Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemini 2.5 Pro
65
Gemma 4 31B
65
Treat this as a split decision. Gemini 2.5 Pro makes more sense if coding is the priority or you need the larger 1M context window; Gemma 4 31B is the better fit if knowledge is the priority or you want the cheaper token bill.
Coding
+22.2 difference
Knowledge
+20.5 difference
Gemini 2.5 Pro
Gemma 4 31B
$1.25 / $10
$0 / $0
117 t/s
N/A
21.19s
N/A
1M
256K
Treat this as a split decision. Gemini 2.5 Pro makes more sense if coding is the priority or you need the larger 1M context window; Gemma 4 31B is the better fit if knowledge is the priority or you want the cheaper token bill.
Gemini 2.5 Pro and Gemma 4 31B finish on the same provisional overall score, so this is less about a single winner and more about where the edge shows up. The provisional headline says tie; the benchmark table is where the real choice happens.
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 31B. That is roughly Infinityx on output cost alone. Gemma 4 31B 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 256K for Gemma 4 31B.
Gemini 2.5 Pro and Gemma 4 31B are tied on the provisional overall score, so the right pick depends on which category matters most for your use case.
Gemma 4 31B has the edge for knowledge tasks in this comparison, averaging 61.3 versus 40.8. Inside this category, HLE is the benchmark that creates the most daylight between them.
Gemini 2.5 Pro has the edge for coding in this comparison, averaging 63.8 versus 41.6. Gemma 4 31B stays close enough that the answer can still flip depending on your workload.
Estimates at 50,000 req/day · 1000 tokens/req average.
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