GPU Colocation for AI & HPC Workloads (Unlisted Providers)

We know where GPU infrastructure actually exists including providers that don’t publish pricing or even show up in search.

Looking to deploy GPU servers, AI clusters, or HPC workloads? We’ll give you 3-5 qualified facilities with real power availability, pricing, and timelines. Free.

GPU & AI & HPC Colocation Pricing by Market (2026)

Market	GPU Colocation (per kW)	Typical Rack Density	Notes
Northern Virginia (Ashburn)	$180–$300 / kW	10–30 kW	Tight power availability, premium pricing
Dallas / Texas markets	$140–$240 / kW	10–40 kW	Best balance of cost + availability
Chicago	$160–$260 / kW	10–25 kW	Strong carrier-neutral ecosystem
Phoenix / Arizona	$130–$220 / kW	15–40 kW	Popular for AI deployments
Los Angeles	$180–$320 / kW	10–25 kW	Space constrained, high cross-connect costs
Pacific Northwest (OR/WA)	$120–$200 / kW	15–50 kW	Strong for AI + power-heavy workloads
Washington State	$110–$180 / kW	20–50 kW	Cheap hydro power, ideal for AI clusters
North Dakota / South Dakota	$100–$170 / kW	20–60 kW	Lowest cost power, very limited competition
Atlanta	$140–$230 / kW	10–25 kW	Growing secondary hub, good pricing
Denver	$140–$220 / kW	10–30 kW	Central location, improving capacity
New Jersey (NYC metro)	$170–$280 / kW	8–20 kW	Low latency to NYC, expensive power
Silicon Valley / Bay Area	$200–$350 / kW	10–25 kW	Very limited capacity, highest pricing
Salt Lake City	$130–$210 / kW	15–40 kW	Emerging AI-friendly market
Las Vegas	$130–$220 / kW	15–40 kW	Tax advantages + proximity to CA
Columbus / Ohio	$130–$210 / kW	10–30 kW	Cloud adjacency + lower costs
Minneapolis	$140–$220 / kW	10–25 kW	Stable power, under-the-radar market
Montreal / Toronto	$120–$200 / kW	10–30 kW	Lower power costs, strong for AI workloads

*Notes: Actual quotes vary by date and your needs.

The real constraint today is not space. It’s power delivery and cooling capacity.

Price per kW → your real cost driver (not rack price)

Rack density → determines if your GPUs will even be accepted

Notes → where deals actually happen vs where you waste time

What do these prices typically include?

Here’s what is usually included:

Power (committed kW, often billed at 80–100% utilization)
Basic cabinet or cage space
Standard cooling (air or containment)
1–10 Gbps connectivity (sometimes commit-based)

What’s not included (but will show up later):

Cross-connects ($100–$400/month each)
Remote hands ($150–$300/hour)
Installation fees ($500–$3,000+)
Burst bandwidth or overages
High-density cooling upgrades (rear-door HX, liquid-ready)

Real-world difference between “quoted” vs “final” cost:

+20% to +60% depending on networking, support, and term structure

Why Go Through a Broker like Us? (Spoiler: It’s Faster)

Option A: Google/ChatGPT → direct emails

15 tabs, vague “GPU colocation” pages, “schedule call” replies. 100kW min rejections, no pricing transparency. Weeks wasted.

Option B: Provider lists (DatacenterMap/Baxtel)

Outdated inventories, no power avail., sales fishing expeditions. Hidden mid‑tier GPU hosts missing.

Option C: Consultants/RFPs

$10k+ fees for enterprise audits; slow for single‑rack GPU cluster. Overkill for startups.

Option D: QuoteColo broker

Specs once (GPUs, kW, cooling, market). 3–5 vetted GPU colocation providers (incl. unlisted single‑rack OK) with apples‑to‑apples matrix: power model, cooling, 100G, hands rates, lead time. 48hrs, free, 10% savings avg. Most teams waste weeks chasing quotes. You don’t have to!

How It Works

Submit Your Request

Rack kW (5–50), GPUs/model, cooling (air/immersion), network (100G?), market, timeline. E.g., “8x H100, 12kW, Ashburn, liquid‑ready.”

Get Quotes, Fast

Tap 500+ providers (Equinix, QTS, unlisted regionals). Quotes w/ power billing, x‑connects, hands, contracts side‑by‑side.

Choose Your Best Option

Pick, ship gear (we flag pallet/hands). Track install, SLAs. Scale to MW later.

