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 53. 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 mathematics, where it averages 87.2 against 65.1. The single biggest benchmark swing on the page is AIME 2023, 90 to 62.
GPT-5 mini 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. Seed-2.0-Mini gives you the larger context window at 256K, compared with 128K for GPT-5 mini.
Pick GPT-5 mini if you want the stronger benchmark profile. Seed-2.0-Mini only becomes the better choice if you need the larger 256K context window or you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5 mini
65.7
Seed-2.0-Mini
46.2
GPT-5 mini
42.8
Seed-2.0-Mini
24.7
GPT-5 mini
83.8
Seed-2.0-Mini
73.1
GPT-5 mini
81.8
Seed-2.0-Mini
64.8
GPT-5 mini
62.8
Seed-2.0-Mini
44.6
GPT-5 mini
82
Seed-2.0-Mini
80
GPT-5 mini
80.1
Seed-2.0-Mini
71.8
GPT-5 mini
87.2
Seed-2.0-Mini
65.1
GPT-5 mini is ahead overall, 69 to 53. The biggest single separator in this matchup is AIME 2023, where the scores are 90 and 62.
GPT-5 mini has the edge for knowledge tasks in this comparison, averaging 62.8 versus 44.6. 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 24.7. Inside this category, HumanEval 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 65.1. 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 64.8. Inside this category, SimpleQA 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 46.2. 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 73.1. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-5 mini has the edge for instruction following in this comparison, averaging 82 versus 80. 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 71.8. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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