Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Qwen3.5 397B is clearly ahead on the aggregate, 62 to 56. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.5 397B's sharpest advantage is in mathematics, where it averages 81.6 against 67.1. The single biggest benchmark swing on the page is SimpleQA, 80 to 61. Seed 1.6 Flash does hit back in multimodal & grounded, so the answer changes if that is the part of the workload you care about most.
Seed 1.6 Flash is also the more expensive model on tokens at $0.08 input / $0.30 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.5 397B. That is roughly Infinityx on output cost alone. Seed 1.6 Flash is the reasoning model in the pair, while Qwen3.5 397B 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 Flash gives you the larger context window at 256K, compared with 128K for Qwen3.5 397B.
Pick Qwen3.5 397B if you want the stronger benchmark profile. Seed 1.6 Flash only becomes the better choice if multimodal & grounded is the priority or you need the larger 256K context window.
Qwen3.5 397B
56.9
Seed 1.6 Flash
54.5
Qwen3.5 397B
40.7
Seed 1.6 Flash
27.6
Qwen3.5 397B
61.4
Seed 1.6 Flash
73.1
Qwen3.5 397B
75.9
Seed 1.6 Flash
66.8
Qwen3.5 397B
59.3
Seed 1.6 Flash
47.3
Qwen3.5 397B
82
Seed 1.6 Flash
81
Qwen3.5 397B
78.8
Seed 1.6 Flash
72.8
Qwen3.5 397B
81.6
Seed 1.6 Flash
67.1
Qwen3.5 397B is ahead overall, 62 to 56. The biggest single separator in this matchup is SimpleQA, where the scores are 80 and 61.
Qwen3.5 397B has the edge for knowledge tasks in this comparison, averaging 59.3 versus 47.3. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Qwen3.5 397B has the edge for coding in this comparison, averaging 40.7 versus 27.6. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Qwen3.5 397B has the edge for math in this comparison, averaging 81.6 versus 67.1. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Qwen3.5 397B has the edge for reasoning in this comparison, averaging 75.9 versus 66.8. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
Qwen3.5 397B has the edge for agentic tasks in this comparison, averaging 56.9 versus 54.5. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Seed 1.6 Flash has the edge for multimodal and grounded tasks in this comparison, averaging 73.1 versus 61.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Qwen3.5 397B has the edge for instruction following in this comparison, averaging 82 versus 81. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Qwen3.5 397B has the edge for multilingual tasks in this comparison, averaging 78.8 versus 72.8. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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