Hyperbolic vs Aquanode
Open-model inference plus an on-demand GPU marketplace
Hyperbolic pairs open-model inference with rentable GPU capacity, aimed at developers who want both from one vendor. We do not host open models for you: our jobs run a version of a setup you built yourself, not a catalogue you pick a model from.
Where Hyperbolic wins
- Hosted open-model inference alongside GPU rental, from a single account.
- On-demand, reserved and private-cloud options across one supply base.
Where Aquanode wins
- Your setup outlives the GPU you rented it on. Save the environment (custom nodes, model weights, packages, the config you spent an evening getting right) and bring it back up later on a completely different provider, instead of reinstalling it from scratch every session.
- Supply moved, the price moved, or the region ran dry. Your environment follows you out. It is not stranded in the account that happened to create it, which is the part that makes leaving any single vendor cheap.
- Pause and resume in place on every provider we support: it's a snapshot-and-terminate, then a fresh box restored from that snapshot, the same mechanism everywhere. (Voltage Park's adapter supports it too, it just has no live GPUs to rent right now.) On any provider, the same environment also comes back by restoring your saved setup onto a fresh box, a little slower, same result.
- Turn on automatic snapshots yourself and pick the interval (as often as every 15 minutes, 30 by default) instead of remembering to snapshot by hand or wiring up your own cron job.
- One account, one bill and one set of keys across every provider we support, rather than a separate login and invoice per vendor every time you chase capacity.
- Run a saved version of your setup as a job. If a provider takes the box back mid-run, we detect the loss and queue the run to retry on a different provider, excluding the one that just lost it, and if the job checkpoints the next attempt picks up from the last one. Jobs scale to zero when the queue empties, so an idle one is not sitting on a rented GPU, and every job is bounded in the unit we bill: its time limit times its attempts times its machines is the most a single run can cost.
Hyperbolic pricing
We could not verify a Hyperbolic price first-party, so this page publishes none. As of 2026-09-19 hyperbolic.xyz/pricing redirects to www.hyperbolic.ai/pricing and that path still returns HTTP 404; their homepage states that pricing depends on the compute model chosen but publishes no hourly rate. There is no first-party figure to cite, so we cite none.
Checked https://www.hyperbolic.ai/ on 2026-09-19.
What we do not claim
Restoring an environment requires a snapshot that already exists. Stopping a deployment yourself captures it on the way out, so you can bring it back later on any provider. A provider-side termination is different: it is only recoverable if you had already switched automated snapshots on for that deployment, and it costs you the work since the last one. Automated snapshots are opt-in, nothing runs until you start it, and with none running there is nothing to restore.
`aq deploy --snapshot <id>` rents the cheapest matching GPU and restores your snapshot onto it, including onto a different provider than the one it came from. Creating the snapshot is a separate step today: the standalone ogre CLI on the box writes it.
Hyperbolic vs Aquanode: common questions
Why are there no Hyperbolic prices on this page?
Because we could not find them on Hyperbolic's own site. Every competitor price we publish is read off that vendor's own pricing page and dated; where there is no such page, we say so rather than repeat a number from a third party.
