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 45. 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 52.3. The single biggest benchmark swing on the page is SWE-bench Verified, 46 to 9.
Seed 1.6 is the reasoning model in the pair, while Llama 3 70B 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 70B.
Pick Seed 1.6 if you want the stronger benchmark profile. Llama 3 70B 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 70B
41.2
Seed 1.6
42.4
Llama 3 70B
15.8
Seed 1.6
79.6
Llama 3 70B
52.3
Seed 1.6
74.5
Llama 3 70B
59.6
Seed 1.6
56.4
Llama 3 70B
42.2
Seed 1.6
87
Llama 3 70B
77
Seed 1.6
83.4
Llama 3 70B
67.5
Seed 1.6
75.9
Llama 3 70B
63.3
Seed 1.6 is ahead overall, 65 to 45. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 46 and 9.
Seed 1.6 has the edge for knowledge tasks in this comparison, averaging 56.4 versus 42.2. 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 15.8. Inside this category, SWE-bench Verified 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 63.3. 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 59.6. 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 41.2. 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 52.3. 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 77. 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 67.5. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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