Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.5 Pro
100
MiniMax M2.7
64
Pick GPT-5.5 Pro 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.
Agentic
+33.1 difference
GPT-5.5 Pro
MiniMax M2.7
$30 / $180
$0.3 / $1.2
N/A
45 t/s
N/A
2.53s
1M
200K
Pick GPT-5.5 Pro 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-5.5 Pro is clearly ahead on the provisional aggregate, 100 to 64. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.5 Pro's sharpest advantage is in agentic, where it averages 90.1 against 57.
GPT-5.5 Pro is also the more expensive model on tokens at $30.00 input / $180.00 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M2.7. That is roughly 150.0x on output cost alone. GPT-5.5 Pro 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-5.5 Pro gives you the larger context window at 1M, compared with 200K for MiniMax M2.7.
GPT-5.5 Pro is ahead on BenchLM's provisional leaderboard, 100 to 64.
GPT-5.5 Pro has the edge for agentic tasks in this comparison, averaging 90.1 versus 57. MiniMax M2.7 stays close enough that the answer can still flip depending on your workload.
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