one large training job spread across many tightly coupled GPUs, compare against an NVLink system such as NVIDIA DGX before you decide.

Does Liqid work with VMware, Kubernetes and Slurm?

Liqid lists native compatibility with Kubernetes, Slurm, OpenShift, VMware and Ansible, plus its own UI, CLI and REST API. Its Cisco brief adds that composed GPUs appear to Windows, Linux and VMware/Nutanix as local bare-metal devices. See LIQID Matrix software.

Can Servnet supply Liqid in the UK?

Yes. We can supply and quote Liqid systems for UK organisations, together with the host servers, GPUs, networking and rack power around them, and we check every build against Liqid’s current compatibility list first. Use the quote form on this page or contact us.

Keep exploring

Related Servnet guides, tools and hardware

Sources

Every specification on this page comes from Liqid's own product pages and datasheets, listed below with their dates. Where Liqid's web copy and a datasheet differ, we use the datasheet. Figures are confirmed against the current revision when we quote.

  1. LIQID GPU Pooling Solutions · web page, read 29 Oct 2026
  2. LIQID Memory Pooling Solutions · web page, read 29 Oct 2026
  3. EX-5410P SmartStack datasheet (GPU) · dated 10 Dec 2025
  4. EX-5410C SmartStack datasheet (CXL memory) · dated 10 Dec 2025
  5. SmartStack MX datasheet (Dell PowerEdge MX) · dated 12 Sep 2024
  6. EX-5410P PCIe Gen5 expansion chassis datasheet · dated 11 Dec 2025
  7. EX-5410C CXL 2.0 expansion chassis datasheet · dated 11 Dec 2025
  8. HX-5160P-1C PCIe Gen5 HBA datasheet · dated 27 Oct 2025
  9. FX-5016-2 PCIe Gen5 fabric switch datasheet · dated 26 Aug 2026
  10. Liqid Matrix CDI datasheet · dated 2 Nov 2023
  11. UltraStack with AMD MI350P datasheet · dated 13 Oct 2026
  12. LQD4500 IO Accelerator datasheet · dated 14 Apr 2025
  13. Cisco UCS C-Series with high-power GPUs (tech brief) · Nov 2025
  14. Liqid Hardware Compatibility List · dated 17 Aug 2026
  15. What Is Abaco? Liqid technical brief · Aug 2026
  16. Liqid support information · updated 10 Oct 2024
  17. About Liqid · web page, read 29 Oct 2026

LIQID, LIQID Matrix, SmartStack and UltraStack are trademarks of Liqid Inc. Servnet is an independent UK IT reseller; this page is our own guide to the range.

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