GPT-5.4 mini vs MiniMax M2.7

Pick GPT-5.4 mini if you want the stronger benchmark profile. MiniMax M2.7 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.

GPT-5.4 mini is clearly ahead on the provisional aggregate, 71 to 62. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

GPT-5.4 mini's sharpest advantage is in agentic, where it averages 65.6 against 57. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 60% to 57%.

GPT-5.4 mini is also the more expensive model on tokens at $0.75 input / $4.50 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M2.7. That is roughly 3.8x on output cost alone. GPT-5.4 mini is the reasoning model in the pair, while MiniMax M2.7 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-5.4 mini gives you the larger context window at 400K, compared with 200K for MiniMax M2.7.