Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Seed 1.6 is clearly ahead on the aggregate, 65 to 59. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Seed 1.6's sharpest advantage is in multimodal & grounded, where it averages 79.6 against 62.3. The single biggest benchmark swing on the page is MMMU-Pro, 80 to 60.
Seed 1.6 is the reasoning model in the pair, while Llama 3.1 405B 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 Llama 3.1 405B.
Pick Seed 1.6 if you want the stronger benchmark profile. Llama 3.1 405B only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Seed 1.6
62.3
Llama 3.1 405B
53.9
Seed 1.6
42.4
Llama 3.1 405B
40.6
Seed 1.6
79.6
Llama 3.1 405B
62.3
Seed 1.6
74.5
Llama 3.1 405B
68.3
Seed 1.6
56.4
Llama 3.1 405B
53.2
Seed 1.6
87
Llama 3.1 405B
86
Seed 1.6
83.4
Llama 3.1 405B
80.1
Seed 1.6
75.9
Llama 3.1 405B
74.9
Seed 1.6 is ahead overall, 65 to 59. The biggest single separator in this matchup is MMMU-Pro, where the scores are 80 and 60.
Seed 1.6 has the edge for knowledge tasks in this comparison, averaging 56.4 versus 53.2. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
Seed 1.6 has the edge for coding in this comparison, averaging 42.4 versus 40.6. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
Seed 1.6 has the edge for math in this comparison, averaging 75.9 versus 74.9. 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 68.3. 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 53.9. 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 62.3. 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 86. 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 80.1. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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