Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Seed 1.6 has the cleaner overall profile here, landing at 65 versus 62. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Seed 1.6'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 1.6 is the reasoning model in the pair, while DeepSeek LLM 2.0 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 1.6 gives you the larger context window at 256K, compared with 128K for DeepSeek LLM 2.0.
Pick Seed 1.6 if you want the stronger benchmark profile. DeepSeek LLM 2.0 only becomes the better choice if mathematics is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Seed 1.6
62.3
DeepSeek LLM 2.0
57.9
Seed 1.6
42.4
DeepSeek LLM 2.0
42.9
Seed 1.6
79.6
DeepSeek LLM 2.0
64.5
Seed 1.6
74.5
DeepSeek LLM 2.0
73.6
Seed 1.6
56.4
DeepSeek LLM 2.0
57.5
Seed 1.6
87
DeepSeek LLM 2.0
85
Seed 1.6
83.4
DeepSeek LLM 2.0
78.8
Seed 1.6
75.9
DeepSeek LLM 2.0
80.8
Seed 1.6 is ahead overall, 65 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 56.4. 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 42.4. 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 75.9. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Seed 1.6 has the edge for reasoning in this comparison, averaging 74.5 versus 73.6. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
Seed 1.6 has the edge for agentic tasks in this comparison, averaging 62.3 versus 57.9. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Seed 1.6 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 1.6 has the edge for instruction following in this comparison, averaging 87 versus 85. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Seed 1.6 has the edge for multilingual tasks in this comparison, averaging 83.4 versus 78.8. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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