Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemini 3.1 Pro is clearly ahead on the aggregate, 84 to 65. 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 coding, where it averages 71.9 against 41.1. The single biggest benchmark swing on the page is LiveCodeBench, 71 to 38.
Gemini 3.1 Pro is also the more expensive model on tokens at $1.25 input / $5.00 output per 1M tokens, versus $0.25 input / $0.75 output per 1M tokens for Mercury 2. That is roughly 6.7x on output cost alone. Mercury 2 is the reasoning model in the pair, while Gemini 3.1 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 3.1 Pro gives you the larger context window at 1M, compared with 128K for Mercury 2.
Pick Gemini 3.1 Pro if you want the stronger benchmark profile. Mercury 2 only becomes the better choice if you want the cheaper token bill or you want the stronger reasoning-first profile.
Gemini 3.1 Pro
76.1
Mercury 2
63.7
Gemini 3.1 Pro
71.9
Mercury 2
41.1
Gemini 3.1 Pro
95
Mercury 2
68.3
Gemini 3.1 Pro
92.7
Mercury 2
80.1
Gemini 3.1 Pro
79.4
Mercury 2
57.2
Gemini 3.1 Pro
95
Mercury 2
84
Gemini 3.1 Pro
94.1
Mercury 2
79.7
Gemini 3.1 Pro
96.8
Mercury 2
80.9
Gemini 3.1 Pro is ahead overall, 84 to 65. The biggest single separator in this matchup is LiveCodeBench, where the scores are 71 and 38.
Gemini 3.1 Pro has the edge for knowledge tasks in this comparison, averaging 79.4 versus 57.2. Inside this category, HLE is the benchmark that creates the most daylight between them.
Gemini 3.1 Pro has the edge for coding in this comparison, averaging 71.9 versus 41.1. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
Gemini 3.1 Pro has the edge for math in this comparison, averaging 96.8 versus 80.9. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Gemini 3.1 Pro has the edge for reasoning in this comparison, averaging 92.7 versus 80.1. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
Gemini 3.1 Pro has the edge for agentic tasks in this comparison, averaging 76.1 versus 63.7. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
Gemini 3.1 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 95 versus 68.3. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Gemini 3.1 Pro has the edge for instruction following in this comparison, averaging 95 versus 84. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Gemini 3.1 Pro has the edge for multilingual tasks in this comparison, averaging 94.1 versus 79.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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