This is a great example of why smaller models shouldn’t be overlooked. Testing 15 different decision models for AWS incident triage makes the comparison much more meaningful than simply assuming a larger model will always perform better.

I found the trade-off between accuracy, speed, and cost particularly interesting. For incident response, where decisions often need to be made quickly and repeatedly, a smaller model that performs well enough could be a very practical choice.

It also raises a good question about where different models actually belong in an AI infrastructure stack. Sometimes the best solution may not be the most powerful model, but the one that fits the job.