Together AI vs Aquanode
Inference and fine-tuning APIs plus on-demand GPU clusters
Together AI is primarily a model platform — inference endpoints and fine-tuning on open models — with GPU clusters alongside. If you want to call a model rather than administer a machine, they are the better answer and we are not competing for that.
Where Together AI wins
- Managed inference and fine-tuning APIs for open models, with no machine to run at all.
- Large on-demand clusters with modern interconnect for serious training runs.
Where Aquanode wins
- Your environment survives the box. Pause a deployment, come back tomorrow, resume with packages, model weights and config intact — instead of rebuilding from a fresh image every session.
- A snapshot taken on one provider restores onto another. Supply moved, price moved, or a region ran dry — the environment follows, rather than being stranded in the account that created it.
- One account across every provider we broker, so you are not maintaining separate logins, keys and billing per vendor to chase capacity.
- Automated backups are on by default when you attach storage at deploy time, at a 6-hour interval — you do not have to remember to configure them.
Together AI pricing vs Aquanode
Together AI figures are On-demand GPU clusters, per GPU per hour, read from their own pricing page on 2026-08-05. The Aquanode column is the lowest live per-GPU rate in our marketplace feed and moves on its own — the two columns are not measured the same way, so treat this as a starting point, not a quote.
Source: https://www.together.ai/pricing — On-demand GPU clusters, per GPU per hour. Verified 2026-08-05. Vendors change prices; check theirs before deciding.
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.
Together AI vs Aquanode: common questions
Do I need a GPU box if Together AI hosts the model?
If a hosted endpoint covers your use case, no — use the endpoint. You need a box when the environment itself is the work: custom nodes, patched libraries, your own tooling on top.
