You can count on ChatGPT to know the exact versions and release dates of software just the same as you can rely on your friendly neighborhood dev to know it off the top of their head - not at all. A dev would likely have to look it up too. A language model would also need to look it up through function calling (or just including in your prompt).

This kind of scenario, where there are concrete answers in some datastore somewhere and the relevance of the content that the model was trained on varies chronologically (a blog post on the latest version of React circa 2015 could deliver a wrong answer), are the ones you want to engineer around. This is where you start using SDKs and binding tools to your LLM so you can ensure grounding context is available to generate correct answers.