Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.5
91
Laguna M.1
51
Verified leaderboard positions: GPT-5.5 #5 · Laguna M.1 unranked
Pick GPT-5.5 if you want the stronger benchmark profile. Laguna M.1 only becomes the better choice if you want the cheaper token bill.
Agentic
+35.7 difference
Coding
GPT-5.5
Laguna M.1
$5 / $30
$0 / $0
N/A
N/A
N/A
N/A
1M
131K
Pick GPT-5.5 if you want the stronger benchmark profile. Laguna M.1 only becomes the better choice if you want the cheaper token bill.
GPT-5.5 is clearly ahead on the provisional aggregate, 91 to 51. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.5's sharpest advantage is in agentic, where it averages 81.5 against 45.8. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 82% to 45.8%.
GPT-5.5 is also the more expensive model on tokens at $5.00 input / $30.00 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-5.5 gives you the larger context window at 1M, compared with 131K for Laguna M.1.
GPT-5.5 is ahead on BenchLM's provisional leaderboard, 91 to 51. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 82% and 45.8%.
GPT-5.5 and Laguna M.1 are effectively tied for coding here, both landing at 58.6 on average.
GPT-5.5 has the edge for agentic tasks in this comparison, averaging 81.5 versus 45.8. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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