This is a myth, from the old days when BEAM was the only thing that could juggle thousands of "processes" without losing performance, and even back then, people routinely missed that while BEAM could juggle those thousands of processes, each of them was individually not that fast. That is, BEAM's extremely high performance was only in one isolated thing, not high performance across the board.
Now BEAM is far from the only runtime juggling that many processes, but it remains a relatively slow VM. I rule-of-thumb it at 10x slower than C, making it a medium performance VM at best, and you want to watch your abstraction layers in those nicer languages like Gleam because further multiplicative slow downs can really start to bite.
The first serious Go program I wrote was a replacement for something written in Erlang, there was no significant architectural improvement in the rewrite (it was already reasonably well-architected), and from the first deployment, we went from 4 systems, sometimes struggling with the load spikes, to where just one could handle it all, even with BEAM being over a decade more mature and the Go clustering code being something I wrote over a few weeks rather than battle tested, optimized code.
BEAM is good at managing concurrency, but it is slowish in other ways. It's better than the dynamic scripting languages like Python by a good amount but it is not performance-competitive with a modern compiled language.
Go's runtime is indeed faster for CPU-bound and raw throughput scenarios, but it lacks the same fault-tolerance semantics, hot-code reloading, and actor-level isolation - things that make BEAM indispensable in telecoms, messaging systems, and fault-resilient distributed architectures. Go may run faster, but Erlang and Elixir recover faster and fail more gracefully, which in distributed systems often matters more than raw speed. Go might win on throughput, but the BEAM wins on fault-tolerant system design - and that's why systems built on it keep running reliably for decades.
Additionally, high-performance Erlang/Elixir systems often delegate compute-intensive work to NIFs (native implemented functions) in C or Rust, or use ports to external services.