Quetext is the gold standard right now. 1Text is even better at times - but can be over-diligent at times.
You have to understand that to detect plagiarism - most advanced detection systems use tokenization. Meaning your text is converted into tokens that can be parsed by a computer system using an NLP model. A computer cannot read your sentence verbatim.
This is how most AI writers work as well. They "guess" or "estimate" the next token based on the information fed to them, resulting in a coherent sentence for you to read.
If all your paraphraser or your writer or even yourself when rewriting do is introduce fluff words, 1text or any token based plagiarism detector will detect it.
If the fluff words - "is, an, the, of, you, me, is, a" et al are removed - you're left with a very rudimentary idea of the scope of the sentence.
So for example, -
you might be wondering how long does thermal paste lasts when turned into something like "
how long does thermal paste lasts is a question you might be thinking of" looks pretty much the same at a token level. A simple similarity scan and a low enough benchmark and you have a hit.
Don't overanalyse though. Google isn't out there tokenizing the web. And has clearly stated that it isn't against duplicate content as badly as is made out to be.
Credit for the above tokenization example goes to
@Alexion