Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemma 4 E2B
34
LFM2.5-VL-450M
33
Pick Gemma 4 E2B 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
+32.5 difference
Gemma 4 E2B
LFM2.5-VL-450M
$0 / $0
$0 / $0
N/A
N/A
N/A
N/A
128K
128K
Pick Gemma 4 E2B 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 E2B finishes one point ahead on BenchLM's provisional leaderboard, 34 to 33. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
Gemma 4 E2B's sharpest advantage is in knowledge, where it averages 54.1 against 21.6. The single biggest benchmark swing on the page is MMLU-Pro, 60% to 19.3%.
Gemma 4 E2B 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 E2B is ahead on BenchLM's provisional leaderboard, 34 to 33. The biggest single separator in this matchup is MMLU-Pro, where the scores are 60% and 19.3%.
Gemma 4 E2B has the edge for knowledge tasks in this comparison, averaging 54.1 versus 21.6. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
Get notified when new models drop, benchmark scores change, or the leaderboard shifts. One email per week.
Free. No spam. Unsubscribe anytime. We only store derived location metadata for consent routing.