Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Seed-2.0-Lite finishes one point ahead overall, 63 to 62. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
Seed-2.0-Lite's sharpest advantage is in multimodal & grounded, where it averages 79.6 against 64.5. The single biggest benchmark swing on the page is MMMU-Pro, 80 to 60. DeepSeek LLM 2.0 does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.
Seed-2.0-Lite gives you the larger context window at 256K, compared with 128K for DeepSeek LLM 2.0.
Pick Seed-2.0-Lite if you want the stronger benchmark profile. DeepSeek LLM 2.0 only becomes the better choice if mathematics is the priority.
Seed-2.0-Lite
55.1
DeepSeek LLM 2.0
57.9
Seed-2.0-Lite
41.4
DeepSeek LLM 2.0
42.9
Seed-2.0-Lite
79.6
DeepSeek LLM 2.0
64.5
Seed-2.0-Lite
73
DeepSeek LLM 2.0
73.6
Seed-2.0-Lite
53.9
DeepSeek LLM 2.0
57.5
Seed-2.0-Lite
89
DeepSeek LLM 2.0
85
Seed-2.0-Lite
82.5
DeepSeek LLM 2.0
78.8
Seed-2.0-Lite
75
DeepSeek LLM 2.0
80.8
Seed-2.0-Lite is ahead overall, 63 to 62. The biggest single separator in this matchup is MMMU-Pro, where the scores are 80 and 60.
DeepSeek LLM 2.0 has the edge for knowledge tasks in this comparison, averaging 57.5 versus 53.9. Inside this category, MMLU is the benchmark that creates the most daylight between them.
DeepSeek LLM 2.0 has the edge for coding in this comparison, averaging 42.9 versus 41.4. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
DeepSeek LLM 2.0 has the edge for math in this comparison, averaging 80.8 versus 75. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
DeepSeek LLM 2.0 has the edge for reasoning in this comparison, averaging 73.6 versus 73. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
DeepSeek LLM 2.0 has the edge for agentic tasks in this comparison, averaging 57.9 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 64.5. 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 85. 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 78.8. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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