Gemini 3.5 Flash vs GPT-4.1 nano

Pick Gemini 3.5 Flash if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if instruction following is the priority or you want the cheaper token bill.

Gemini 3.5 Flash is clearly ahead on the provisional aggregate, 88 to 27. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Gemini 3.5 Flash's sharpest advantage is in knowledge, where it averages 58 against 50.3. The single biggest benchmark swing on the page is GPQA, 92.2% to 50.3%. GPT-4.1 nano does hit back in instruction following, so the answer changes if that is the part of the workload you care about most.

Gemini 3.5 Flash is also the more expensive model on tokens at $1.50 input / $9.00 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for GPT-4.1 nano. That is roughly 22.5x on output cost alone. Gemini 3.5 Flash 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.