GPT-4.1 mini vs Sakana Fugu Ultra

Pick Sakana Fugu Ultra 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.

Sakana Fugu Ultra is clearly ahead on the provisional aggregate, 100 to 45. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Sakana Fugu Ultra's sharpest advantage is in coding, where it averages 83.5 against 23.6. The single biggest benchmark swing on the page is GPQA, 64.2% to 95.5%.

Sakana Fugu Ultra is also the more expensive model on tokens at $5.00 input / $30.00 output per 1M tokens, versus $0.40 input / $1.60 output per 1M tokens for GPT-4.1 mini. That is roughly 18.8x on output cost alone. Sakana Fugu Ultra 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.