Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Mercury 2 is clearly ahead on the aggregate, 65 to 58. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Mercury 2's sharpest advantage is in mathematics, where it averages 80.9 against 23.1. The single biggest benchmark swing on the page is AIME 2024, 83 to 23.1. GPT-4.1 mini does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
GPT-4.1 mini is also the more expensive model on tokens at $0.40 input / $1.60 output per 1M tokens, versus $0.25 input / $0.75 output per 1M tokens for Mercury 2. That is roughly 2.1x on output cost alone. Mercury 2 is the reasoning model in the pair, while GPT-4.1 mini 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. GPT-4.1 mini gives you the larger context window at 1M, compared with 128K for Mercury 2.
Pick Mercury 2 if you want the stronger benchmark profile. GPT-4.1 mini only becomes the better choice if knowledge is the priority or you need the larger 1M context window.
Mercury 2
63.7
GPT-4.1 mini
56.5
Mercury 2
41.1
GPT-4.1 mini
28.8
Mercury 2
68.3
GPT-4.1 mini
69.6
Mercury 2
80.1
GPT-4.1 mini
80.9
Mercury 2
57.2
GPT-4.1 mini
62.4
Mercury 2
84
GPT-4.1 mini
88.5
Mercury 2
79.7
GPT-4.1 mini
72
Mercury 2
80.9
GPT-4.1 mini
23.1
Mercury 2 is ahead overall, 65 to 58. The biggest single separator in this matchup is AIME 2024, where the scores are 83 and 23.1.
GPT-4.1 mini has the edge for knowledge tasks in this comparison, averaging 62.4 versus 57.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Mercury 2 has the edge for coding in this comparison, averaging 41.1 versus 28.8. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Mercury 2 has the edge for math in this comparison, averaging 80.9 versus 23.1. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
GPT-4.1 mini has the edge for reasoning in this comparison, averaging 80.9 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 56.5. Inside this category, OSWorld-Verified is the benchmark that creates the most daylight between them.
GPT-4.1 mini has the edge for multimodal and grounded tasks in this comparison, averaging 69.6 versus 68.3. Inside this category, OfficeQA Pro is the benchmark that creates the most daylight between them.
GPT-4.1 mini has the edge for instruction following in this comparison, averaging 88.5 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 72. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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