Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-4.1
57
GPT-5.4 nano
59
Pick GPT-5.4 nano if you want the stronger benchmark profile. GPT-4.1 only becomes the better choice if knowledge is the priority or you need the larger 1M context window.
Knowledge
+13.1 difference
GPT-4.1
GPT-5.4 nano
$2 / $8
$0.2 / $1.25
108 t/s
191 t/s
1.02s
3.64s
1M
400K
Pick GPT-5.4 nano if you want the stronger benchmark profile. GPT-4.1 only becomes the better choice if knowledge is the priority or you need the larger 1M context window.
GPT-5.4 nano has the cleaner provisional overall profile here, landing at 59 versus 57. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
GPT-4.1 is also the more expensive model on tokens at $2.00 input / $8.00 output per 1M tokens, versus $0.20 input / $1.25 output per 1M tokens for GPT-5.4 nano. That is roughly 6.4x on output cost alone. GPT-5.4 nano 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 400K for GPT-5.4 nano.
GPT-5.4 nano is ahead on BenchLM's provisional leaderboard, 59 to 57. The biggest single separator in this matchup is GPQA, where the scores are 66.3% and 82.8%.
GPT-4.1 has the edge for knowledge tasks in this comparison, averaging 66.3 versus 53.2. Inside this category, AA-HLE is the benchmark that creates the most daylight between them.
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