Actually it looks like that might not be the case - see this post if you’re interested: https://blog.coiled.io/blog/burstable-vs-nonburstable.html

“Coiled runs a suite of Python/Dask benchmarks on AWS. This collection of ~100 benchmarks cover common data science, data engineering, and machine learning workloads. A typical run takes around 150 instance-hours (though as we’ll see, this depends on the choice of instance type). When we switched from burstable to non-burstable instance types, we saw a significant reduction in cost. For instance, comparing two individual runs, we saw costs go from $7.13 (burstable) to $3.89 (non-burstable).”

but it’s probably workload-specific. spot + check pointing will still give you good savings though, assuming you can do it correctly

We are an orchestrator so we benchmark number of tasks and workflows

Or am I missing something?