The thing that made gotoBLAS good was the hand-tuned assembly kernels, so we can be reasonably sure that MKL has hand tuned assembly kernels at this point.
I think the tongue-in-cheek comment is actually really good. It is a reminder that BLAS is more like a linear algebra API than a particular library.
Reference BLAS is of course Fortran but nobody would actually use it. Some other good BLAS are (in order of historical to cutting edge), ATLAS, OpenBLAS, and then BLIS. They all mostly use C and assembly.
BLIS makes a good BLAS. It almost keeps up with MKL, according to the nice plots on their GitHub.
https://github.com/flame/blis/blob/master/docs/Performance.m...
They use C mostly, because the magic is in the GEMM (and possibly TRSM) kernels, which you are going to write in assembly anyway.
Intel also released oneDNN open source, which has an awful lot of BLAS-like functionality. No Fortran in there.
MKL is older than all these libraries of course (maybe not ATLAS, I’m not sure actually), and has a lot of other functionality (sparse stuff, FFTs), so I’m sure it has more Fortran! But it would be atypical compared to the rest of the BLAS implementations, if, like, their DGEMM was Fortran.
The reply about cuBLAS was tongue in cheek as it is a GPU BLAS library