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 58. 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 23.1. The single biggest benchmark swing on the page is AIME 2024, 73 to 23.1. GPT-4.1 mini does hit back in knowledge, 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 $0.40 input / $1.60 output per 1M tokens for GPT-4.1 mini. GPT-4.1 mini 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 mini only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Seed-2.0-Lite
55.1
GPT-4.1 mini
56.5
Seed-2.0-Lite
41.4
GPT-4.1 mini
28.8
Seed-2.0-Lite
79.6
GPT-4.1 mini
69.6
Seed-2.0-Lite
73
GPT-4.1 mini
80.9
Seed-2.0-Lite
53.9
GPT-4.1 mini
62.4
Seed-2.0-Lite
89
GPT-4.1 mini
88.5
Seed-2.0-Lite
82.5
GPT-4.1 mini
72
Seed-2.0-Lite
75
GPT-4.1 mini
23.1
Seed-2.0-Lite is ahead overall, 63 to 58. The biggest single separator in this matchup is AIME 2024, where the scores are 73 and 23.1.
GPT-4.1 mini has the edge for knowledge tasks in this comparison, averaging 62.4 versus 53.9. Inside this category, MMLU 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 28.8. Inside this category, SWE-bench Verified 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 23.1. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
GPT-4.1 mini has the edge for reasoning in this comparison, averaging 80.9 versus 73. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
GPT-4.1 mini has the edge for agentic tasks in this comparison, averaging 56.5 versus 55.1. Inside this category, BrowseComp 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 69.6. 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 88.5. 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 72. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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