Rent an RTX 5070
NVIDIA GeForce RTX 5070
Blackwell mid-range GPU with 12GB GDDR7 for AI inference and gaming.
Specifications
Best for
Renting a RTX 5070
Rent an RTX 5070 by the minute
The RTX 5070 is a fast card with a small memory: 12 GB of GDDR7 on the current Blackwell generation. It is quicker than an RTX 5060 Ti and holds less, so it suits work that fits comfortably in 10 GB and wants to finish soon. On ParalonCloud you rent the whole machine it sits in and pay for the minutes it runs.
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 5070 listed here has been benchmarked by us before it is offered. The one we have verified measured 580 GB/s of memory bandwidth and 21.2 TFLOPS in FP32, and each machine's own result is on its page.
What fits
What fits in 12 GB
Twelve gigabytes is where you have to count. The figure that matters is not the 12 on the box but what is left once the driver and the desktop have taken their share.
Measured
Verified on an RTX 5070 on this network
These are the results of our verification job on a provider's machine with two RTX 5070s (Core i7-14700K, native Linux, power limit 175 W per card), run before it was listed. We have not yet published language-model throughput for this card, so there is no tokens-per-second figure here.
Steps
How to rent one
- 01
Pick a machine
Open the rent page and filter for RTX 5070. 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 5070
RTX 5070 or RTX 5060 Ti 16 GB: which should I rent?
The RTX 5070 is the faster of the two and the RTX 5060 Ti has more memory. On our verification runs the RTX 5070 measured 580 GB/s of memory bandwidth and 58 TFLOPS in FP16, the RTX 5060 Tis 291 to 385 GB/s and 39 to 50. If your job fits in 10 GB, the RTX 5070 finishes sooner. If it needs 13, only the RTX 5060 Ti runs it.
Is 12 GB enough to run an LLM?
For a 4B model at 4-bit, yes: our own serving rule asks for 8,000 MB and a verification run could allocate 10,224 MB on this card. Not for the 27B class, whose weights alone are 18.7 GB.
Do two RTX 5070s act as one 24 GB card?
No. They are two separate 12 GB cards. Frameworks that can split a model across cards will use both, but a model that needs 18 GB in one piece does not load.
How do I know the card is really an RTX 5070?
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 5070?
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.