Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemini 2.5 Pro
64
Mellum2-12B-A2.5B-Thinking
59
Pick Gemini 2.5 Pro if you want the stronger benchmark profile. Mellum2-12B-A2.5B-Thinking only becomes the better choice if knowledge is the priority or you want the stronger reasoning-first profile.
Coding
+6.1 difference
Knowledge
+16.8 difference
Gemini 2.5 Pro
Mellum2-12B-A2.5B-Thinking
$1.25 / $10
N/A
117 t/s
N/A
21.19s
N/A
1M
128K
Pick Gemini 2.5 Pro if you want the stronger benchmark profile. Mellum2-12B-A2.5B-Thinking only becomes the better choice if knowledge is the priority or you want the stronger reasoning-first profile.
Gemini 2.5 Pro is clearly ahead on the provisional aggregate, 64 to 59. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Mellum2-12B-A2.5B-Thinking is the reasoning model in the pair, while Gemini 2.5 Pro 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. Gemini 2.5 Pro gives you the larger context window at 1M, compared with 128K for Mellum2-12B-A2.5B-Thinking.
Gemini 2.5 Pro is ahead on BenchLM's provisional leaderboard, 64 to 59. The biggest single separator in this matchup is GPQA, where the scores are 83% and 57.6%.
Mellum2-12B-A2.5B-Thinking has the edge for knowledge tasks in this comparison, averaging 57.6 versus 40.8. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Mellum2-12B-A2.5B-Thinking has the edge for coding in this comparison, averaging 69.9 versus 63.8. Gemini 2.5 Pro stays close enough that the answer can still flip depending on your workload.
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