Actually, Google created a bigger model than GPT-3 and models in the GPT-3.5 series, and consequently ChatGPT too (because ChatGPT is based on a GPT-3.5 model) - Switch-C has trillions of parameters, one order of magnitude bigger than the GPT models that I know of, and it was developed before ChatGPT was announced. I don't know how many parameters ChatGPT has exactly, but it shouldn't have more than several billions of parameters.
So, what makes reproducing a model like ChatGPT difficult for companies like Google? Definitely, not the lack of computational resources or money, but the lack of transparency. My impression is that Google also tends to be open-source, as opposed to OpenAI, which wants to make money of everything.
Moreover, I'd like to note that the GPT models have received a lot of hype, but there are other pre-trained models (e.g. Lambda or Switch-C), for example, developed by Google, that maybe should also have our attention. Google simply doesn't need to generate all this hype to get the money, as they still get most of their revenue from ads (the last time I checked)