Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
o1 is clearly ahead on the aggregate, 68 to 53. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
o1's sharpest advantage is in knowledge, where it averages 69.6 against 44.6. The single biggest benchmark swing on the page is MMLU, 91.8 to 62. Seed-2.0-Mini does hit back in multimodal & grounded, so the answer changes if that is the part of the workload you care about most.
o1 is also the more expensive model on tokens at $15.00 input / $60.00 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for Seed-2.0-Mini. That is roughly 150.0x on output cost alone. o1 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 200K for o1.
Pick o1 if you want the stronger benchmark profile. Seed-2.0-Mini only becomes the better choice if multimodal & grounded is the priority or you want the cheaper token bill.
o1
65.4
Seed-2.0-Mini
46.2
o1
48.4
Seed-2.0-Mini
24.7
o1
70.7
Seed-2.0-Mini
73.1
o1
78.1
Seed-2.0-Mini
64.8
o1
69.6
Seed-2.0-Mini
44.6
o1
92.2
Seed-2.0-Mini
80
o1
77
Seed-2.0-Mini
71.8
o1
74.3
Seed-2.0-Mini
65.1
o1 is ahead overall, 68 to 53. The biggest single separator in this matchup is MMLU, where the scores are 91.8 and 62.
o1 has the edge for knowledge tasks in this comparison, averaging 69.6 versus 44.6. Inside this category, MMLU is the benchmark that creates the most daylight between them.
o1 has the edge for coding in this comparison, averaging 48.4 versus 24.7. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
o1 has the edge for math in this comparison, averaging 74.3 versus 65.1. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
o1 has the edge for reasoning in this comparison, averaging 78.1 versus 64.8. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
o1 has the edge for agentic tasks in this comparison, averaging 65.4 versus 46.2. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Seed-2.0-Mini has the edge for multimodal and grounded tasks in this comparison, averaging 73.1 versus 70.7. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
o1 has the edge for instruction following in this comparison, averaging 92.2 versus 80. Inside this category, IFEval is the benchmark that creates the most daylight between them.
o1 has the edge for multilingual tasks in this comparison, averaging 77 versus 71.8. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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