Rent an RTX 5090
NVIDIA GeForce RTX 5090
The most powerful consumer GPU with 32GB GDDR7 and Blackwell architecture.
Specifications
Best for
Renting a RTX 5090
Rent an RTX 5090 by the minute
The RTX 5090 has 32 GB of GDDR7 and the highest memory bandwidth of any consumer card. For model serving that second number matters more than the first: generating a token means reading the weights once, so a card that moves memory faster makes tokens faster. The extra 8 GB over an RTX 4090 goes to context.
On ParalonCloud you rent the whole machine with the card in it and pay for the minutes it runs. A rental opens as Jupyter Lab in your browser, with a terminal, in under a minute. The rate you see when you start is locked for the session, and there is no contract or minimum spend.
Not every RTX 5090 performs like one. Between hosts we have measured the same card at anything from 245 GB/s to 1,534 GB/s of memory bandwidth, depending on the machine around it. That is why each one is benchmarked before it is listed, and why the result is on its page before you pay.
What fits
What 32 GB buys over 24 GB
A 27B model at 4-bit loads on a 24 GB card with little to spare. On 32 GB the same weights leave room to batch and to hold long prompts.
Measured
Measured on RTX 5090s on this network
Our own measurements, each with the article it comes from. The first two rows are the same card on the same day: the difference is configuration, which is the point of the article.
Steps
How to rent one
- 01
Pick a machine
Open the rent page and filter for RTX 5090. Compare the measured memory bandwidth first: it is the best single sign of how the card will perform on that host.
- 02
Start the rental
Choose Jupyter Lab, accept the terms and start. You need credits for one hour to open a session and are charged only for the minutes you use.
- 03
Work, then stop
Use the terminal for pip, conda or apt, run your job, download what you want to keep, and stop. Or script it with the rental API.
Limits
Know before you rent
- A rental is an unprivileged container: Docker inside it does not work. Install what you need with pip, conda or apt.
- Access is through Jupyter Lab and its terminal. Other ports are not exposed to the internet.
- Everything on the machine is wiped when the rental ends. Download results before you stop, and checkpoint long jobs.
- RTX 5090s are in demand and are often all rented. This page shows whether one is free right now.
FAQ
Questions about the RTX 5090
How much does it cost to rent an RTX 5090?
The price at the top of this page comes from the machines available right now, since providers set their own rate. When none is free it shows the list price. You are billed per minute at the rate shown when you start, and that rate is locked for the session.
Is an RTX 5090 worth it over an RTX 4090?
For serving a model near the 24 GB limit, yes. On a 27B model we measured 94.7 tokens per second on one request on a 5090, where a single 4090 gives about 30, because the extra memory lets the faster decoding features run. For work that fits comfortably in 24 GB the gap is smaller and the 4090 is cheaper.
Why do two RTX 5090s perform differently?
The card is one part of the machine. We have measured RTX 5090s from 245 to 1,534 GB/s of memory bandwidth depending on the host: PCIe link, power limit, drivers and whether it runs under WSL2 all matter. Each machine's own measurement is on its page.
How much power does an RTX 5090 draw under load?
Serving a 27B model at 16 concurrent long generations, we measured 534 W on average and 553 W at peak for the GPU alone. That matters if you are comparing renting with running your own.
Do I get SSH or root on the host?
You get Jupyter Lab with a terminal inside an unprivileged container. You can install packages with pip, conda or apt and use the whole GPU, but you cannot run Docker or open other ports.
Can I rent one from code?
Yes. The rental API lists available GPUs with prices and starts, inspects and stops rentals with an API key.