Deploy a model you trained or licensed on dedicated GPUs, and call it with the same key, routes and request shape as the catalogue. You choose the hardware and how far it scales; we run it, keep it healthy and show you what it is doing.
01/Bring your model
Point Fluxion at a Hugging Face repository, a container image of your own, or a model you fine-tuned here. We pull the weights, build the serving image and run a health check before any request reaches it.
02/Choose hardware
Pick a GPU type and how many each replica gets, then set the fewest and the most replicas to run. The deployment adds replicas when requests start to queue and removes them when traffic falls, down to zero when nothing is running, if you allow it.
03/One API
A deployment is a model id on your account, served from the same endpoint as the catalogue. Your application keeps its key, its routes and its polling code; moving a request between a catalogue model and your own is a change to one field. Only your account's keys can call it.
04/Monitor
Each deployment has a page of its own: requests and failures, replicas as they come and go, the GPU time used, and the logs from every replica in one stream. Usage lands on the same bill as the rest of your account, in dollars.
Tell us about the model you want to run and the traffic you expect, and we will get you set up.
Requests go to hello@fluxion-sys.ai. In the meantime, every model in the catalogue is available today.