It is hard to predict how Gurobi performs on a certain machine. In general, the solver benefits from high CPU speeds and low-latency, high-bandwidth memory. You can consult this benchmark to compare different CPUs with respect to single-thread performance.
Having multiple cores at your disposal can improve performance quite a lot but is also highly problem-dependent.
The same holds for the amount of memory (RAM). You should ensure that the model can be solved without exceeding physical memory. Otherwise, this will have a strong negative performance impact. Even smaller models can require a lot of memory because of a large MIP tree. In such cases, it can help to use the NodeFileStart parameter to write compressed node information to disk and free some memory. More channels, e.g. DDR4, increase the data throughput and should be preferred over single-channel RAM. Memory benchmarks can be found here.
Whenever possible, we recommend performing actual testing to determine real-world performance.
A general guideline: if you are solving a large MIP in parallel, it is best to use a system with the fastest possible clock rate, using the fastest available memory, with as many fully-populated memory channels as are available. Current Intel Xeon systems support up to six channels per CPU, while current AMD EPYC systems support up to eight. Desktop and low-end server configurations typically have a lot fewer channels.