Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemma 4 12B
53
MiniMax M3
76
Verified leaderboard positions: Gemma 4 12B unranked · MiniMax M3 #13
Pick MiniMax M3 if you want the stronger benchmark profile. Gemma 4 12B only becomes the better choice if coding is the priority or you want the stronger reasoning-first profile.
Coding
+5.0 difference
Multimodal
+4.2 difference
Gemma 4 12B
MiniMax M3
N/A
$0.3 / $1.2
N/A
N/A
N/A
N/A
256K
1M
Pick MiniMax M3 if you want the stronger benchmark profile. Gemma 4 12B only becomes the better choice if coding is the priority or you want the stronger reasoning-first profile.
MiniMax M3 is clearly ahead on the provisional aggregate, 76 to 53. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemma 4 12B is the reasoning model in the pair, while MiniMax M3 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. MiniMax M3 gives you the larger context window at 1M, compared with 256K for Gemma 4 12B.
MiniMax M3 is ahead on BenchLM's provisional leaderboard, 76 to 53. The biggest single separator in this matchup is MMMU-Pro, where the scores are 69.1% and 78.1%.
Gemma 4 12B has the edge for coding in this comparison, averaging 72 versus 67. MiniMax M3 stays close enough that the answer can still flip depending on your workload.
Gemma 4 12B has the edge for multimodal and grounded tasks in this comparison, averaging 69.1 versus 64.9. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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