Wider market
Compare neoclouds, hyperscalers, and specialist GPU providers side by side.
GPU sourcing for AI startups
Find the right GPU
provider for
your workload.
Compare current and next-gen GPUs across neoclouds, hyperscalers, and specialist clouds. Get competing quotes and negotiate a contract that fits how you’ll grow.
Purchase file
01
Requirements64× H100, US East, January start
✓02
Rent vs. ownBreakeven at 68% utilization
✓03
Bids5 requested, 3 tested
✓04
Terms12 months, 15% prepaid, step-down at month 6
✓Sample file
Built for AI teams
buying compute
Credits endingCapacity by a dateContract renewalLarge training runRent or own
Benefits
Why AI teams use us
One team handles the search, the quotes, and the contract.
Comparable quotes
Every quote priced the same way, so you can actually compare them.
Tested before you sign
We test the top options on your real workload before you sign.
Flexible terms
Room to scale down, upgrade, or leave, written into the contract.
The market right now
GPU prices are going up,
not down
Capacity is tight and rates keep climbing, and the contract you sign now could last three years.
~38%
How much AWS has raised reserved GPU prices this year
+40%
Rise in one-year H100 rental rates in just five months
1 in 100+
GPU clouds that earned a top reliability rating
Sources: AWS, Compute Exchange, SemiAnalysis.
Options
Rent, reserve, or own
We model each option against your usage and recommend the right mix.
On-demand reviewInputs
1
GPU and workload fitModel, memory, performance
2
Availability and regionCapacity, location, start date
3
All-in costCompute, storage, egress, support
Sample structure
Rent · on-demand
Pay as you go while demand is uncertain.
Best when usage is spiky or you’re still experimenting. We find the cheapest reliable capacity across neoclouds and hyperscalers.
You receive a shortlist, comparable quotes, and a recommendation.
Process
How it works
Three steps from first quote to running cluster.
Requirements briefAssessment
WorkloadTraining / inference
HardwareGPU, memory, interconnect
CommercialBudget and term
DeliveryRegion and start date
Cost model + decision memo
Sample document
Step 01
Define needs.
Tell us what you’re running and when you need it. We work out what to buy, and whether to rent or own.
Deliverable: requirements brief, cost model, decision memo.
Bid comparisonProcurement
EvaluateProvider AProvider B
Workload testPassPass
All-in costModelModel
TermsReviewReview
Start dateConfirmConfirm
Sample comparison · no live quotes
Step 02Compare and
Compare and
negotiate.
We get quotes from several providers, test the best ones, and negotiate the contract.
Deliverable: bid comparison, test results, negotiated terms.
Deployment planHandover
Confirm the orderScope, contacts, commitments
Track dependenciesCapacity, network, access
Run acceptanceBurn-in and sign-off
Set the renewal reviewUsage against commitment
Sample sequence
Step 03
Go live.
We stay on it until your cluster is running, and check back before renewal.
Deliverable: deployment plan, issue log, renewal date.
What we negotiate
Negotiate smarter
A good rate can still come with a bad contract. Here’s what we fix.
Price
The best rate for the term that actually fits you.
Upfront payment
Pay less upfront, or tie payments to delivery.
Scaling down
Cut back if demand comes in lower than planned.
Upgrades
Switch to newer GPUs mid-contract at a set price.
Extra capacity
A set price for spikes, instead of on-demand rates.
Unused hours
Carry over hours you paid for but didn’t use.
Uptime
A clear uptime promise, and money back when it’s missed.
Testing
The cluster has to pass tests before you start paying.
Leaving
Get your data out cheaply when the term ends.
What you receive
What you get
Everything is written down, so you can reuse it the next time you buy.
Requirements brief
What you need, where, and by when, on one page.
Cost model
What renting vs. owning costs, with the math shown.
Recommendation
What we’d buy, why, and the tradeoffs.
Shortlist
Which providers made the cut, and why.
Quote comparison
Every quote side by side, priced the same way.
Test results
What we tested and how each cluster did.
Negotiation notes
What we asked for, what we got, and what’s still open.
Deployment plan
Who does what, and by when.
Renewal check
What you’re using vs. paying for, before you renew.
Engagements
Ways to work with us
Start with just the advice, or have us handle the whole purchase.
Every fee agreed before we start
Assessment
Figure out
what to buy.
For teams deciding whether to rent, reserve, or buy hardware.
Includes
- Review of your workload and usage
- Rent vs. reserve vs. own costs
- A clear recommendation
Fixed fee
Sourcing
Get the
best deal.
For teams ready to buy. We get the quotes, test the clusters, and negotiate the contract.
Includes
- Quotes from multiple providers
- Clusters tested before you sign
- Contract negotiated for you
- A final recommendation
Project fee (provider fees disclosed)
Launch support
Get it
running.
For teams that want someone tracking delivery after the contract is signed.
Includes
- Delivery tracked until you’re live
- Problems chased with the provider
- Check-ins before renewal
Project fee or monthly retainer
For GPU providers
Partner with us
We connect GPU providers with AI teams that have a spec, a budget, and a start date.
Provider profile
Get matched
with buyers.
Share your GPUs, regions, and terms. We bring you requirements that fit.
Buyer requirementsWorkload and GPU typeRegion and start dateBudget and termProvider fit review
Qualified demand
Every buyer we send has a real spec, budget, and timeline.
Introductions require buyer consent.
Faster evaluations
A shared test plan and one contact on each side.
Provider fees are disclosed to buyers.
FAQ
Common questions
Who is this for?
AI startups about to spend real money on GPUs. We usually work with the founder, CTO, or whoever runs infrastructure.
How is this different from a GPU marketplace?
Marketplaces are great for renting by the hour. We help when you’re signing a longer contract: we get competing quotes, test the clusters, and negotiate the terms.
Should we reserve or stay on-demand?
Reserve once your usage is steady. If your GPUs would sit idle much of the time, on-demand is usually cheaper. We check against your actual usage before you commit.
Should we buy our own GPUs?
Only if they’ll be busy almost all the time and you have people to run them. Otherwise renting is cheaper and less hassle. We’ll run the numbers with you.
We’re already in a contract. Can you help?
Yes. We review what you signed, flag what can change at renewal, and plan your next purchase around it.
How are you paid?
You pay us a set fee, agreed before we start. In some deals the provider also pays us, and we always tell you. Your contract is always directly with the provider.
Get started
Before you sign,
talk to us.
Send us a quote you’re weighing, or tell us what you need. We’ll tell you if it’s a good deal.
Before you sign