Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemma 4 26B A4B
55
o3-mini
56
Pick o3-mini if you want the stronger benchmark profile. Gemma 4 26B A4B only becomes the better choice if you want the cheaper token bill or you need the larger 256K context window.
Knowledge
+28.0 difference
Gemma 4 26B A4B
o3-mini
$0 / $0
$1.1 / $4.4
N/A
160 t/s
N/A
7.12s
256K
200K
Pick o3-mini if you want the stronger benchmark profile. Gemma 4 26B A4B only becomes the better choice if you want the cheaper token bill or you need the larger 256K context window.
o3-mini finishes one point ahead on BenchLM's provisional leaderboard, 56 to 55. 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.
o3-mini's sharpest advantage is in knowledge, where it averages 77.2 against 49.2.
o3-mini is also the more expensive model on tokens at $1.10 input / $4.40 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Gemma 4 26B A4B. That is roughly Infinityx on output cost alone. Gemma 4 26B A4B gives you the larger context window at 256K, compared with 200K for o3-mini.
o3-mini is ahead on BenchLM's provisional leaderboard, 56 to 55.
o3-mini has the edge for knowledge tasks in this comparison, averaging 77.2 versus 49.2. Gemma 4 26B A4B stays close enough that the answer can still flip depending on your workload.
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