Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Seed-2.0-Lite is clearly ahead on the aggregate, 63 to 49. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Seed-2.0-Lite's sharpest advantage is in mathematics, where it averages 75 against 9.8. The single biggest benchmark swing on the page is AIME 2024, 73 to 9.8. GPT-4.1 nano does hit back in reasoning, so the answer changes if that is the part of the workload you care about most.
Seed-2.0-Lite is also the more expensive model on tokens at $0.25 input / $2.00 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for GPT-4.1 nano. That is roughly 5.0x on output cost alone. GPT-4.1 nano gives you the larger context window at 1M, compared with 256K for Seed-2.0-Lite.
Pick Seed-2.0-Lite if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if reasoning is the priority or you want the cheaper token bill.
Seed-2.0-Lite
55.1
GPT-4.1 nano
47.4
Seed-2.0-Lite
41.4
GPT-4.1 nano
18
Seed-2.0-Lite
79.6
GPT-4.1 nano
59.3
Seed-2.0-Lite
73
GPT-4.1 nano
74.1
Seed-2.0-Lite
53.9
GPT-4.1 nano
50.7
Seed-2.0-Lite
89
GPT-4.1 nano
83.2
Seed-2.0-Lite
82.5
GPT-4.1 nano
59
Seed-2.0-Lite
75
GPT-4.1 nano
9.8
Seed-2.0-Lite is ahead overall, 63 to 49. The biggest single separator in this matchup is AIME 2024, where the scores are 73 and 9.8.
Seed-2.0-Lite has the edge for knowledge tasks in this comparison, averaging 53.9 versus 50.7. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Seed-2.0-Lite has the edge for coding in this comparison, averaging 41.4 versus 18. 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 9.8. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
GPT-4.1 nano has the edge for reasoning in this comparison, averaging 74.1 versus 73. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
Seed-2.0-Lite has the edge for agentic tasks in this comparison, averaging 55.1 versus 47.4. Inside this category, OSWorld-Verified 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 59.3. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Seed-2.0-Lite has the edge for instruction following in this comparison, averaging 89 versus 83.2. 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 59. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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