Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Kimi K2.5
64
Mellum2-12B-A2.5B-Thinking
59
Verified leaderboard positions: Kimi K2.5 #16 · Mellum2-12B-A2.5B-Thinking unranked
Pick Kimi K2.5 if you want the stronger benchmark profile. Mellum2-12B-A2.5B-Thinking only becomes the better choice if coding is the priority or you want the stronger reasoning-first profile.
Coding
+5.7 difference
Knowledge
+7.5 difference
Inst. Following
+17.4 difference
Kimi K2.5
Mellum2-12B-A2.5B-Thinking
$0.6 / $3
N/A
45 t/s
N/A
2.38s
N/A
256K
128K
Pick Kimi K2.5 if you want the stronger benchmark profile. Mellum2-12B-A2.5B-Thinking only becomes the better choice if coding is the priority or you want the stronger reasoning-first profile.
Kimi K2.5 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.
Kimi K2.5's sharpest advantage is in instruction following, where it averages 93.9 against 76.5. The single biggest benchmark swing on the page is GPQA, 87.6% to 57.6%. Mellum2-12B-A2.5B-Thinking does hit back in coding, so the answer changes if that is the part of the workload you care about most.
Mellum2-12B-A2.5B-Thinking is the reasoning model in the pair, while Kimi K2.5 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. Kimi K2.5 gives you the larger context window at 256K, compared with 128K for Mellum2-12B-A2.5B-Thinking.
Kimi K2.5 is ahead on BenchLM's provisional leaderboard, 64 to 59. The biggest single separator in this matchup is GPQA, where the scores are 87.6% and 57.6%.
Kimi K2.5 has the edge for knowledge tasks in this comparison, averaging 65.1 versus 57.6. 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 64.2. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
Kimi K2.5 has the edge for instruction following in this comparison, averaging 93.9 versus 76.5. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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