Claude Opus 4.7 (Adaptive) vs GPT-4.1 mini

Pick Claude Opus 4.7 (Adaptive) if you want the stronger benchmark profile. GPT-4.1 mini only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.

Claude Opus 4.7 (Adaptive) is clearly ahead on the provisional aggregate, 90 to 46. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Claude Opus 4.7 (Adaptive)'s sharpest advantage is in coding, where it averages 72.9 against 23.6. The single biggest benchmark swing on the page is SWE-bench Verified, 87.6% to 23.6%.

Claude Opus 4.7 (Adaptive) is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $0.40 input / $1.60 output per 1M tokens for GPT-4.1 mini. That is roughly 15.6x on output cost alone. Claude Opus 4.7 (Adaptive) is the reasoning model in the pair, while GPT-4.1 mini is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use.