Together AI Alternatives for Training
Training a model from scratch or continuing a pre-training run, usually for days rather than hours.
What training actually needs
Why people look past Together AI for this
The checkpoint is the cheap part to move; the built environment, the dataset cache and the exact CUDA and framework versions around it are what take a day to rebuild. That is exactly the gap Together AI does not close: 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.
To be fair, Together AI's real strength is real: Managed inference and fine-tuning APIs for open models, with no machine to run at all.
Live rates for the GPUs training wants
Live per-GPU rates from Aquanode's marketplace. Refreshes hourly.
How you run it here today
Run it today as a Pod: the console's own box workload card preselects the right template for this job.
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.
More alternatives pages
Other workloads on Together AI
Training alternatives to other clouds
