Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-4.1
58
o1
58
Treat this as a split decision. GPT-4.1 makes more sense if you want the cheaper token bill or you need the larger 1M context window; o1 is the better fit if knowledge is the priority or you want the stronger reasoning-first profile.
Knowledge
+9.4 difference
Inst. Following
+4.8 difference
GPT-4.1
o1
$2 / $8
$15 / $60
108 t/s
98 t/s
1.02s
32.29s
1M
200K
Treat this as a split decision. GPT-4.1 makes more sense if you want the cheaper token bill or you need the larger 1M context window; o1 is the better fit if knowledge is the priority or you want the stronger reasoning-first profile.
GPT-4.1 and o1 finish on the same provisional overall score, so this is less about a single winner and more about where the edge shows up. The provisional headline says tie; the benchmark table is where the real choice happens.
o1 is also the more expensive model on tokens at $15.00 input / $60.00 output per 1M tokens, versus $2.00 input / $8.00 output per 1M tokens for GPT-4.1. That is roughly 7.5x on output cost alone. o1 is the reasoning model in the pair, while GPT-4.1 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 gives you the larger context window at 1M, compared with 200K for o1.
GPT-4.1 and o1 are tied on the provisional overall score, so the right pick depends on which category matters most for your use case.
o1 has the edge for knowledge tasks in this comparison, averaging 75.7 versus 66.3. Inside this category, GPQA is the benchmark that creates the most daylight between them.
o1 has the edge for instruction following in this comparison, averaging 92.2 versus 87.4. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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