Regarding this analogy, fps don't matter as much for Photoshop, since it's not an immediate mode GUI. 8 fps would be quite ok for comfortably getting feedback on live image filters and such.

It’s not because you didn’t find use cases for local LLMs that there are none.

I use local LLMs on my Mac Mini M4 Pro with 48G to review text messages tone, act as a text correction tool, act as a code review tool, to do code agent work, generate code snippets, etc

Gemma 4 26B A4B gives me steady 20 tps.

Qwen3.8-27B runs at 59.5 tok/s on my M4 Max, 40-core GPU, 128 GB

I use it occasionally for classification and other tasks but I wouldn't trust those smaller models with the real work and for larger data processing it's too slow, e.g. a dataset I wanted to classify would've taken 56 days on my laptop vs just paying the cheap Luna prices to openai and getting it done in a few hours.

I've been using Qwen3.6-37B-A3B on an M1 Max w/ llama.cpp and for my practical uses I prefer it to qwen3.8. When 3.8 does answer its slower and, qualitatively, marginally better than qwen3.6, but 3.8 often ends up in unresolved thought loops and runs slower. The Moe 3.6 on my setup is much faster, 500t/s peaks, 30t/s typical, vs 3.8 150 peak, 4-9 t/s typical.

While I've spend a little time tuning, I'm assuming there will be deeper tuning for 3.8 that might close the gap.