That very much depends on the size of the model, batch size, the sequence length you want/expect to generate and on your available resources.
I was trying to do without cache with a GPT2 the other day and had issues quite soon. Longer sequences took way too long: I guess already with batch size 8, sequence length 30, GPT2-base model it started to get really slow on my local machine. It depends also if you want to decode a lot of sequences at once etc. Just for trying a few example, you might be okay without the cache.
I would recommend reading this blog about cache 8 to understand the concept and then check the code of GPT-2 to see how it is implemented.