Optimizing Data Transfer Costs Simplifies | Generated by AI
Yes, moving data across regions costs time (network transfer). DO doesn’t have a “hyper link” between regions — it goes over public internet, roughly 100-500 Mbps, so 100 GB = ~30 min to a few hours.
But honestly, the simplest approach: just recreate the GPU droplet when ready, download and prep data directly on it. Data download + tokenization for GPT-2 training data is maybe 1-2 hours of GPU time = ~$4-8. Not worth optimizing around.
The real cost is idle time, not compute time.
Here’s the math:
| Approach | Cost |
|---|---|
| GPU droplet idle for 1 week while prepping data on CPU | $336 GPU idle + $16 CPU |
| GPU droplet on for 2 hrs to download + tokenize, then train | $4-8 for prep + training cost |
Recommendation: Keep things simple.
- Delete the atl1 volume ($10/mo saved) — you have no data on it
- Delete all snapshots except
gpu-mi300x-snapshot-20260601($7/mo saved) - When ready to train: recreate GPU droplet from snapshot, download data from HuggingFace, tokenize, train
- Total idle cost: ~$1.53/mo (just the snapshot)
Want me to clean up and go this route?