Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Mellum2-12B-A2.5B-Instruct
27
o1-pro
28
Pick o1-pro 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.
Knowledge
+38.1 difference
Mellum2-12B-A2.5B-Instruct
o1-pro
N/A
$150 / $600
N/A
N/A
N/A
N/A
128K
200K
Pick o1-pro 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.
o1-pro finishes one point ahead on BenchLM's provisional leaderboard, 28 to 27. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
o1-pro's sharpest advantage is in knowledge, where it averages 79 against 40.9. The single biggest benchmark swing on the page is GPQA, 40.9% to 79%.
o1-pro 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. o1-pro gives you the larger context window at 200K, compared with 128K for Mellum2-12B-A2.5B-Instruct.
o1-pro is ahead on BenchLM's provisional leaderboard, 28 to 27. The biggest single separator in this matchup is GPQA, where the scores are 40.9% and 79%.
o1-pro has the edge for knowledge tasks in this comparison, averaging 79 versus 40.9. Inside this category, GPQA is the benchmark that creates the most daylight between them.
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