Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GLM-5.2
94
Laguna M.1
51
Verified leaderboard positions: GLM-5.2 #9 · Laguna M.1 unranked
Pick GLM-5.2 if you want the stronger benchmark profile. Laguna M.1 only becomes the better choice if you want the cheaper token bill.
Agentic
+35.2 difference
Coding
+3.5 difference
GLM-5.2
Laguna M.1
$1.4 / $4.4
$0 / $0
N/A
N/A
N/A
N/A
1M
131K
Pick GLM-5.2 if you want the stronger benchmark profile. Laguna M.1 only becomes the better choice if you want the cheaper token bill.
GLM-5.2 is clearly ahead on the provisional aggregate, 94 to 51. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-5.2's sharpest advantage is in agentic, where it averages 81 against 45.8. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 81% to 45.8%.
GLM-5.2 is also the more expensive model on tokens at $1.40 input / $4.40 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. GLM-5.2 gives you the larger context window at 1M, compared with 131K for Laguna M.1.
GLM-5.2 is ahead on BenchLM's provisional leaderboard, 94 to 51. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 81% and 45.8%.
GLM-5.2 has the edge for coding in this comparison, averaging 62.1 versus 58.6. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GLM-5.2 has the edge for agentic tasks in this comparison, averaging 81 versus 45.8. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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