What are the main disadvantages of Keras for building neural networks?

The disadvantages of using Keras for building neural networks include limited flexibility compared with low-level frameworks such as TensorFlow or PyTorch, making complex custom architectures difficult to implement. Keras’s abstraction can obscure important implementation details, limiting fine-grained control for advanced users. Additionally, Keras relies largely on TensorFlow as its backend, reducing its capability as a standalone platform.