Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemini 3.1 Flash-Lite
48
Gemma 4 26B A4B
55
Pick Gemma 4 26B A4B if you want the stronger benchmark profile. Gemini 3.1 Flash-Lite only becomes the better choice if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model.
Multimodal
+0.6 difference
Gemini 3.1 Flash-Lite
Gemma 4 26B A4B
$0.25 / $1.5
$0 / $0
205 t/s
N/A
7.50s
N/A
1M
256K
Pick Gemma 4 26B A4B if you want the stronger benchmark profile. Gemini 3.1 Flash-Lite only becomes the better choice if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model.
Gemma 4 26B A4B is clearly ahead on the provisional aggregate, 55 to 48. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemma 4 26B A4B's sharpest advantage is in multimodal & grounded, where it averages 73.8 against 73.2.
Gemini 3.1 Flash-Lite is also the more expensive model on tokens at $0.25 input / $1.50 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 is the reasoning model in the pair, while Gemini 3.1 Flash-Lite 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 3.1 Flash-Lite gives you the larger context window at 1M, compared with 256K for Gemma 4 26B A4B.
Gemma 4 26B A4B is ahead on BenchLM's provisional leaderboard, 55 to 48.
Gemma 4 26B A4B has the edge for multimodal and grounded tasks in this comparison, averaging 73.8 versus 73.2. Gemini 3.1 Flash-Lite stays close enough that the answer can still flip depending on your workload.
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