Ah, good point.
Though I was more thinking of Shor's algorithm and Grover's algorithm that tells us the theoretical expected performance that could be achieved with quantum computers. Normally these are described as showing the speedup provided by a possible quantum computer (in relation to non-quantum computers).
So, when reading the Wolfram Model paper I cited, I read the statement regarding quantum computers as dismissing the possibility of achieving qantum computers capable of realising Shor's and Grover's.
But one could of course read it in a flip-side way, that there are algorithms out there to be discovered that achieves the same lower bound complexities on non-quantum machines.
Considering that the Wolfram Model is all about graphs and cellular automata, the statement should probably be considered not based on a RAM complexity model, but something like PRAM that considers parallelism.
Congratulations, you've rediscovered quantum annealing!
[warning: uninformed tangent]
A more optimistic interpretation could be that quantum & non-quantum machines will be similar because we have huge leaps to make in non-quantum computer architecture.
This is strictly a theoretical thought-experiment for me, but it has always intrigued me that quantum computers sort-of model the problem itself in the hardware circuit & shove a bunch of qubits through it.
In digital computers, we mostly model Boolean logical structures & then, in software, translate our problem into that Boolean logic. This translation into discrete steps places a limit on the theoretical efficiency.
However, perhaps there is room in analog computing hardware to more closely model specific types of optimization problems & then shove a bunch of electrons through it (shouldn’t the electrons follow the path of least resistance?).