massive slowdown for nested folding operations

Nested folding operations may lead to massive slowdowns, apparently from 32 bit numbers on:

julia> N = 32; T = Int16; v = [rand(T, N) for _ in 1:1000]; w = map(SVector{N}, v);

julia> @b sum(sum, $v)
11.637 μs

julia> @b sum(sum, $w)
1.401 μs

julia> N = 16; T = Int32; v = [rand(T, N) for _ in 1:1000]; w = map(SVector{N}, v);

julia> @b sum(sum, $v)
10.120 μs

julia> @b sum(sum, $w)
28.138 μs

julia> N = 16; T = Float32; v = [rand(T, N) for _ in 1:1000]; w = map(SVector{N}, v);

julia> @b sum(sum, $v)
10.656 μs

julia> @b sum(sum, $w)
29.554 μs

I've tried out several processors (all x86-64), with the same result. Maybe it's an LLVM issue. Is it known?

Julia Version 1.11.2
Commit 5e9a32e7af2 (2024-12-01 20:02 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: 4 × Intel(R) Core(TM) i3-10110U CPU @ 2.10GHz
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, skylake)

StaticArrays v1.9.13

Reproduce the Julia REPL benchmarks from the issue with StaticArrays v1.9.13, comparing nested sum on ordinary vectors and SVector values across the listed element types and sizes. Investigate the generated performance or compiler behavior to determine why some nested folds slow down, then document a confirmed cause and regression coverage or a focused fix.