On M4 Max 128GB we're seeing ~100 tok/s generation on a 30B parameter model in our from scratch inference engine. Very curious what the "4x faster LLM prompt processing" translates to in practice. Smallish, local 30B-70B inference is genuinely usable territory for real dev workflows, not just demos. Will require staying plugged in though.
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I think the truth is somewhere in the middle, many people don't realize just how performant (especially with MLX) some of these models have become on Mac hardware, and just how powerful the shared memory architecture they've built is, but also there is a lot of hype and misinformation on performance when compared to dedicated GPU's. It's a tradeoff between available memory and performance, but often it makes sense.