> even the lower-end models can find the things they didn't think of first when inspecting the already-written output

I use Deepseek V4 Pro for my hobby project (an OpenCode client). The economics will obviously be different at work.

It’s worse than the GPTs, but indeed, if you focus it on reviewing its own code (essentially spending more reasoning and changing perspective), it’s also quite capable at improving its own approaches.

The GPTs are better at general architecting, but I think a lot of the performance gains also came from my more careful prompting (“okay, this is a hard problem, let’s think this through …”) to make using the more expensive model worth it. I use them and they are worth it on subsidized rates, but not at API prices. Since my Codex sub ran out I sometimes miss the models, but it really hasn’t devastated me.

On my own time I still like the 'chat' format of me writing a short prompt and having the model turn it into a few dozen lines of code, or make a simple refactor (like turn a field into a method parameter.

I wasn't impressed with Chinese models (I tried Deepseek V4 Pro/Flash, and GLM5.2) the amount of questionable code and mistakes and misunderstandings meant the money saved and faster speed of models didn't translate to faster progress for me.