Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GLM-5.2
94
Qwen3.7 Max
90
Verified leaderboard positions: GLM-5.2 #9 · Qwen3.7 Max #3
Pick GLM-5.2 if you want the stronger benchmark profile. Qwen3.7 Max only becomes the better choice if coding is the priority.
Agentic
+11.3 difference
Coding
+11.5 difference
Knowledge
+4.0 difference
GLM-5.2
Qwen3.7 Max
$1.4 / $4.4
$null / $null
N/A
N/A
N/A
N/A
1M
1M
Pick GLM-5.2 if you want the stronger benchmark profile. Qwen3.7 Max only becomes the better choice if coding is the priority.
GLM-5.2 is clearly ahead on the provisional aggregate, 94 to 90. 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 69.7. The single biggest benchmark swing on the page is HLE, 54.7% to 41.4%. Qwen3.7 Max does hit back in coding, so the answer changes if that is the part of the workload you care about most.
GLM-5.2 is ahead on BenchLM's provisional leaderboard, 94 to 90. The biggest single separator in this matchup is HLE, where the scores are 54.7% and 41.4%.
Qwen3.7 Max has the edge for knowledge tasks in this comparison, averaging 71.2 versus 67.2. Inside this category, HLE is the benchmark that creates the most daylight between them.
Qwen3.7 Max has the edge for coding in this comparison, averaging 73.6 versus 62.1. 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 69.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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