Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemma 4 E4B
36
Kimi K2.5 (Reasoning)
76
Pick Kimi K2.5 (Reasoning) if you want the stronger benchmark profile. Gemma 4 E4B only becomes the better choice if you want the cheaper token bill.
Knowledge
+21.7 difference
Gemma 4 E4B
Kimi K2.5 (Reasoning)
$0 / $0
$0.6 / $3
N/A
N/A
N/A
N/A
128K
128K
Pick Kimi K2.5 (Reasoning) if you want the stronger benchmark profile. Gemma 4 E4B only becomes the better choice if you want the cheaper token bill.
Kimi K2.5 (Reasoning) is clearly ahead on the provisional aggregate, 76 to 36. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Kimi K2.5 (Reasoning)'s sharpest advantage is in knowledge, where it averages 87.3 against 65.6. The single biggest benchmark swing on the page is GPQA, 58.6% to 87.6%.
Kimi K2.5 (Reasoning) is also the more expensive model on tokens at $0.60 input / $3.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Gemma 4 E4B. That is roughly Infinityx on output cost alone.
Kimi K2.5 (Reasoning) is ahead on BenchLM's provisional leaderboard, 76 to 36. The biggest single separator in this matchup is GPQA, where the scores are 58.6% and 87.6%.
Kimi K2.5 (Reasoning) has the edge for knowledge tasks in this comparison, averaging 87.3 versus 65.6. Inside this category, GPQA is the benchmark that creates the most daylight between them.
For engineers, researchers, and the plain curious — a weekly brief on new models, ranking shifts, and pricing changes.
Free. No spam. Unsubscribe anytime.