Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemma 4 E4B
37
Mellum2-12B-A2.5B-Instruct
27
Pick Gemma 4 E4B 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
+24.7 difference
Gemma 4 E4B
Mellum2-12B-A2.5B-Instruct
$0 / $0
N/A
N/A
N/A
N/A
N/A
128K
128K
Pick Gemma 4 E4B 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.
Gemma 4 E4B is clearly ahead on the provisional aggregate, 37 to 27. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemma 4 E4B's sharpest advantage is in knowledge, where it averages 65.6 against 40.9. The single biggest benchmark swing on the page is GPQA, 58.6% to 40.9%.
Gemma 4 E4B 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.
Gemma 4 E4B is ahead on BenchLM's provisional leaderboard, 37 to 27. The biggest single separator in this matchup is GPQA, where the scores are 58.6% and 40.9%.
Gemma 4 E4B has the edge for knowledge tasks in this comparison, averaging 65.6 versus 40.9. Inside this category, GPQA is the benchmark that creates the most daylight between them.
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