Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GLM-5.2
94
Qwen 3.6 Max (preview)
78
Verified leaderboard positions: GLM-5.2 #9 · Qwen 3.6 Max (preview) unranked
Pick GLM-5.2 if you want the stronger benchmark profile. Qwen 3.6 Max (preview) only becomes the better choice if knowledge is the priority.
Agentic
+15.6 difference
Coding
+8.0 difference
Knowledge
+6.7 difference
GLM-5.2
Qwen 3.6 Max (preview)
$1.4 / $4.4
N/A
N/A
N/A
N/A
N/A
1M
256K
Pick GLM-5.2 if you want the stronger benchmark profile. Qwen 3.6 Max (preview) only becomes the better choice if knowledge is the priority.
GLM-5.2 is clearly ahead on the provisional aggregate, 94 to 78. 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 65.4. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 81% to 65.4%. Qwen 3.6 Max (preview) does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
GLM-5.2 gives you the larger context window at 1M, compared with 256K for Qwen 3.6 Max (preview).
GLM-5.2 is ahead on BenchLM's provisional leaderboard, 94 to 78. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 81% and 65.4%.
Qwen 3.6 Max (preview) has the edge for knowledge tasks in this comparison, averaging 73.9 versus 67.2. GLM-5.2 stays close enough that the answer can still flip depending on your workload.
GLM-5.2 has the edge for coding in this comparison, averaging 62.1 versus 54.1. 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 65.4. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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