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 53. 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 24.7. The single biggest benchmark swing on the page is SWE-bench Pro, 84 to 29.
GPT-5.1-Codex-Max is also the more expensive model on tokens at $2.00 input / $8.00 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for Seed-2.0-Mini. That is roughly 20.0x on output cost alone. GPT-5.1-Codex-Max is the reasoning model in the pair, while Seed-2.0-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-5.1-Codex-Max gives you the larger context window at 400K, compared with 256K for Seed-2.0-Mini.
Pick GPT-5.1-Codex-Max if you want the stronger benchmark profile. Seed-2.0-Mini only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5.1-Codex-Max
86
Seed-2.0-Mini
46.2
GPT-5.1-Codex-Max
75.5
Seed-2.0-Mini
24.7
GPT-5.1-Codex-Max
88.2
Seed-2.0-Mini
73.1
GPT-5.1-Codex-Max
92.1
Seed-2.0-Mini
64.8
GPT-5.1-Codex-Max
72.6
Seed-2.0-Mini
44.6
GPT-5.1-Codex-Max
91
Seed-2.0-Mini
80
GPT-5.1-Codex-Max
87.7
Seed-2.0-Mini
71.8
GPT-5.1-Codex-Max
94.9
Seed-2.0-Mini
65.1
GPT-5.1-Codex-Max is ahead overall, 84 to 53. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 84 and 29.
GPT-5.1-Codex-Max has the edge for knowledge tasks in this comparison, averaging 72.6 versus 44.6. 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 24.7. 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 65.1. 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 64.8. Inside this category, SimpleQA 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 46.2. 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 73.1. 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 80. 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 71.8. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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