Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5 mini is clearly ahead on the aggregate, 69 to 65. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5 mini's sharpest advantage is in multimodal & grounded, where it averages 83.8 against 68.3. The single biggest benchmark swing on the page is MMMU-Pro, 86 to 66. Mercury 2 does hit back in instruction following, so the answer changes if that is the part of the workload you care about most.
Pick GPT-5 mini if you want the stronger benchmark profile. Mercury 2 only becomes the better choice if instruction following is the priority.
GPT-5 mini
65.7
Mercury 2
63.7
GPT-5 mini
42.8
Mercury 2
41.1
GPT-5 mini
83.8
Mercury 2
68.3
GPT-5 mini
81.8
Mercury 2
80.1
GPT-5 mini
62.8
Mercury 2
57.2
GPT-5 mini
82
Mercury 2
84
GPT-5 mini
80.1
Mercury 2
79.7
GPT-5 mini
87.2
Mercury 2
80.9
GPT-5 mini is ahead overall, 69 to 65. The biggest single separator in this matchup is MMMU-Pro, where the scores are 86 and 66.
GPT-5 mini has the edge for knowledge tasks in this comparison, averaging 62.8 versus 57.2. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-5 mini has the edge for coding in this comparison, averaging 42.8 versus 41.1. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
GPT-5 mini has the edge for math in this comparison, averaging 87.2 versus 80.9. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
GPT-5 mini has the edge for reasoning in this comparison, averaging 81.8 versus 80.1. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
GPT-5 mini has the edge for agentic tasks in this comparison, averaging 65.7 versus 63.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5 mini has the edge for multimodal and grounded tasks in this comparison, averaging 83.8 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 82. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5 mini has the edge for multilingual tasks in this comparison, averaging 80.1 versus 79.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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