Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemini 2.5 Pro
67
GPT-5.4
93
Verified leaderboard positions: Gemini 2.5 Pro unranked · GPT-5.4 #4
Pick GPT-5.4 if you want the stronger benchmark profile. Gemini 2.5 Pro only becomes the better choice if coding is the priority or you want the cheaper token bill.
Coding
+6.1 difference
Knowledge
+52.0 difference
Gemini 2.5 Pro
GPT-5.4
$1.25 / $5
$2.5 / $15
117 t/s
74 t/s
21.19s
151.79s
1M
1.05M
Pick GPT-5.4 if you want the stronger benchmark profile. Gemini 2.5 Pro only becomes the better choice if coding is the priority or you want the cheaper token bill.
GPT-5.4 is clearly ahead on the provisional aggregate, 93 to 67. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.4's sharpest advantage is in knowledge, where it averages 92.8 against 40.8. The single biggest benchmark swing on the page is GPQA, 83% to 92.8%. Gemini 2.5 Pro does hit back in coding, so the answer changes if that is the part of the workload you care about most.
GPT-5.4 is also the more expensive model on tokens at $2.50 input / $15.00 output per 1M tokens, versus $1.25 input / $5.00 output per 1M tokens for Gemini 2.5 Pro. That is roughly 3.0x on output cost alone. GPT-5.4 is the reasoning model in the pair, while Gemini 2.5 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 gives you the larger context window at 1.05M, compared with 1M for Gemini 2.5 Pro.
GPT-5.4 is ahead on BenchLM's provisional leaderboard, 93 to 67. The biggest single separator in this matchup is GPQA, where the scores are 83% and 92.8%.
GPT-5.4 has the edge for knowledge tasks in this comparison, averaging 92.8 versus 40.8. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Gemini 2.5 Pro has the edge for coding in this comparison, averaging 63.8 versus 57.7. GPT-5.4 stays close enough that the answer can still flip depending on your workload.
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