Comparison with transfer learning and CNN from scratch on a small dataset
They have better performance for now.

If you continued to re-train your pre-trained NN you would spezialise more and more for your dataset at hand and converge to 89%.

But here is the kicker, if you used some pre-trained models for example based ImageNet dataset you would be able to generalise a lot more better. In other words for any images in the test data that were different from the ones in the train (or from the holdout/new set) you would perform better with the transfer learning.