Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.5 Pro
100
MiniMax M3
76
Verified leaderboard positions: GPT-5.5 Pro unranked · MiniMax M3 #12
Pick GPT-5.5 Pro if you want the stronger benchmark profile. MiniMax M3 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
+18.2 difference
GPT-5.5 Pro
MiniMax M3
$30 / $180
$0.3 / $1.2
N/A
N/A
N/A
N/A
1M
1M
Pick GPT-5.5 Pro if you want the stronger benchmark profile. MiniMax M3 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 76. 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 71.9. The single biggest benchmark swing on the page is BrowseComp, 90.1% to 83.5%.
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 M3. That is roughly 150.0x on output cost alone. GPT-5.5 Pro is the reasoning model in the pair, while MiniMax M3 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 is ahead on BenchLM's provisional leaderboard, 100 to 76. The biggest single separator in this matchup is BrowseComp, where the scores are 90.1% and 83.5%.
GPT-5.5 Pro has the edge for agentic tasks in this comparison, averaging 90.1 versus 71.9. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
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