Renting a 5090 Costs 69 Cents an Hour. We Ran the Break-Even on Buying.

A post went up on r/LocalLLaMA yesterday from somebody who got tired of confident opinions and published their working on buying versus renting an eight GPU HGX H200 server. Their numbers: roughly $320k to $420k to buy, and a median on demand rate of about $4.40 per GPU hour across 34 providers as of 18 September.

That is a company decision and most people reading this are not making it. So we ran the same arithmetic for one consumer card, because the inputs have changed enough in the last year that the old answer no longer holds.

The two prices

An RTX 5090 launched at $1,999. Today it is tracked at $6,795, which price trackers put at 240 percent above that launch price, and the wider range reported across retailers runs from about $4,300 in store to $9,500 from third party sellers. Official retailers are largely out of stock. We did not buy one to check, so treat those as reported figures rather than a receipt.

Renting the same card is $0.69 an hour on RunPod’s community tier and $0.99 on their secure tier, which is roughly where it was a year ago.

One price moved by a factor of three. The other did not move.

The arithmetic

Owning is not free per hour either. A 5090 under a sustained render pulls around 575 W, and the rest of the machine is doing work too, so call it 10 to 15 cents an hour at the US average electricity rate.

That makes the saving from owning about 55 to 60 cents for every hour you actually render. Divide the purchase price by that and you get the break-even:

Eleven thousand nine hundred hours is 496 days of the card running flat out with no gaps, no sleep and no idle.

We are a heavy user and it still does not pay back

This is where we can put our own numbers in rather than guessing at somebody’s usage.

We measured two longform episodes this month. One cost 5.1 hours of GPU for its rendered beats including the re-rolls. The other cost 9.7 hours. We publish more than most people do, and a generous estimate of our own render load is somewhere between 40 and 120 GPU hours in a month.

Take the middle of that, 80 hours a month, and the cheapest reported card breaks even against rental in about eight years. The tracked price takes twelve. Neither of those is a current card by the time it gets there.

So on cost alone, at today’s prices, renting wins for almost everybody, including us. That is not the conclusion we sat down expecting, and it goes first, before the part where we explain ourselves.

Why we still own one

Three reasons, and only one of them is stubbornness.

You pay for the failures either way, but the meter changes how you work. We wrote last week about rendering 105 clips to use 44. A bit under half of what comes off the card gets used. On hardware you own, the other half costs electricity and patience. On a rented hour it costs money, and the thing that actually happens is that you stop trying the third idea. Our whole method depends on generating more than we need and choosing afterwards, and that method gets quietly expensive when it is metered.

The hourly rate is not the whole bill. A working video setup is tens of gigabytes of checkpoints, LoRAs and node packs. Every rented session either rebuilds that or pays storage to keep it warm, and you pay wall clock for the model loading as well as the rendering. Our own numbers from that same piece include queue and load time for exactly this reason. Nobody quotes that in the per hour price.

Some files should not leave the building. Our trained identity weights are the one thing here we could not remake, and they stay on a machine we control. That is a preference rather than a rule, but it is the sort of preference that decides a purchase.

None of those three are savings. They are things we are buying with the difference, which is a different sentence from the one most hardware advice ends on.

How to actually decide

If your work is occasional and bursty, a weekend project every few weeks, rent. The arithmetic is not close and it has not been close for a while.

If you experiment constantly, if the value is in trying things that do not work, own the card and stop doing the sum. You are buying the freedom to waste it.

And if you already have a capable card, none of this applies to you at all. You bought yours before the market did this. The correct move is to use it, and to notice that the thing sitting in your machine is now worth two to three times what you paid.

We earn a referral commission on both sides of this question, from a retailer and from a GPU host, which is exactly why the arithmetic above is laid out for you to check rather than summarised. Our disclosure page lists every relationship.

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