Comment by m0zg

EfficientNet is extremely difficult to train: it took people months to replicate even a subset of original results from the paper, and for larger configs IIRC the results still haven't been replicated, same with EfficientDet - the detection model that uses EfficientNet as a backbone. It's also not so much faster to run on e.g. NVIDIA GPUs, where much lower GFLOPs don't necessarily translate into much lower milliseconds due to EfficientNet having _a ton_ more ops in the graph, and those ops being "small" and unable to take advantage of all the throughput. Indeed, some configs are slower than comparably accurate alternatives. TL;DR: just because Google is able to get sexy results out of this doesn't mean there aren't better options available to you to solve practical tasks.