Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.2
78
GPT-5.4 nano
59
Pick GPT-5.2 if you want the stronger benchmark profile. GPT-5.4 nano only becomes the better choice if you want the cheaper token bill.
Agentic
+12.3 difference
Knowledge
+39.2 difference
Multimodal
+14.2 difference
GPT-5.2
GPT-5.4 nano
$1.75 / $14
$0.2 / $1.25
73 t/s
191 t/s
130.34s
3.64s
400K
400K
Pick GPT-5.2 if you want the stronger benchmark profile. GPT-5.4 nano only becomes the better choice if you want the cheaper token bill.
GPT-5.2 is clearly ahead on the provisional aggregate, 78 to 59. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.2's sharpest advantage is in knowledge, where it averages 92.4 against 53.2. The single biggest benchmark swing on the page is MMMU-Pro, 79.5% to 66.1%.
GPT-5.2 is also the more expensive model on tokens at $1.75 input / $14.00 output per 1M tokens, versus $0.20 input / $1.25 output per 1M tokens for GPT-5.4 nano. That is roughly 11.2x on output cost alone.
GPT-5.2 is ahead on BenchLM's provisional leaderboard, 78 to 59. The biggest single separator in this matchup is MMMU-Pro, where the scores are 79.5% and 66.1%.
GPT-5.2 has the edge for knowledge tasks in this comparison, averaging 92.4 versus 53.2. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for agentic tasks in this comparison, averaging 55.2 versus 42.9. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for multimodal and grounded tasks in this comparison, averaging 80.3 versus 66.1. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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