GPT-4.1 nano vs o3-mini

Pick o3-mini if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.

o3-mini is clearly ahead on the provisional aggregate, 56 to 27. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

o3-mini's sharpest advantage is in knowledge, where it averages 77.2 against 50.3. The single biggest benchmark swing on the page is GPQA, 50.3% to 77.2%.

o3-mini is also the more expensive model on tokens at $1.10 input / $4.40 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for GPT-4.1 nano. That is roughly 11.0x on output cost alone. o3-mini is the reasoning model in the pair, while GPT-4.1 nano 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. GPT-4.1 nano gives you the larger context window at 1M, compared with 200K for o3-mini.