Here are my own anecdotes from using o3-pro recently.
My primary use cases where I am willing to wait 10-20 minutes for an answer from the "big slow" model (o3-pro) is code reviews of large amounts of code. I have been comparing results on this task from the three models above.
Oddly, I see many cases where each model will surface issues that the other two miss. In previous months when running this test (e.g., Claude 3.7 Sonnet vs o1-pro vs earlier Gemini), that wasn't the case. Back then, the best model (o1-pro) would almost always find all the issues that the other models found. But now it seems they each have their own blindspots (although they are also all better than the previous generation of models).
With that said, I am seeing Claude Opus 4 (w/extended thinking) be distinctly worse at missing problems which o3-pro and Gemini find. It seems fairly consistent that Opus will be the worst out of the three (despite sometimes noticing things the others do not).
Whether o3-pro or Gemini 2.5 Pro is better is less clear. o3-pro will report more issues, but it also has a tendency to confabulate problems. My workflow involves providing the model with a diff of all changes, plus the full contents of the files that were changed. o3-pro seems to have a tendency to imagine and report problems in the files that were not provided to it. It also has an odd new failure mode, which is very consistent: it gets confused by the fact that I provide both the diff and the full file contents. It "sees" parts of the same code twice and will usually report that there has accidentally been some code duplicated. Base o3 does this as well. None of the other models get confused in that way, and I also do not remember seeing that failure mode with o1-pro.
Nevertheless, it seems o3-pro can sometimes find real issues that Gemini 2.5 Pro and Opus 4 cannot more often than vice versa.
Back in the o1-pro days, it was fairly straightforward in my testing for this use case that o1-pro was simply better across the board. Now with o3-pro compared particularly with Gemini 2.5 Pro, it's no longer clear whether the bonus of occasionally finding a problem that Gemini misses is worth the trouble of (1) waiting way longer for an answer and (2) sifting through more false positives.
My other common code-related use case is actually writing code. Here, Claude Code (with Opus 4) is amazing and has replaced all my other use of coding models, including Cursor. I now code almost exclusively by peer programming with Claude Code, allowing it to be the code writer while I oversee and review. The OpenAI competitor to Claude Code, called Codex CLI, feels distinctly undercooked. It has a recurring problem where it seems to "forget" that it is an agent that needs to go ahead and edit files, and it will instead start to offer me suggestions about how I can make the change. It also hallucinates running commands on a regular basis (e.g., I tell it to commit the changes we've done, and outputs that it has done so, but it has not.)
So where will I spend my $200 monthly model budget? Answer: Claude, for nearly unlimited use of Claude Code. For highly complex tasks, I switch to Gemini 2.5 Pro, which is still free in AI Studio. If I can wait 10+ minutes, I may hand it to o3-pro. But once my ChatGPT Pro subscription expires this month, I may either stop using o3-pro altogether, or I may occasionally use it as a second opinion by paying on-demand through the API.
> With that said, I am seeing Claude Opus 4 (w/extended thinking) be distinctly worse at missing problems which o3-pro and Gemini find. It seems fairly consistent that Opus will be the worst out of the three (despite sometimes noticing things the others do not).
I've found the same thing. That claude is more likely miss a bug than o3 or gemini but more likely to catch something o3 and gemini missed. If I had to pick one model I'd pick o3 or gemini, but if I had to pick a second model I'd pick opus.
It's also seems to have a much higher false positive rate where as gemini seems to have the lowest false positive rate.
Basically o3 and gemini are better, but also more correlated which gives opus a lot of value.
My primary use cases where I am willing to wait 10-20 minutes for an answer from the "big slow" model (o3-pro) is code reviews of large amounts of code. I have been comparing results on this task from the three models above.
Oddly, I see many cases where each model will surface issues that the other two miss. In previous months when running this test (e.g., Claude 3.7 Sonnet vs o1-pro vs earlier Gemini), that wasn't the case. Back then, the best model (o1-pro) would almost always find all the issues that the other models found. But now it seems they each have their own blindspots (although they are also all better than the previous generation of models).
With that said, I am seeing Claude Opus 4 (w/extended thinking) be distinctly worse at missing problems which o3-pro and Gemini find. It seems fairly consistent that Opus will be the worst out of the three (despite sometimes noticing things the others do not).
Whether o3-pro or Gemini 2.5 Pro is better is less clear. o3-pro will report more issues, but it also has a tendency to confabulate problems. My workflow involves providing the model with a diff of all changes, plus the full contents of the files that were changed. o3-pro seems to have a tendency to imagine and report problems in the files that were not provided to it. It also has an odd new failure mode, which is very consistent: it gets confused by the fact that I provide both the diff and the full file contents. It "sees" parts of the same code twice and will usually report that there has accidentally been some code duplicated. Base o3 does this as well. None of the other models get confused in that way, and I also do not remember seeing that failure mode with o1-pro.
Nevertheless, it seems o3-pro can sometimes find real issues that Gemini 2.5 Pro and Opus 4 cannot more often than vice versa.
Back in the o1-pro days, it was fairly straightforward in my testing for this use case that o1-pro was simply better across the board. Now with o3-pro compared particularly with Gemini 2.5 Pro, it's no longer clear whether the bonus of occasionally finding a problem that Gemini misses is worth the trouble of (1) waiting way longer for an answer and (2) sifting through more false positives.
My other common code-related use case is actually writing code. Here, Claude Code (with Opus 4) is amazing and has replaced all my other use of coding models, including Cursor. I now code almost exclusively by peer programming with Claude Code, allowing it to be the code writer while I oversee and review. The OpenAI competitor to Claude Code, called Codex CLI, feels distinctly undercooked. It has a recurring problem where it seems to "forget" that it is an agent that needs to go ahead and edit files, and it will instead start to offer me suggestions about how I can make the change. It also hallucinates running commands on a regular basis (e.g., I tell it to commit the changes we've done, and outputs that it has done so, but it has not.)
So where will I spend my $200 monthly model budget? Answer: Claude, for nearly unlimited use of Claude Code. For highly complex tasks, I switch to Gemini 2.5 Pro, which is still free in AI Studio. If I can wait 10+ minutes, I may hand it to o3-pro. But once my ChatGPT Pro subscription expires this month, I may either stop using o3-pro altogether, or I may occasionally use it as a second opinion by paying on-demand through the API.