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Cost guide · 6 min read

When monthly rental beats per-hour.

Per-hour pricing is the right answer for a job that finishes today. It becomes the wrong answer sooner than most people expect — and the break-even is arithmetic, not opinion.

The short answer

Our monthly price
$1,469 for a NVIDIA H100 PCIe — $2.01 an hour if you divide it out
The break-even
Against a $2.99/hour cloud, monthly wins past 492 hours — about 20 days
The real question
Not "how many hours will I compute" but "how many hours will the machine exist"
Where hourly wins
A job that finishes today, or a load that is genuinely bursty and can tolerate eviction

The break-even

One NVIDIA H100 PCIe, at our monthly price of $1,469, against three ways of renting the same card by the hour. The break-even is the point where the meter has cost you what a whole month costs us.

Hours until a monthly term is cheaper than hourly billing
Hourly option Per hour A full month Break-even You save at 24/7
Hyperscaler, on demandCommitted-use discounts need a year and a contract $6.98 $5,095730 hours 211 h9 days $3,626every month
Specialist GPU cloudPer-second billing, no commitment $2.99 $2,183730 hours 492 h21 days $714every month
Marketplace, community tierSomeone else's machine, interruptible $1.89 $1,380730 hours 778 h32 days Hourly is cheaper
Our monthly termDedicated, no meter, no eviction $2.01derived, not billed $1,469

Hourly figures are public list prices for the same card, observed in August 2026. We do not bill by the hour; the per-hour figure on our own row is the monthly price divided by 730, shown only so the columns can be compared.

The arithmetic

Three lines, and worth writing out because the second one is where most estimates go wrong.

Break-even, in hours
break_even_hours = monthly_price / hourly_price

# For this card, against a $2.99/hour cloud:
$1,469 / $2.99 = 492 hours = 20.5 days

# The mistake: counting only the hours you compute.
# The meter runs while the machine exists, not while it works.
hours_billed = hours_the_instance_is_running   # not hours of useful work

A month is 730 hours. If your machine needs to exist for more than about 20 days out of thirty, a monthly term is cheaper — and every hour past that point is pure saving.

What an hourly price hides

The published rate is the part you can compare. These three are the part you cannot, and together they usually matter more than the rate itself.

Storage that bills separately

On most hourly platforms the disk is a separate line item, charged per GB per month, and it keeps charging while the instance is stopped. A 2 TB dataset can quietly cost more than the GPU on a lightly used month.

Here: 2 × 2 TB NVMe is in the price, and nothing is metered.

Egress

Getting your model weights, checkpoints or generated output out is charged per gigabyte almost everywhere. It is the cost that only appears once the work succeeds.

Here: 1 Gbit/s, unmetered, both directions, no overage at any volume.

Cold start and eviction

Pulling a 140 GB model onto a fresh instance is fifteen to forty minutes you pay for and get nothing from. On interruptible tiers you pay it again every time you are evicted mid-run.

Here: the machine is yours for the term. Weights are on its disks and stay there.

The idle-time trap

This is the one that turns a careful estimate into a bill three times larger. Per-second billing feels safe because you can stop the instance — and almost nobody does, because stopping it means losing the state on it.

Monthly cost at different levels of actual utilisation, hourly versus monthly
The machine runsHoursAt $2.99/hOur monthlyCheaper
A few hours a week 12 h $36 $1,469 Hourly, by $1,433
Working hours, weekdays 176 h $526 $1,469 Hourly, by $943
Every day, working hours 240 h $718 $1,469 Hourly, by $751
Continuously 730 h $2,183 $1,469 Monthly, by $714

Read the second row carefully. "Working hours, weekdays" sounds modest and is already the wrong side of the line — and it assumes you diligently stop the instance every evening, which requires that nothing you care about lives on it.

Ask the honest question. Not "how many hours will I use the GPU" but "how many hours will this machine need to exist". An endpoint that answers requests, a model you are iterating on, a dataset you do not want to re-download — all of those need the machine to exist continuously, whatever the utilisation graph says.

Longer terms

If the answer is "for a year", the monthly price is not the best one available either. The same card on our three terms:

The same configuration on each term
TermPer monthPaid up frontSaved over a yearTrade
Monthlymonthly billing, cancel any time $1,469 $1,469 None. Cancel before the renewal date and it simply stops.
3 months3-month term, 5% off every month $1,396 $4,188 $876 Paid up front, not refunded pro rata. That is what the discount buys.
12 months12-month term, 12% off every month $1,293 $15,516 $2,112 Paid up front, not refunded pro rata. That is what the discount buys.

When hourly really is right

We do not sell hourly, so take this as what it is: the cases where you should go elsewhere.

A job that finishes today. One fine-tune, one benchmark, one render. Rent it by the hour, pay for four hours, be done.

Genuinely bursty load that tolerates eviction. If your work checkpoints cleanly and can be killed mid-run, interruptible capacity is dramatically cheaper than anything dedicated.

You need eight cards for six hours, once. A monthly term on an eight-GPU node to run one experiment is the wrong shape of purchase.

You do not know yet. Rent by the hour until the utilisation graph tells you what you actually need, then come back with a number.

Everywhere else — an endpoint that has to answer, a model you are living with for a quarter, a card you want to leave loaded — a month costs less than the meter and behaves better. And unlike a committed-use discount, a monthly term here needs no contract, no company, and no identity check: it is one payment and the machine is yours.

Every price in the catalogue is a monthly price.

No meter, no egress charge, no storage line item, and no setup fee to add to it.

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