Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
o3-mini is clearly ahead on the aggregate, 71 to 65. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
o3-mini's sharpest advantage is in coding, where it averages 55.6 against 41.1. The single biggest benchmark swing on the page is SWE-bench Pro, 57 to 43. Mercury 2 does hit back in multilingual, so the answer changes if that is the part of the workload you care about most.
o3-mini is also the more expensive model on tokens at $1.10 input / $4.40 output per 1M tokens, versus $0.25 input / $0.75 output per 1M tokens for Mercury 2. That is roughly 5.9x on output cost alone. o3-mini gives you the larger context window at 200K, compared with 128K for Mercury 2.
Pick o3-mini if you want the stronger benchmark profile. Mercury 2 only becomes the better choice if multilingual is the priority or you want the cheaper token bill.
o3-mini
66.6
Mercury 2
63.7
o3-mini
55.6
Mercury 2
41.1
o3-mini
74.4
Mercury 2
68.3
o3-mini
81.1
Mercury 2
80.1
o3-mini
70.8
Mercury 2
57.2
o3-mini
93.9
Mercury 2
84
o3-mini
73
Mercury 2
79.7
o3-mini
87.3
Mercury 2
80.9
o3-mini is ahead overall, 71 to 65. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 57 and 43.
o3-mini has the edge for knowledge tasks in this comparison, averaging 70.8 versus 57.2. Inside this category, MMLU is the benchmark that creates the most daylight between them.
o3-mini has the edge for coding in this comparison, averaging 55.6 versus 41.1. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
o3-mini has the edge for math in this comparison, averaging 87.3 versus 80.9. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
o3-mini has the edge for reasoning in this comparison, averaging 81.1 versus 80.1. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
o3-mini has the edge for agentic tasks in this comparison, averaging 66.6 versus 63.7. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
o3-mini has the edge for multimodal and grounded tasks in this comparison, averaging 74.4 versus 68.3. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
o3-mini has the edge for instruction following in this comparison, averaging 93.9 versus 84. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Mercury 2 has the edge for multilingual tasks in this comparison, averaging 79.7 versus 73. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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