Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.1 is clearly ahead on the aggregate, 80 to 65. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.1's sharpest advantage is in coding, where it averages 66.2 against 41.1. The single biggest benchmark swing on the page is SWE-bench Pro, 71 to 43.
GPT-5.1 is also the more expensive model on tokens at $1.50 input / $6.00 output per 1M tokens, versus $0.25 input / $0.75 output per 1M tokens for Mercury 2. That is roughly 8.0x on output cost alone. GPT-5.1 gives you the larger context window at 200K, compared with 128K for Mercury 2.
Pick GPT-5.1 if you want the stronger benchmark profile. Mercury 2 only becomes the better choice if you want the cheaper token bill.
GPT-5.1
75.8
Mercury 2
63.7
GPT-5.1
66.2
Mercury 2
41.1
GPT-5.1
91.8
Mercury 2
68.3
GPT-5.1
88.4
Mercury 2
80.1
GPT-5.1
72.5
Mercury 2
57.2
GPT-5.1
89
Mercury 2
84
GPT-5.1
87.7
Mercury 2
79.7
GPT-5.1
95.4
Mercury 2
80.9
GPT-5.1 is ahead overall, 80 to 65. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 71 and 43.
GPT-5.1 has the edge for knowledge tasks in this comparison, averaging 72.5 versus 57.2. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-5.1 has the edge for coding in this comparison, averaging 66.2 versus 41.1. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
GPT-5.1 has the edge for math in this comparison, averaging 95.4 versus 80.9. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
GPT-5.1 has the edge for reasoning in this comparison, averaging 88.4 versus 80.1. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
GPT-5.1 has the edge for agentic tasks in this comparison, averaging 75.8 versus 63.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5.1 has the edge for multimodal and grounded tasks in this comparison, averaging 91.8 versus 68.3. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-5.1 has the edge for instruction following in this comparison, averaging 89 versus 84. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5.1 has the edge for multilingual tasks in this comparison, averaging 87.7 versus 79.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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