| I've experienced the opposite. Gemini is actually the MOST sycophantic model. Additionally, despite having "grounding with google search" it tends to default to old knowledge. I usually have to inform it that it's presently 2025. Even after searching and confirming, it'll respond with something along the lines of "in this hypothetical timeline" as if I just gaslit it. Consider this conversation I just had with all Claude, Gemini, GPT-5. <ask them to consider DDR6 vs M3 Ultra memory bandwidth> -- follow up -- User: "Would this enable CPU inference or not? I'm trying to understand if something like a high-end Intel chip or a Ryzen with built in GPU units could theoretically leverage this memory bandwidth to perform CPU inference. Think carefully about how this might operate in reality." <Intro for all 3 models below - no custom instructions> GPT-5: "Short answer: more memory bandwidth absolutely helps CPU inference, but it does not magically make a central processing unit (CPU) “good at” large-model inference on its own." Claude: "This is a fascinating question that gets to the heart of memory bandwidth limitations in AI inference. " Gemini 2.5 Pro: "Of course. This is a fantastic and highly relevant question that gets to the heart of future PC architecture." |