Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.1-Codex-Max is clearly ahead on the aggregate, 84 to 65. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.1-Codex-Max's sharpest advantage is in coding, where it averages 75.5 against 41.1. The single biggest benchmark swing on the page is SWE-bench Pro, 84 to 43.
GPT-5.1-Codex-Max is also the more expensive model on tokens at $2.00 input / $8.00 output per 1M tokens, versus $0.25 input / $0.75 output per 1M tokens for Mercury 2. That is roughly 10.7x on output cost alone. GPT-5.1-Codex-Max gives you the larger context window at 400K, compared with 128K for Mercury 2.
Pick GPT-5.1-Codex-Max if you want the stronger benchmark profile. Mercury 2 only becomes the better choice if you want the cheaper token bill.
GPT-5.1-Codex-Max
86
Mercury 2
63.7
GPT-5.1-Codex-Max
75.5
Mercury 2
41.1
GPT-5.1-Codex-Max
88.2
Mercury 2
68.3
GPT-5.1-Codex-Max
92.1
Mercury 2
80.1
GPT-5.1-Codex-Max
72.6
Mercury 2
57.2
GPT-5.1-Codex-Max
91
Mercury 2
84
GPT-5.1-Codex-Max
87.7
Mercury 2
79.7
GPT-5.1-Codex-Max
94.9
Mercury 2
80.9
GPT-5.1-Codex-Max is ahead overall, 84 to 65. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 84 and 43.
GPT-5.1-Codex-Max has the edge for knowledge tasks in this comparison, averaging 72.6 versus 57.2. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-5.1-Codex-Max has the edge for coding in this comparison, averaging 75.5 versus 41.1. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
GPT-5.1-Codex-Max has the edge for math in this comparison, averaging 94.9 versus 80.9. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
GPT-5.1-Codex-Max has the edge for reasoning in this comparison, averaging 92.1 versus 80.1. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
GPT-5.1-Codex-Max has the edge for agentic tasks in this comparison, averaging 86 versus 63.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5.1-Codex-Max has the edge for multimodal and grounded tasks in this comparison, averaging 88.2 versus 68.3. Inside this category, OfficeQA Pro is the benchmark that creates the most daylight between them.
GPT-5.1-Codex-Max has the edge for instruction following in this comparison, averaging 91 versus 84. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5.1-Codex-Max 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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