Hi everyone — I’m a startup founder working on ML-heavy products, and we’re evaluating different cloud GPU providers for both training and inference.
Curious to hear from this community — when you choose a provider, what are the biggest factors that drive your decision? Is it:
- Price
- Queue times / availability
- GPU network latency
- Bundled MLOps features (training pipelines, monitoring, model hosting, etc.)
- Or other factors I should be thinking about?
Would love to learn from your experience as we’re making some decisions on our stack. Thanks in advance!