Head-to-head comparison across 4benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemma 4 12B
53
Qwen3.5 397B
63
Verified leaderboard positions: Gemma 4 12B unranked · Qwen3.5 397B #20
Pick Qwen3.5 397B if you want the stronger benchmark profile. Gemma 4 12B only becomes the better choice if knowledge is the priority or you need the larger 256K context window.
Coding
+11.7 difference
Reasoning
+19.8 difference
Knowledge
+12.6 difference
Multimodal
+10.5 difference
Gemma 4 12B
Qwen3.5 397B
N/A
$0.6 / $3.6
N/A
96 t/s
N/A
2.44s
256K
128K
Pick Qwen3.5 397B if you want the stronger benchmark profile. Gemma 4 12B only becomes the better choice if knowledge is the priority or you need the larger 256K context window.
Qwen3.5 397B is clearly ahead on the provisional aggregate, 63 to 53. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.5 397B's sharpest advantage is in reasoning, where it averages 63.2 against 43.4. The single biggest benchmark swing on the page is MMLU-Pro, 77.2% to 87.8%. 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 Qwen3.5 397B 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. Gemma 4 12B gives you the larger context window at 256K, compared with 128K for Qwen3.5 397B.
Qwen3.5 397B is ahead on BenchLM's provisional leaderboard, 63 to 53. The biggest single separator in this matchup is MMLU-Pro, where the scores are 77.2% and 87.8%.
Gemma 4 12B has the edge for knowledge tasks in this comparison, averaging 77.8 versus 65.2. 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 60.3. Qwen3.5 397B stays close enough that the answer can still flip depending on your workload.
Qwen3.5 397B has the edge for reasoning in this comparison, averaging 63.2 versus 43.4. Gemma 4 12B stays close enough that the answer can still flip depending on your workload.
Qwen3.5 397B has the edge for multimodal and grounded tasks in this comparison, averaging 79.6 versus 69.1. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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