Rent an RTX 5060
NVIDIA GeForce RTX 5060
Specifications
Renting a RTX 5060
Rent an RTX 5060 by the minute
The RTX 5060 is the smallest card of the current generation: 8 GB of GDDR7. It is the cheapest thing you can rent here that still has this generation's features, and it is for work that is small on purpose: trying a library, a speech or embedding model, a class assignment, a script you want to see run on a GPU before you pay for a large one.
A rental opens as Jupyter Lab in your browser, with a terminal, in under a minute. The hourly rate you see when you start is locked for the whole session, billing stops the minute you stop, and there is no contract or minimum spend.
Every RTX 5060 listed here has been benchmarked by us before it is offered. The one we have verified could allocate 6,318 MB of its 8 GB, and that number, not the 8, is the one to plan around.
What fits
What fits in 8 GB
Less than the box says. On the machine we verified, 1.8 GB of the card was not available to a job at all.
Measured
Verified on an RTX 5060 on this network
These are the results of our verification job on a provider's RTX 5060 (Ryzen 5 5600, a Windows machine running WSL2, power limit 145 W), run before the machine was listed. It is a spot machine: its owner also uses it. We have not published language-model throughput for this card.
Steps
How to rent one
- 01
Pick a machine
Open the rent page and filter for RTX 5060. Each machine shows its measured bandwidth, PCIe link, power limit, CPU, RAM, free disk, location and reliability score.
- 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 drive the whole thing from a script 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.
- A spot machine can be reclaimed with two minutes' notice. Use on demand for work that cannot be interrupted.
FAQ
Questions about the RTX 5060
Is 8 GB enough for AI work?
For small models, yes; for a current language model, mostly no. On the RTX 5060 we verified, a job could allocate 6,318 MB. The RTX 5060 on our network serves a speech-to-text model. A 4B model in bf16 is 7.9 GB and does not fit.
RTX 5060 or RTX 5060 Ti: which should I rent?
If what you run fits in 6 GB, the RTX 5060 is the cheaper card. If it does not, the RTX 5060 Ti with 16 GB could allocate 13,642 MB in the same verification run, more than twice as much.
What does it mean that the machine is spot?
Its owner also uses it. It rents at a discount and can be taken back with two minutes' notice, after which the rental stops and billing ends. It suits jobs that checkpoint, or that are short.
How do I know the card is really an RTX 5060?
Before a machine is listed, a verification job allocates its memory and measures memory bandwidth and compute. The result, and when it was last checked, is on the machine's page.
How much does it cost to rent an RTX 5060?
The current price is shown at the top of this page and comes from the machines available right now, since providers set their own rate. You are billed per minute at the rate shown when you start, and that rate is locked for the session. There is no contract and no minimum beyond having credits for one hour when you open a session.
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. There are also MCP servers for driving it from an AI coding assistant.