Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemma 4 12B
53
LFM2.5-VL-450M
0
Pick Gemma 4 12B if you want the stronger benchmark profile. LFM2.5-VL-450M only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Knowledge
+56.2 difference
Gemma 4 12B
LFM2.5-VL-450M
N/A
$0 / $0
N/A
N/A
N/A
N/A
256K
128K
Pick Gemma 4 12B if you want the stronger benchmark profile. LFM2.5-VL-450M only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Gemma 4 12B is clearly ahead on the provisional aggregate, 53 to 0. 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 21.6. The single biggest benchmark swing on the page is MMLU-Pro, 77.2% to 19.3%.
Gemma 4 12B is the reasoning model in the pair, while LFM2.5-VL-450M 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 LFM2.5-VL-450M.
Gemma 4 12B is ahead on BenchLM's provisional leaderboard, 53 to 0. The biggest single separator in this matchup is MMLU-Pro, where the scores are 77.2% and 19.3%.
Gemma 4 12B has the edge for knowledge tasks in this comparison, averaging 77.8 versus 21.6. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
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