Why Choose Us

Access to 500+ Hosting Colocation Facilities
10% OFF Avg. Annual Savings
Trusted service since 2004

Quotecolo, Llc

4.8

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Get Free Quotes From Providers

Describe your needs and and we’ll email you 3-5 options with pricing and terms from providers that match. Free.

Case studies

Helped 750+ companies in 20+ years

From startups colocating their first servers to companies deploying multi-rack, high-density GPU and AI colocation infrastructure, businesses trust QuoteColo to find the right data center faster.

See how we helped teams secure colocation with the right power, pricing, and providers.

View our case studies

Multiple Location Colocation The Pairing Service

500+ Colocation Providers in Our Network worldwide

From global brands to highly competitive regional datacenters that rarely show up in ChatGPT and Google searches. We help you compare both – and often uncover better pricing and faster availability.

Talk to us to find your best option

Popular Client Requests

“We bought GPUs, now we can’t find space”

1 rack, 12–20kW
8–10 GPU servers
Rejected due to minimum commitments

We found facilities that accept single-rack high-density deployments.

“Can your colo support a fast-scaling AI inference cluster?”

2–4 racks, 30–80kW total, 10–25Gb networking, and tight deployment timelines are well within range. We prioritize facilities that can spin up capacity quickly without bottlenecks. That means you can go from initial racks to production-ready infrastructure fast—without waiting on long provisioning cycles.

“Will I be locked into big-brand providers I don’t need?”

Not at all. We focus on availability and speed, not logos. You’ll get access to high-performance sites that meet your technical requirements without paying a premium for brand-name providers that don’t add value to your workload.

“Can this setup handle enterprise-scale AI and analytics workloads long-term?”

Yes—whether you’re deploying 5–20 racks at 20–40kW per rack or scaling hybrid cloud + private infrastructure, we match you with facilities built for sustained high-density compute. Your infrastructure will be ready for both current demand and future growth.

“How do you ensure power delivery and cost efficiency at scale?”

We prioritize data centers designed for high-density power with predictable pricing. You’ll get stable power delivery for demanding workloads, along with transparent, long-term cost structures—so you can scale without unexpected increases or inefficiencies.

Who Actually Uses GPU & AI Colocation

Data/AI analytics leads: Small clusters (10–100kW/rack) rejected by hyperscalers. Need HD w/o MW mins.

SaaS CTOs: Inference engines (4–8 H100, 4–12kW). Egress kills cloud TCO.

HPC/research: Simulations/weather (8–32 GPUs, 20–40kW). Predictable power > cloud burst.

Fintech/risk modeling: Low‑latency algos (10–20kW). Colo beats VPC noise.

Healthcare/biotech: Genomics/imaging (liquid 30kW+). HIPAA + stable cooling.

Media/rendering: VFX farms (16 GPUs/rack). 100G + peering density.

Autonomous/edge AI: Sensor processing (20kW clusters). Latency < cloud.

Understanding GPU Colocation (What Actually Matters)

Power density is the first constraint

Typical GPU servers:

5–15kW per server
10–40kW per rack (common)
50kW+ for advanced deployments

Many data centers simply cannot support this.

Cooling: air vs liquid

Air cooling works up to ~20–30kW per rack
Rear-door heat exchangers extend that range
Liquid cooling is becoming standard for >40kW

Not all “high-density” facilities are actually ready

Networking expectations

GPU workloads typically require:

10G / 25G / 100G ports
Low-latency interconnects
High burst capacity (data transfer spikes)

Remote hands matters more than you think

GPU environments fail differently than standard servers. You need:

Fast hardware swaps
Cable troubleshooting
On-site diagnostics

Example GPU Deployments

Deployment	GPUs	Power
AI inference server	4–8 GPUs	4–6kW
Training node	8–10 GPUs	8–12kW
Cluster rack	16–32 GPUs	20–40kW

2026 GPU Colocation Market: Power Crunch + AI Boom

Demand exploding: High-Density colo up 80% (AI inference/training); vacancy <1% prime (Ashburn/Dallas). Power availability is now the #1 bottleneck (not space). Many deals happen off-market (brokers, referrals, private networks).

Trends:

Single‑rack GPU OK (no 100kW min) → mid‑tier/regionals (QTS, Flexential).
Liquid/immersion standard >30kW ($1–2k/mo premium).
Cloud repatriation: 40–60% TCO savings vs AWS H100 $3.90/hr.

Pro tip: Spec peak kW + cooling upfront – avoids “qualified but no power” rejections.

