Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-4.1 mini
45
GPT-5.2
79
Pick GPT-5.2 if you want the stronger benchmark profile. GPT-4.1 mini only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
Coding
+41.1 difference
Knowledge
+28.2 difference
GPT-4.1 mini
GPT-5.2
$0.4 / $1.6
$1.75 / $14
80 t/s
73 t/s
0.76s
130.34s
1M
400K
Pick GPT-5.2 if you want the stronger benchmark profile. GPT-4.1 mini only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
GPT-5.2 is clearly ahead on the provisional aggregate, 79 to 45. 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 coding, where it averages 64.7 against 23.6. The single biggest benchmark swing on the page is SWE-bench Verified, 23.6% to 80%.
GPT-5.2 is also the more expensive model on tokens at $1.75 input / $14.00 output per 1M tokens, versus $0.40 input / $1.60 output per 1M tokens for GPT-4.1 mini. That is roughly 8.8x on output cost alone. GPT-5.2 is the reasoning model in the pair, while GPT-4.1 mini 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-4.1 mini gives you the larger context window at 1M, compared with 400K for GPT-5.2.
GPT-5.2 is ahead on BenchLM's provisional leaderboard, 79 to 45. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 23.6% and 80%.
GPT-5.2 has the edge for knowledge tasks in this comparison, averaging 92.4 versus 64.2. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for coding in this comparison, averaging 64.7 versus 23.6. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
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