GPU rental is not one SKU. The price reflects the GPU family, quantity, duration, storage, network, deployment model, and support scope. We quote the whole configuration, not a headline rate with surprises underneath.
For experiments, burst work, and defined projects that need capacity without a long commitment.
For teams that know the capacity they need and want a stable commercial and deployment window.
For deployments that need a more specific node, network, storage, or operational envelope.
We do not publish a single "from" price because two deployments with the same GPU can carry very different infrastructure and service costs.
The model, memory footprint, and number of GPUs set the base capacity envelope.
Short-notice and longer reservations create different commitments for both sides.
Fabric, bandwidth, capacity, persistence, and data movement can materially change the design.
On-demand, reserved, and dedicated models carry different operational responsibilities.
Your written quote is the source of truth. It should make the deployment boundary visible before anyone starts work.
Tell us the model, GPU count, deployment model, and timeline. We will confirm the right configuration and commercial path.
Request capacity