Actually, going from 91.3% to 94.5% is a significant jump, because it means the model has gotten a lot better at solving the hardest problems thrown at it. This has downstream effects as well: it means that during long implementation tasks, instead of getting stuck at the most challenging parts and stopping (or going in loops!), it can now get past them to finish the implementation.

We can look at the same numbers in different way:

  Error with 91.3% = 8.7%
  Error with 94.5% = 5.5%

  Error reduction = 8.7% - 5.5% = 3.2%

So the improvement is 3.2% / 8.7% = 36.8%