Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.4 mini
72
Laguna M.1
46
Pick GPT-5.4 mini if you want the stronger benchmark profile. Laguna M.1 only becomes the better choice if you want the cheaper token bill.
Agentic
+24.9 difference
GPT-5.4 mini
Laguna M.1
$0.75 / $4.5
$0 / $0
201 t/s
N/A
3.85s
N/A
400K
131K
Pick GPT-5.4 mini if you want the stronger benchmark profile. Laguna M.1 only becomes the better choice if you want the cheaper token bill.
GPT-5.4 mini is clearly ahead on the provisional aggregate, 72 to 46. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.4 mini's sharpest advantage is in agentic, where it averages 65.6 against 40.7. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 60% to 40.7%.
GPT-5.4 mini is also the more expensive model on tokens at $0.75 input / $4.50 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Laguna M.1. That is roughly Infinityx on output cost alone. GPT-5.4 mini gives you the larger context window at 400K, compared with 131K for Laguna M.1.
GPT-5.4 mini is ahead on BenchLM's provisional leaderboard, 72 to 46. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 60% and 40.7%.
GPT-5.4 mini has the edge for agentic tasks in this comparison, averaging 65.6 versus 40.7. Inside this category, Terminal-Bench 2.0 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.