GPU rental for Stable Diffusion and generative models
Generative image models are unevenly demanding: basic SD 1.5 generation runs even on a consumer card, while Flux, LoRA training and video generation hit a video memory ceiling that a home machine simply does not have. Buying a card for a few projects a month does not pay off, and waiting a minute per frame wastes time.
QuData gives access to RTX 4090, A10, L40S and A100 for as long as the work lasts. ComfyUI, Automatic1111 and Fooocus deploy from ready-made images and open via a link from your account — nothing to install, the interface is available right in the browser. Finished the batch — stop the instance.
Ready-made images
Assembling an environment for generative models means Python versions, extension dependencies and conflicts between them. We maintain ready-made images that start in about 30 seconds and open in the browser.
ComfyUI
A node-based interface for complex pipelines: model chains, ControlNet, upscaling and post-processing in a single graph.Automatic1111
The classic web interface with broad extension support. The familiar choice if you already have a tuned setup.Fooocus
A simplified interface for fast generation without diving into sampler parameters.Kohya
An environment for training LoRA on your own dataset.Who it suits
Designers and illustrators
Work through a series of concepts for a project when the generation volume exceeds what your workstation can handle, then return to regular tasks without an idle card.Marketing agencies
Deliver a campaign with a large volume of visuals on a tight deadline by spinning up several instances in parallel.Content creators
Train a LoRA on your own style or character and get a recognizable visual identity across all materials.Developers of generative services
Load-test and pick a configuration before committing to permanently rented capacity.How to choose a graphics card for Stable Diffusion
The requirements of generative image models have grown by an order of magnitude in a couple of years. A card that was enough for SD 1.5 no longer copes with Flux and video generation — and it is almost always about video memory, not chip speed.
How much video memory different models need
SD 1.5 runs on 8 GB and works comfortably on 12. SDXL already requires 12–16 GB, and with ControlNet and several extensions it approaches 24. Flux in full precision asks for 24 GB and up, and that is the line where consumer cards end. Video generation models start at 48 GB and above.
LoRA training is a separate story. For SDXL the comfortable minimum is 24 GB, for Flux 48 GB. Less memory works too, but only through aggressive optimization that slows the process several times over, and on a rented card that saving usually turns out to be false economy.
Generation speed and how to measure it
Generation performance is measured in iterations per second. The figure depends on resolution, the number of sampler steps and the model itself, so comparing cards only makes sense at identical settings. A practical benchmark: moving from a previous-generation card to a current one gives a 1.5–2x speed-up at the same memory size.
If you generate in batches rather than one image at a time, what matters is not single-iteration speed but how many frames fit into the batch. Memory size wins again here.
When renting beats buying
Do the math on utilization. If the card works a few hours a week on projects, renting is cheaper than buying over a horizon of several years — bearing in mind that in two years models will demand more memory while a purchased card will not grow. If generation runs continuously and forms the core of your production process, owning hardware is justified.
A separate argument for renting is access to cards that make no sense to buy for personal use. Training a LoRA on an A100 once a quarter is a rational scenario; buying an A100 for that is not.
What to do with the results
The instance lives until the end of the session, so plan the export of generated files in advance. Set up saving to cloud storage or download in a batch before stopping — data cannot be recovered once the rental ends.
Frequently asked questions
Which graphics card do I need for Stable Diffusion?
For SD 1.5 and SDXL a 12–24 GB card such as the RTX 4090 is enough. For Flux and LoRA training, 48 GB and above is more comfortable — A10, L40S or A100.
Can I run ComfyUI or Automatic1111 without installing anything?
Yes, both interfaces are available as ready-made images: the instance starts in 30 seconds and access opens via a link from your account.
How much does image generation cost?
With per-minute billing the cost is set by instance runtime: an hour on an RTX 4090 produces hundreds of images. The current hourly price for each card is shown in the marketplace.
Can I train my own LoRA model?
Yes, a Kohya image is available for that. Training a LoRA on a small dataset usually takes from 30 minutes to a few hours.
Is renting suitable for video generation?
Yes, video generation models are more demanding on video memory — we recommend cards from 48 GB, which are available in the marketplace.