Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Mellum2-12B-A2.5B-Thinking
59
Qwen3.7 Max
91
Verified leaderboard positions: Mellum2-12B-A2.5B-Thinking unranked · Qwen3.7 Max #2
Pick Qwen3.7 Max if you want the stronger benchmark profile. Mellum2-12B-A2.5B-Thinking only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Coding
+3.7 difference
Knowledge
+13.6 difference
Inst. Following
+12.5 difference
Mellum2-12B-A2.5B-Thinking
Qwen3.7 Max
N/A
$null / $null
N/A
N/A
N/A
N/A
128K
1M
Pick Qwen3.7 Max if you want the stronger benchmark profile. Mellum2-12B-A2.5B-Thinking 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, 91 to 59. 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 57.6. The single biggest benchmark swing on the page is GPQA, 57.6% to 92.4%.
Qwen3.7 Max gives you the larger context window at 1M, compared with 128K for Mellum2-12B-A2.5B-Thinking.
Qwen3.7 Max is ahead on BenchLM's provisional leaderboard, 91 to 59. The biggest single separator in this matchup is GPQA, where the scores are 57.6% and 92.4%.
Qwen3.7 Max has the edge for knowledge tasks in this comparison, averaging 71.2 versus 57.6. Inside this category, GPQA 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 69.9. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
Qwen3.7 Max has the edge for instruction following in this comparison, averaging 89 versus 76.5. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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