There's different kinds of fast. For most kinds of fast that people doing 'web' type things need, a garbage collector and a VM are not going to be the bottleneck. Efficient management of workloads across blocking I/O is going to be where the hard work is.
Now, I've written ad servers and video streamers, and other low latency high throughput things, and yes, I'd probably reach for C++ or Rust there. But some of the jobs I've seen lately posting for Rust, I do question. Even if I'm tempted to apply, because I'd like to get $$ to work in Rust.
That said, people misuse technology all the dang time(I've done it). And in general I agree, Go is usually enough and has the best cloud ecosystem. I've had trouble with large go code bases exploding over time and requiring a lot of bodies to maintain compared with rust/scala.
Sometimes it's hard to speculate when one tool is clearly better than another. Some companies just want to use new stuff to sound cooler...
Super high-end stuff can outclass Go by that much, like if you're seriously using DPDK or something, and in those cases I strongly recommend Rust over Go. There some other noches like that. But in general, it's not a factor of magnitude.
However, by far the bigger problem is people thinking their little web service serving out 5 requests a second requires that level of optimization when in fact even a Go implementation will use <1% of the CPU and no other resources to speak of. Dynamic scripting languages, IMHO, have skewed a lot of people's performance views. Go is already more power than most problems need, in terms of raw performance, and it's only a sliver, a niche where that's the difference between a Go vs. Rust choice.
It's a delicate understanding, but an important one for a professional.
https://web-frameworks-benchmark.netlify.app/result?f=axum,g...
I've done some benchmarking with Actic, Axum and Go (std lib). Actix was top, Axum about 85 % of Actix and Go about 75 % of Actix.
For a lot of web stuff you need throughput more than you need latency "fast".
In order to do throughput well you need concurrency.
Anecdata are all I can provide, but the equivalent (Google) batch job in C++ vs. Java is often an order of magnitude better for a variety of reasons. It might only be 0.5-3x faster, but it also uses less cores and less memory to do the same amount of work.
Having written C++ and Java services, the median C++ service is performs better than the median Java service. Some of that is less pointer chasing, some of it is better libraries. Some services will be slow no matter what you write them in. There's too many variables to quantify, and "performs better" is a real load bearing term. Sometimes it's less CPU, memory. Sometimes it's latency.
I still primarily work on Java services, and they perform pretty well. That said, the operational dynamism of Java services is a real thorn in my side. Beyond the GC, there's a lot going on in the runtime including JIT that just makes JVM services less predictable. Even classloading is a source of unpredictability, unless you eagerly load classes.
FWIW, I think Go does a pretty good job being predictable too. AOT compilation helps there, you're not worrying about new tasks needing to JIT. Go mostly worries about GC (often irrelevant), warmup of state (like TCP connections), and avoiding footguns that leak Goroutines. :) At least Go's footguns rarely blow your whole leg off.
To be fair, I usually prefer to use go as well, lately though rust is more appealing.