Head-to-head comparison across 4benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemma 4 12B
53
Kimi K2.5
64
Verified leaderboard positions: Gemma 4 12B unranked · Kimi K2.5 #16
Pick Kimi K2.5 if you want the stronger benchmark profile. Gemma 4 12B only becomes the better choice if knowledge is the priority or you want the stronger reasoning-first profile.
Coding
+7.8 difference
Reasoning
+17.6 difference
Knowledge
+12.7 difference
Multimodal
+9.4 difference
Gemma 4 12B
Kimi K2.5
N/A
$0.6 / $3
N/A
45 t/s
N/A
2.38s
256K
256K
Pick Kimi K2.5 if you want the stronger benchmark profile. Gemma 4 12B only becomes the better choice if knowledge is the priority or you want the stronger reasoning-first profile.
Kimi K2.5 is clearly ahead on the provisional aggregate, 64 to 53. 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 reasoning, where it averages 61 against 43.4. The single biggest benchmark swing on the page is LiveCodeBench, 72% to 85%. Gemma 4 12B does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Gemma 4 12B 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 is ahead on BenchLM's provisional leaderboard, 64 to 53. The biggest single separator in this matchup is LiveCodeBench, where the scores are 72% and 85%.
Gemma 4 12B has the edge for knowledge tasks in this comparison, averaging 77.8 versus 65.1. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
Gemma 4 12B has the edge for coding in this comparison, averaging 72 versus 64.2. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
Kimi K2.5 has the edge for reasoning in this comparison, averaging 61 versus 43.4. Gemma 4 12B stays close enough that the answer can still flip depending on your workload.
Kimi K2.5 has the edge for multimodal and grounded tasks in this comparison, averaging 78.5 versus 69.1. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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