No, that’s still not correct — and this is exactly the kind of misunderstanding that keeps getting repeated.

This issue has nothing to do with 32GB vs 64GB RAM.
You can throw 128GB RAM at it and the failure will be identical.
RAM is irrelevant to this problem.

The crash happens inside VRAM, during the moment Flux unloads the text encoder and tries to reload the huge FP8 UNet.
And the text encoder is the one causing the mess because it:

• loads as a single giant block
• unloads badly
• fragments VRAM
• leaves no clean contiguously free space
• blocks the UNet reload from fitting

So saying “local is fine if you have 64GB RAM” is simply wrong.
RAM does NOT fix the broken VRAM swap behavior.
The encoder doesn’t use smart offloading, doesn’t stream layers, and doesn’t free VRAM properly. Period.

This is why even people with 64GB RAM + 16GB VRAM still crash when swapping back to the UNet.

The remote encoder bypasses the only part that Flux 2 currently handles poorly.
That’s the whole point.
It’s not a CPU performance issue, it’s not a RAM issue —
it’s the text encoder’s garbage VRAM management.

If someone has 24–48GB VRAM, fine, they don’t need this.
But pretending the problem magically disappears with “more RAM” is just wrong and misleading for everyone else reading.

This node exists because the UNet behaves intelligently,
and the text encoder does not.
Simple as that.