Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Gemini 3.1 Pro is clearly ahead on the aggregate, 89 to 32. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemini 3.1 Pro's sharpest advantage is in knowledge, where it averages 86 against 73.7. The single biggest benchmark swing on the page is MMLU, 99 to 73.7.
Gemini 3.1 Pro is also the more expensive model on tokens at $1.25 input / $5.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for DBRX Instruct. That is roughly Infinityx on output cost alone. Gemini 3.1 Pro gives you the larger context window at 1M, compared with 32K for DBRX Instruct.
Pick Gemini 3.1 Pro if you want the stronger benchmark profile. DBRX Instruct only becomes the better choice if you want the cheaper token bill.
Gemini 3.1 Pro
86
DBRX Instruct
73.7
Gemini 3.1 Pro
79
DBRX Instruct
70.1
Gemini 3.1 Pro is ahead overall, 89 to 32. The biggest single separator in this matchup is MMLU, where the scores are 99 and 73.7.
Gemini 3.1 Pro has the edge for knowledge tasks in this comparison, averaging 86 versus 73.7. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Gemini 3.1 Pro has the edge for coding in this comparison, averaging 79 versus 70.1. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
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