Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
o1 is clearly ahead on the aggregate, 68 to 63. 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 53.9. The single biggest benchmark swing on the page is MMLU, 91.8 to 71. Seed-2.0-Lite 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 $0.25 input / $2.00 output per 1M tokens for Seed-2.0-Lite. That is roughly 30.0x on output cost alone. o1 is the reasoning model in the pair, while Seed-2.0-Lite 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-Lite 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-Lite only becomes the better choice if multimodal & grounded is the priority or you want the cheaper token bill.
o1
65.4
Seed-2.0-Lite
55.1
o1
48.4
Seed-2.0-Lite
41.4
o1
70.7
Seed-2.0-Lite
79.6
o1
78.1
Seed-2.0-Lite
73
o1
69.6
Seed-2.0-Lite
53.9
o1
92.2
Seed-2.0-Lite
89
o1
77
Seed-2.0-Lite
82.5
o1
74.3
Seed-2.0-Lite
75
o1 is ahead overall, 68 to 63. The biggest single separator in this matchup is MMLU, where the scores are 91.8 and 71.
o1 has the edge for knowledge tasks in this comparison, averaging 69.6 versus 53.9. 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 41.4. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
Seed-2.0-Lite has the edge for math in this comparison, averaging 75 versus 74.3. 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 73. 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 55.1. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Seed-2.0-Lite has the edge for multimodal and grounded tasks in this comparison, averaging 79.6 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 89. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Seed-2.0-Lite has the edge for multilingual tasks in this comparison, averaging 82.5 versus 77. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
Get notified when new models drop, benchmark scores change, or the leaderboard shifts. One email per week.
Free. No spam. Unsubscribe anytime. We only store derived location metadata for consent routing.