On-demand AI compute

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Spin up GPU clusters for training and inference.
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Pay-as-you-go compute

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Pay only for the cluster time you use.
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Low-cost GPU clusters

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Aggregated GPU compute below mainstream cloud rates.
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Saving on io.net

By pooling GPUs from many sources, io.net can undercut the big clouds on raw compute. Matching the cluster size to your job is how you keep that saving.

How to keep it cheap

  1. Size the cluster to the workload rather than over provisioning.
  2. Use on demand for bursty training runs.
  3. Release clusters as soon as a job finishes.

Worth knowing

This is a newer, decentralised platform, so expect a different workflow to a mainstream cloud. For GPU heavy AI work where cost matters, the savings can be substantial once you are set up.