Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V4 Pro Base
41
Gemma 4 12B
53
Pick Gemma 4 12B if you want the stronger benchmark profile. DeepSeek V4 Pro Base only becomes the better choice if reasoning is the priority or you need the larger 1M context window.
Reasoning
+8.1 difference
Knowledge
+14.4 difference
DeepSeek V4 Pro Base
Gemma 4 12B
$null / $null
N/A
N/A
N/A
N/A
N/A
1M
256K
Pick Gemma 4 12B if you want the stronger benchmark profile. DeepSeek V4 Pro Base only becomes the better choice if reasoning is the priority or you need the larger 1M context window.
Gemma 4 12B is clearly ahead on the provisional aggregate, 53 to 41. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemma 4 12B's sharpest advantage is in knowledge, where it averages 77.8 against 63.4. The single biggest benchmark swing on the page is MMLU-Pro, 73.5% to 77.2%. DeepSeek V4 Pro Base does hit back in reasoning, 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 DeepSeek V4 Pro Base 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. DeepSeek V4 Pro Base gives you the larger context window at 1M, compared with 256K for Gemma 4 12B.
Gemma 4 12B is ahead on BenchLM's provisional leaderboard, 53 to 41. The biggest single separator in this matchup is MMLU-Pro, where the scores are 73.5% and 77.2%.
Gemma 4 12B has the edge for knowledge tasks in this comparison, averaging 77.8 versus 63.4. Inside this category, MMMLU is the benchmark that creates the most daylight between them.
DeepSeek V4 Pro Base has the edge for reasoning in this comparison, averaging 51.5 versus 43.4. Inside this category, BBH is the benchmark that creates the most daylight between them.
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