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I think models are smart enough for most of the stuff, these little incremental changes barely matter now. What I want is the model that is fast.


I predict a bifurcation in usage.

Serial usecases ("fix this syntax errors") will go on Cerebras and get 10x faster.

Deep usecases ("solve Riemann hypothesis") will become massively parallel and go on slower inference compute.

Teams will stitch both together because some workflows go through stages of requiring deep parallel compute ("scan my codebase for bugs and propose fixes") followed by serial compute ("dedupe and apply the 3 fixes, resolve merge conflict").


I've been using 5.1-codex-max with low reasoning (in Cursor fwiw) recently and it feels like a nice speed while still being effective. Might be worth a shot.


This is faster if their marketing is right, it uses significantly less tokens. Gemini 3 flash is very good as well.




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