I'd offer one riff further on all that: indeed, core languages do continue to influence speed on a scale that implementation details can only batter at the edge

I'd offer one riff further on all that: indeed, core languages do continue to influence speed on a scale that implementation details can only batter at the edges of. In Ruby's case, ObjectSpace is worth taking a peek at for an example: http://ruby-doc.org/core-2.3.0/ObjectSpace.html http://ruby-doc.org/core-2.3.0/ObjectSpace.html We have here a method that counts all objects, by type, in the entire heap. How, exactly, could one propose to parallelize that? Not Easily. Does that leak synchronization needs -- and thus performance implications -- into every layer of GC, scheduling, class/module definition loading, and so on? Yup. Doesn't matter how much you approach the pinnacle of excellence in JIT. Some definitions of operational parameters are just going to be expensive. Other languages that simply don't allow such operations are at a permanent advantage. There is no such thing as engineering without tradeoffs.