The work I do could be called data science and data engineering. Outside some fairly trivial (or highly optimized) sequential processing, the CPU just isn't fast enough to saturate memory bandwidth. For anything more complex, the data you want to load is either in cache (and bandwidth doesn't matter) or it isn't (and you probably care more about latency).
After some digging, I've realized that one had 8x8GB ram modules and the slower one had 2x32GB.
I did some benchmarking then and found that it really depends on the workload. The www app was 50% slower. Memcache 400% slower. Blender 5% slower. File compression 20%. Most single-threaded tasks no difference.
The takeaway was that workloads want some bandwidth per core, and shoving more cores into servers doesn't increase performance once you hit memory bandwidth limits.