Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Mellum2-12B-A2.5B-Instruct
27
Qwen 3.6 Max (preview)
79
Pick Qwen 3.6 Max (preview) if you want the stronger benchmark profile. Mellum2-12B-A2.5B-Instruct only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Coding
+16.9 difference
Knowledge
+33.0 difference
Mellum2-12B-A2.5B-Instruct
Qwen 3.6 Max (preview)
N/A
N/A
N/A
N/A
N/A
N/A
128K
256K
Pick Qwen 3.6 Max (preview) if you want the stronger benchmark profile. Mellum2-12B-A2.5B-Instruct only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Qwen 3.6 Max (preview) is clearly ahead on the provisional aggregate, 79 to 27. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen 3.6 Max (preview)'s sharpest advantage is in knowledge, where it averages 73.9 against 40.9.
Qwen 3.6 Max (preview) is the reasoning model in the pair, while Mellum2-12B-A2.5B-Instruct is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Qwen 3.6 Max (preview) gives you the larger context window at 256K, compared with 128K for Mellum2-12B-A2.5B-Instruct.
Qwen 3.6 Max (preview) is ahead on BenchLM's provisional leaderboard, 79 to 27.
Qwen 3.6 Max (preview) has the edge for knowledge tasks in this comparison, averaging 73.9 versus 40.9. Mellum2-12B-A2.5B-Instruct stays close enough that the answer can still flip depending on your workload.
Qwen 3.6 Max (preview) has the edge for coding in this comparison, averaging 54.1 versus 37.2. Mellum2-12B-A2.5B-Instruct stays close enough that the answer can still flip depending on your workload.
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