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 42. 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 coding, where it averages 42.4 against 12.9. The single biggest benchmark swing on the page is SWE-bench Verified, 46 to 12.
Seed 1.6 is also the more expensive model on tokens at $0.25 input / $2.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Llama 4 Scout. That is roughly Infinityx on output cost alone. Seed 1.6 is the reasoning model in the pair, while Llama 4 Scout 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. Llama 4 Scout gives you the larger context window at 10M, compared with 256K for Seed 1.6.
Pick Seed 1.6 if you want the stronger benchmark profile. Llama 4 Scout only becomes the better choice if you want the cheaper token bill or you need the larger 10M context window.
Seed 1.6
62.3
Llama 4 Scout
40.6
Seed 1.6
42.4
Llama 4 Scout
12.9
Seed 1.6
79.6
Llama 4 Scout
57.8
Seed 1.6
74.5
Llama 4 Scout
55
Seed 1.6
56.4
Llama 4 Scout
35.6
Seed 1.6
87
Llama 4 Scout
68
Seed 1.6
83.4
Llama 4 Scout
59.8
Seed 1.6
75.9
Llama 4 Scout
51
Seed 1.6 is ahead overall, 65 to 42. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 46 and 12.
Seed 1.6 has the edge for knowledge tasks in this comparison, averaging 56.4 versus 35.6. Inside this category, MMLU 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 12.9. 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 51. 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 55. Inside this category, MuSR 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 40.6. 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 57.8. Inside this category, OfficeQA 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 68. 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 59.8. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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