Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemini 3.1 Pro
93
GPT-5.4 Pro
92
Pick Gemini 3.1 Pro if you want the stronger benchmark profile. GPT-5.4 Pro only becomes the better choice if multimodal & grounded is the priority or you need the larger 1.05M context window.
Reasoning
+6.2 difference
Multimodal
+10.1 difference
Gemini 3.1 Pro
GPT-5.4 Pro
$2 / $12
$30 / $180
109 t/s
74 t/s
29.71s
151.79s
1M
1.05M
Pick Gemini 3.1 Pro if you want the stronger benchmark profile. GPT-5.4 Pro only becomes the better choice if multimodal & grounded is the priority or you need the larger 1.05M context window.
Gemini 3.1 Pro finishes one point ahead on BenchLM's provisional leaderboard, 93 to 92. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
GPT-5.4 Pro is also the more expensive model on tokens at $30.00 input / $180.00 output per 1M tokens, versus $2.00 input / $12.00 output per 1M tokens for Gemini 3.1 Pro. That is roughly 15.0x on output cost alone. GPT-5.4 Pro is the reasoning model in the pair, while Gemini 3.1 Pro 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 Pro gives you the larger context window at 1.05M, compared with 1M for Gemini 3.1 Pro.
Gemini 3.1 Pro is ahead on BenchLM's provisional leaderboard, 93 to 92. The biggest single separator in this matchup is MMMU-Pro, where the scores are 83.9% and 94%.
GPT-5.4 Pro has the edge for reasoning in this comparison, averaging 83.3 versus 77.1. Inside this category, ARC-AGI-2 is the benchmark that creates the most daylight between them.
GPT-5.4 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 94 versus 83.9. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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