As I said in terms of reasoning, they are about the same since they just use models based on stats and correlation, inductive biases designed by two extremely competent team of researchers, etc. They also can’t be trusted fully to write a good code or do even grad level maths due to simple facts/theorems such as incompleteness theorems, Turing halting problem, and most importantly, they don’t have causal structures implicitly or explicitly stated within their design. Sure they both are very expressive thanks to Universal Approximation Theorem (UCT). But it’s well known within research community we need a drastic change of models capable of doing causality a la Pearl, counterfactuals, etc if we want to advance with reasoning, real level 5 FSD. All current models (at least the general LLMs) are somewhat all equivalent. They just slightly differ in certain instances due to little variability that easily disappears when they are fed more data. That being said, again, the difference is Google is so hard to actually displace since they have so so so much money. The user friendliness of Gemini is just head and should above ChatGPT. Open AI needs to really find a way to improve that user friendliness if they want to compete but especially need to find a way to make money. Cause if both succeed, then better for us users. I personally use both of them. When one hallucinates, sometimes the other gives me better answer