Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GLM-5.1
83
Qwen3.7 Max
93
Verified leaderboard positions: GLM-5.1 #23 · Qwen3.7 Max #2
Pick Qwen3.7 Max if you want the stronger benchmark profile. GLM-5.1 only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Agentic
+4.4 difference
Coding
+12.7 difference
Knowledge
+18.9 difference
GLM-5.1
Qwen3.7 Max
$1.4 / $4.4
$null / $null
N/A
N/A
N/A
N/A
203K
1M
Pick Qwen3.7 Max if you want the stronger benchmark profile. GLM-5.1 only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Qwen3.7 Max is clearly ahead on the provisional aggregate, 93 to 83. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.7 Max's sharpest advantage is in knowledge, where it averages 71.2 against 52.3. The single biggest benchmark swing on the page is HLE, 52.3% to 41.4%.
Qwen3.7 Max gives you the larger context window at 1M, compared with 203K for GLM-5.1.
Qwen3.7 Max is ahead on BenchLM's provisional leaderboard, 93 to 83. The biggest single separator in this matchup is HLE, where the scores are 52.3% and 41.4%.
Qwen3.7 Max has the edge for knowledge tasks in this comparison, averaging 71.2 versus 52.3. 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 60.9. Inside this category, NL2Repo is the benchmark that creates the most daylight between them.
Qwen3.7 Max has the edge for agentic tasks in this comparison, averaging 69.7 versus 65.3. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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