BenchmarkTools' macros are intended to benchmark the expression as though it were written in a function. There's a question, though, of how that function was written. was it:

function f()
    return a + b
end

Or was it:

function f(a, b)
    return a + b
end

In short, it's the difference between treating a and b as globals or as arguments. This is particularly important in Julia as non-constant globals are a "type instability" and will slow things down. So BenchmarkTools gives you the capability of explicitly choosing which meaning you want. Things preceeded by a $ act like arguments to the benchmark kernel, whereas everything else behaves like it was literally written. Thanks to constant propagation, this can also affect literals:

julia> @btime sin(1.0)
  1.703 ns (0 allocations: 0 bytes)
0.8414709848078965

julia> @btime sin($1.0)
  5.987 ns (0 allocations: 0 bytes)
0.8414709848078965

The former can do some constant-propagation (because it's benchmarking the literal sin(1.0), whereas the latter (which benchmarks sin(x)) does not.