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 43. 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 multimodal & grounded, where it averages 79.6 against 47.5. The single biggest benchmark swing on the page is MMMU-Pro, 80 to 43.
DeepSeek-R1 is also the more expensive model on tokens at $0.55 input / $2.19 output per 1M tokens, versus $0.25 input / $2.00 output per 1M tokens for Seed-2.0-Lite. DeepSeek-R1 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 128K for DeepSeek-R1.
Pick Seed-2.0-Lite if you want the stronger benchmark profile. DeepSeek-R1 only becomes the better choice if you want the stronger reasoning-first profile.
Seed-2.0-Lite
55.1
DeepSeek-R1
44.5
Seed-2.0-Lite
41.4
DeepSeek-R1
21.5
Seed-2.0-Lite
79.6
DeepSeek-R1
47.5
Seed-2.0-Lite
73
DeepSeek-R1
50.9
Seed-2.0-Lite
53.9
DeepSeek-R1
37.9
Seed-2.0-Lite
89
DeepSeek-R1
69
Seed-2.0-Lite
82.5
DeepSeek-R1
60.4
Seed-2.0-Lite
75
DeepSeek-R1
52.5
Seed-2.0-Lite is ahead overall, 63 to 43. The biggest single separator in this matchup is MMMU-Pro, where the scores are 80 and 43.
Seed-2.0-Lite has the edge for knowledge tasks in this comparison, averaging 53.9 versus 37.9. 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 21.5. 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 52.5. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Seed-2.0-Lite has the edge for reasoning in this comparison, averaging 73 versus 50.9. Inside this category, SimpleQA 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 44.5. 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 47.5. 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 69. 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 60.4. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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