Anecdotal, but I've also not experienced any regression in Gemini quality where Claude/OpenAI might push iterative updates (or quantized variants for performance) that cause my test bench to fail more often.
This was hard for me to accept initially as I've learned to be anti-Google over the years, but the better accuracy was too good to pass up on. Still expecting a rugpull eventually — price hike, killing features without warning, changing internal details that break everything — but it hasn't happened yet.
Code quality was fine for my very limited tests but I was disappointed with instruction following.
I tried few tricks but I wasn't able to convince it to first present plan before starting implementation.
I have instructions describing that it should first do exploration (where it tried to discover what I want) then plan implementation and then code, but it always jumps directly to code.
this is bug issue for me especially because gemini-cli lacks plan mode like Claude code.
for codex those instructions make plan mode redundant.
Just early anecdote from trying to build that 1 SaaS application though.
What really impressed me was when I told it that I wanted a particular component’s UI to be cleaned up but I didn’t know how exactly, just wanted to use its deep design expertise to figure it out, and it came up with a UX that I would’ve never thought of and that was amazing.
Another important point is that the error rate for my session yesterday was significantly lower than when I’ve used any other model.
Today I will see how it does when I use it at work, where we have a massive codebase that has particular coding conventions. Curious how it does there.