Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemini 2.5 Pro
64
Gemma 4 E2B
23
Pick Gemini 2.5 Pro if you want the stronger benchmark profile. Gemma 4 E2B only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Knowledge
+13.3 difference
Gemini 2.5 Pro
Gemma 4 E2B
$1.25 / $10
$0 / $0
117 t/s
N/A
21.19s
N/A
1M
128K
Pick Gemini 2.5 Pro if you want the stronger benchmark profile. Gemma 4 E2B only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Gemini 2.5 Pro is clearly ahead on the provisional aggregate, 64 to 23. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemini 2.5 Pro is also the more expensive model on tokens at $1.25 input / $10.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Gemma 4 E2B. That is roughly Infinityx on output cost alone. Gemma 4 E2B is the reasoning model in the pair, while Gemini 2.5 Pro 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. Gemini 2.5 Pro gives you the larger context window at 1M, compared with 128K for Gemma 4 E2B.
Gemini 2.5 Pro is ahead on BenchLM's provisional leaderboard, 64 to 23. The biggest single separator in this matchup is GPQA, where the scores are 83% and 43.4%.
Gemma 4 E2B has the edge for knowledge tasks in this comparison, averaging 54.1 versus 40.8. Inside this category, GPQA is the benchmark that creates the most daylight between them.
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