Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-4.1 nano
26
GPT-5.2
79
Pick GPT-5.2 if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
Knowledge
+42.1 difference
GPT-4.1 nano
GPT-5.2
$0.1 / $0.4
$1.75 / $14
181 t/s
73 t/s
0.63s
130.34s
1M
400K
Pick GPT-5.2 if you want the stronger benchmark profile. GPT-4.1 nano 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 26. 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 50.3. The single biggest benchmark swing on the page is GPQA, 50.3% to 92.4%.
GPT-5.2 is also the more expensive model on tokens at $1.75 input / $14.00 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for GPT-4.1 nano. That is roughly 35.0x on output cost alone. GPT-5.2 is the reasoning model in the pair, while GPT-4.1 nano 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 nano 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 26. The biggest single separator in this matchup is GPQA, where the scores are 50.3% and 92.4%.
GPT-5.2 has the edge for knowledge tasks in this comparison, averaging 92.4 versus 50.3. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
For engineers, researchers, and the plain curious — a weekly brief on new models, ranking shifts, and pricing changes.
Free. No spam. Unsubscribe anytime.