Why Most Teams Struggle to Find GPU Colocation

Because they search like this and expect clear answers:

“GPU colocation providers”
“datacenter for GPU servers”

Reality:

Many providers don’t list pricing
Many won’t accept small deployments
Many don’t actually support high-density racks

That’s where we come in.

Why Choose Us

Access to 500+ Hosting Colocation Facilities
10% OFF Avg. Annual Savings
Trusted service since 2004

Quotecolo, Llc

4.8

See All Google Reviews

Get Free Quotes From Providers

Describe your needs and and we’ll email you 3-5 options with pricing and terms from providers that match. Free.

FAQs – GPU & AI & HPC Colocation

Minimums for GPU colocation?

Many Tier I operators (Equinix, Digital Realty) now gate single racks behind 100kW+ commitments or multi-MW contracts, especially in Ashburn/Dallas where power queues stretch 6–12 months. We specialize in mid-tier and regional providers accepting 5–50kW GPU clusters (H100/L40S inference or small training) – facilities like QTS Manassas, Flexential Hillsboro, or unlisted Texas hydro sites that don’t advertise publicly due to capacity limits. No MW minimums, just vetted power availability.

Power: Metered or committed?

Committed kW ($150–$250/mo per kW) is standard for GPU colocation. Locks predictable pricing for steady 5–15kW draws (e.g., 8x H100 = ~12kW peak). Metered adds $0.06–$0.10/kWh over baseline, risky for variable training loads hitting overages. Always spec avg draw (60–70% utilization) + peak; we include both models in quotes with TCO math. A/B 3-phase feeds typical above 10kW.

Liquid cooling everywhere?

Not yet. Air cooling (RDHx/containment) handles 10–30kW reliably (PUE 1.3–1.5). Liquid-to-chip or immersion mandatory above 30kW for H100/A100 training racks (sub-1.2 PUE). Adds $500–$2k/mo (CDU rental + leak sensors); confirm facility manifold readiness and reseat policies. Hybrid air/liquid growing in Dallas/VA.

Lead time for GPU racks?

2–6 weeks for standard air-cooled inference (if power slotted); 3–6 months+ for prime-market liquid (Ashburn power crunch). Regional markets (Richmond, Atlanta, Phoenix) often 4–8 weeks. We track live capacity across 500+ sites – bypass waitlists via unlisted providers motivated for 12–24mo terms.

Remote hands for GPUs?

$3–$5/min (15–30min SLA) covers GPU reseats, cable management, PSU swaps – critical for no-local-staff teams. Basic (reboot/visual) often bundled; advanced requires trained techs (NVIDIA cert ideal). Pallet receiving $200–$500 + rack/stack $1–2k one-time. Specify drive replacement/hot-swap needs upfront.

Cloud vs GPU colo TCO?

GPU colocation wins 40–60% long-term on stable workloads: H100 colo rack ~$2.5–$5k/mo all-in vs AWS P5 $3.90/hr ($7k+/mo at 80% util.) + massive egress. Break-even at 6–9 months; colo crushes on inference/scale-out. Hybrid sweet spot: train cloud, infer colo. We benchmark your AWS bills.

100Gbps+ networking standard?

10Gbps baseline included; 40–100Gbps (Mellanox/NVIDIA BlueField) $500–$2k/mo port + $200–$1k x-connects each. MMR access is critical for InfiniBand/RoCE clusters – demand copper/fiber pricing tiers. Cloud on-ramps (AWS/Azure Direct) extra $1–3k. Unmetered “fair use” rare at scale; 95th percentile common.

Air vs liquid cooling TCO impact?

Air: $0 premium to 25–30kW, simpler ops but caps density (PUE 1.35 avg). Liquid: $1.2–$2.5k/mo add-on, unlocks 60–100kW/rack (PUE <1.2), 20–30% energy savings on 24/7 inference. Long-term: liquid pays back in 12–18mo via power bills. Confirm CDU maintenance SLAs.

Single rack GPU clusters accepted?

70% of facilities now say “no” below 100kW total footprint. We route to the 30% that do (QTS, CoreSite, regional power-rich sites). Perfect for startups/research: 4–16 GPUs, 5–20kW, no MW gates. Includes expansion paths to cages.

Best markets for first-time GPU colo?

Dallas/Phoenix lead on power abundance ($150/kW, solar/hydro); Ashburn/VA for latency/IX (premium $225/kW). Avoid SV/LA unless peering trumps TCO. We match your latency budget to the cheapest viable market.