The H100 is a great GPU. It is also one of the fastest ways to waste money on a workload that would run just fine on a 4090 or A100.
A lot of teams default to the H100 because it feels like the safe option. But safe and sensible are not the same thing.
Where teams go wrong
They usually make one of these mistakes:
- optimizing for the most famous GPU instead of the best fit
- skipping the VRAM check
- paying for throughput they do not actually use
A better starting rule
- Start with RTX 4090 for smaller experiments and fine-tunes
- Move to A100 80GB when you need more VRAM or heavier inference
- Use H100 when you already know exactly why the extra throughput matters
The 3 questions that save money
Before renting an H100, ask:
- Does this workload actually need H100-level VRAM or throughput?
- Will a faster GPU reduce total job cost enough to justify the rate?
- Am I still experimenting, or am I optimizing a production workflow?
If you are still experimenting, you probably should not start with an H100.
Compare the right GPUs first:
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