◈ Compute for the Fortune 500

At your scale, 30%
is not a rounding error.
It is a budget line.

When cloud spend is measured in tens of millions, the gap between the leading cloud’s list price and ours is a programme’s worth of headcount. Compute prices GPU and CPU capacity, managed databases and AI inference under the leading cloud’s own published rates — and the gap scales with you.

Evaluated workload by workload, against your own the leading cloud invoices.

30%
Under the leading cloud on H100 and A100 hours
30%
Under the leading cloud’s model service on general-model tokens
Zero
Multi-year commitments required
Daily
Re-check of our prices against the leading cloud’s
Against the leading cloud

What fortune 500 pay on Compute, against the leading cloud

H100 GPU hour
$4.82/hr
Leading cloud $6.88/hr · Same GPU (H100 80 GB)
30% less
A100 GPU hour
$1.92/hr
Leading cloud $2.74/hr · Same GPU (A100 40 GB)
30% less
General & code model — output
$0.455 / million tokens
Leading cloud $0.65 / million tokens · The same open-weight model, output tokens
30% less
Business support
$70.00 / month
Leading cloud $100 / month · Business support plan, monthly minimum
30% less

Compared with the leading cloud's own published on-demand prices, US East. Every comparison.

Why fortune 500 choose Compute

Built for how you buy

◆

Savings that scale linearly

The saving is on the unit price, so it grows with the workload rather than tapering off behind a negotiated tier.

◇

A second source of capacity

GPU capacity outside your primary cloud, for training runs and inference fleets that should not queue behind someone else’s reservation.

◈

Finance-ready billing

Itemised monthly invoices by product and meter, prepaid credit, and a price list your FinOps team can check against the leading cloud’s themselves.

○

A named engineer

Enterprise support with a named technical account engineer and quarterly architecture and cost reviews.

The shift

From your current cloud bill to the Compute bill

On the leading cloud today
  • ✕Discounts tied to committing spend years in advance
  • ✕GPU capacity rationed by reservation
  • ✕Concentration in a single provider
  • ✕Cost reviews that start from an opaque invoice
  • ✕Leverage only at renewal
On Compute
  • ✓A lower on-demand price with nothing committed
  • ✓GPU hours when the run is ready
  • ✓A credible second hyperscaler in the estate
  • ✓A meter-by-meter bill that reconciles
  • ✓Leverage every month, because you can move a workload any month
How it works

Three steps, no migration project

  1. 1

    Share one month of the leading cloud spend

    We map each line to its Compute equivalent and price it with the same engine that bills you, against the leading cloud’s own figure.

  2. 2

    Prove it on one workload

    Run one production-shaped workload in parallel for a billing cycle and compare invoices.

  3. 3

    Expand by evidence

    Each further workload moves when its own numbers justify it.

Questions we are asked

Answers, plainly

Can you handle our volume?+

Tell us the workload and the capacity it needs, and we will tell you plainly what we can commit to and when. We would rather say no early than late.

Do your prices hold at volume?+

Our prices are set against the leading cloud’s first-tier on-demand rates. The leading cloud lowers some rates at very high volume; we will price any workload against what the leading cloud would actually charge you for it.

What about compliance?+

We do not currently hold third-party attestations such as SOC 2 or ISO 27001. Separation, access records and residency are configured properties of the platform; ask us about your specific obligations.

Do we have to leave the leading cloud?+

No. Most large estates are multi-cloud already. Compute is the provider you move the workloads to where the price difference is largest.

Put one workload on Compute this month

Run it beside what you have, and compare the invoices line by line. Move the next one when the numbers say so.

No contract, no minimum spend, nothing to tear down if you stop.