Why mix models? One size fits none. You get different strengths and unique...

https://wiki-zine.win/index.php/Beyond_the_Hype:_The_Engineer%E2%80%99s_Guide_to_Evaluating_Multi-Model_AI_Tooling

Why mix models? One size fits none. You get different strengths and unique failure modes. It’s a smart hedge, but watch out—automated synthesis can hide meaningful dissent or leak data across providers