Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.4 nano
61
Interfaze Beta
76
Pick Interfaze Beta if you want the stronger benchmark profile. GPT-5.4 nano only becomes the better choice if you want the cheaper token bill.
Knowledge
+36.7 difference
Multimodal
+5.0 difference
GPT-5.4 nano
Interfaze Beta
$0.2 / $1.25
$1.5 / $3.5
191 t/s
N/A
3.64s
N/A
400K
1M
Pick Interfaze Beta if you want the stronger benchmark profile. GPT-5.4 nano only becomes the better choice if you want the cheaper token bill.
Interfaze Beta is clearly ahead on the provisional aggregate, 76 to 61. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Interfaze Beta's sharpest advantage is in knowledge, where it averages 89.9 against 53.2. The single biggest benchmark swing on the page is GPQA, 82.8% to 89.9%.
Interfaze Beta is also the more expensive model on tokens at $1.50 input / $3.50 output per 1M tokens, versus $0.20 input / $1.25 output per 1M tokens for GPT-5.4 nano. That is roughly 2.8x on output cost alone. Interfaze Beta gives you the larger context window at 1M, compared with 400K for GPT-5.4 nano.
Interfaze Beta is ahead on BenchLM's provisional leaderboard, 76 to 61. The biggest single separator in this matchup is GPQA, where the scores are 82.8% and 89.9%.
Interfaze Beta has the edge for knowledge tasks in this comparison, averaging 89.9 versus 53.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Interfaze Beta has the edge for multimodal and grounded tasks in this comparison, averaging 71.1 versus 66.1. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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