Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.4 mini
68
LongCat-2.0
80
Pick LongCat-2.0 if you want the stronger benchmark profile. GPT-5.4 mini only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Agentic
+5.2 difference
GPT-5.4 mini
LongCat-2.0
$0.75 / $4.5
$0.75 / $2.95
201 t/s
N/A
3.85s
N/A
400K
1M
Pick LongCat-2.0 if you want the stronger benchmark profile. GPT-5.4 mini only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
LongCat-2.0 is clearly ahead on the provisional aggregate, 80 to 68. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
LongCat-2.0's sharpest advantage is in agentic, where it averages 70.8 against 65.6. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 60% to 70.8%.
GPT-5.4 mini is also the more expensive model on tokens at $0.75 input / $4.50 output per 1M tokens, versus $0.75 input / $2.95 output per 1M tokens for LongCat-2.0. LongCat-2.0 gives you the larger context window at 1M, compared with 400K for GPT-5.4 mini.
LongCat-2.0 is ahead on BenchLM's provisional leaderboard, 80 to 68. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 60% and 70.8%.
LongCat-2.0 has the edge for agentic tasks in this comparison, averaging 70.8 versus 65.6. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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