I've been using o3 extensively since release (and a lot of Deep Research). I also use a lot of Claude and Gemini 2.5 Pro (most of the times, for code I'll let all of them go at it and iterate on my fav results).
So far I've only used o3-pro a bit today, and it's a bit too heavy to use interactively (fire it off, revisit in 10-15 minutes), but it seems to generate much cleaner/more well organized code and answers.
I feel like the benchmarks aren't really doing a good job at capturing/reflecting capabilities atm. eg, while Claude 4 Sonnet appears to score about as well as Opus 4, in my usage Opus is always significantly better at solving my problem/writing the code I need.
Besides especially complex/gnarly problems, I feel like a lot of the different models are all good enough and it comes down to reliability. For example, I've stopped using Claude for work basically because multiple times now it's completely eaten my prompts and even artifacts it's generated. Also, it hits limits ridiculously fast (and does so even when on network/resource failures).
I use 4.1 as my workhorse for code interpreter work (creating graphs/charts w/ matplotlib, basic df stuff, converting tables to markdown) as it's just better integrated than the others and so far I haven't caught 4.1 transposing/having errors with numbers (which I've noticed w/ 4o and Sonnet).
Having tested most of the leading edge open and closed models a fair amount, 4.5 is still my current preferred model to actually talk to/make judgement calls (particularly with translations). Again, not reflected in benchmarks, but 4.5 is the only model that gives me the feeling I had when first talking to Opus 3 (eg, of actual fluid intelligence, and a pleasant personality that isn't overly sychophantic) - Opus 4 is a huge regression in that respect for me.
(I also use Codex, Roo Code, Windsurf, and a few other API-based tools, but tbt, OpenAI's ChatGPT UI is generally better for how I leverage the models in my workflow.)