Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemini 2.5 Pro has the cleaner overall profile here, landing at 67 versus 65. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Gemini 2.5 Pro's sharpest advantage is in multimodal & grounded, where it averages 85.1 against 68.3. The single biggest benchmark swing on the page is MMMU-Pro, 86 to 66. Mercury 2 does hit back in agentic, so the answer changes if that is the part of the workload you care about most.
Gemini 2.5 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 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 128K for Mercury 2.
Pick Gemini 2.5 Pro if you want the stronger benchmark profile. Mercury 2 only becomes the better choice if agentic is the priority or you want the cheaper token bill.
Gemini 2.5 Pro
61.7
Mercury 2
63.7
Gemini 2.5 Pro
41
Mercury 2
41.1
Gemini 2.5 Pro
85.1
Mercury 2
68.3
Gemini 2.5 Pro
80.7
Mercury 2
80.1
Gemini 2.5 Pro
58.4
Mercury 2
57.2
Gemini 2.5 Pro
83
Mercury 2
84
Gemini 2.5 Pro
82.7
Mercury 2
79.7
Gemini 2.5 Pro
83.5
Mercury 2
80.9
Gemini 2.5 Pro is ahead overall, 67 to 65. The biggest single separator in this matchup is MMMU-Pro, where the scores are 86 and 66.
Gemini 2.5 Pro has the edge for knowledge tasks in this comparison, averaging 58.4 versus 57.2. Inside this category, HLE is the benchmark that creates the most daylight between them.
Mercury 2 has the edge for coding in this comparison, averaging 41.1 versus 41. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Gemini 2.5 Pro has the edge for math in this comparison, averaging 83.5 versus 80.9. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Gemini 2.5 Pro has the edge for reasoning in this comparison, averaging 80.7 versus 80.1. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
Mercury 2 has the edge for agentic tasks in this comparison, averaging 63.7 versus 61.7. Inside this category, OSWorld-Verified is the benchmark that creates the most daylight between them.
Gemini 2.5 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 85.1 versus 68.3. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Mercury 2 has the edge for instruction following in this comparison, averaging 84 versus 83. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Gemini 2.5 Pro has the edge for multilingual tasks in this comparison, averaging 82.7 versus 79.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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