
I appreciate that pushback (/s), although honestly if you (like myself) find AI-tells like that cringe, you’re almost certainly not the type of person using it addictively.
There’s a pretty strong body of research that lots of people are subconsciously picking up language patterns from AI, such as the increased prevalence of words like “delve”. It’s the basic social mirroring we do to pick up language from anyone we talk to, only weirdly twisted because the thing so many people are talking to isn’t human.
“I appreciate that pushback” isn’t a commonly complained enough tell that people would be intentionally avoiding it, I find it pretty believable that a heavy AI user would unironically use it in a Q&A.





I’m surprised you feel you need that much. Personally, I’m tinkering on a 7900XTX, with 24Gb of VRAM. I can’t run the massive new models, like the latest Deepseek Flash at 400+ Gb, but neither can 192Gb. Means my context isn’t unlimited, but I’m able to run even big local models like Qwen3.8 at Q4_K_M with a context of 64K, which is enough when paired with a front end like Hermes that can run compaction and invoke subagents. Honestly, I’d describe 24Gb as a sweet spot for local AI usage, 32Gb sounds like comfortable headroom for a larger context window, or even multiple heads.
To be fair, I guess it is unified memory, and it doesn’t sound like you’re running it on a dedicated machine, so maybe the other stuff you’re running is pushing past 8Gb and giving you less space for AI than me. But 128Gb still sounds like wild excess to me, well into the diminishing returns of slightly more accurate rounding and needlessly large context.