Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Qwen2.5-1M is clearly ahead on the aggregate, 66 to 56. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen2.5-1M's sharpest advantage is in coding, where it averages 44.8 against 27.6. The single biggest benchmark swing on the page is SWE-bench Verified, 47 to 24. 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 the reasoning model in the pair, while Qwen2.5-1M 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. Qwen2.5-1M gives you the larger context window at 1M, compared with 256K for Seed 1.6 Flash.
Pick Qwen2.5-1M if you want the stronger benchmark profile. Seed 1.6 Flash only becomes the better choice if multimodal & grounded is the priority or you want the stronger reasoning-first profile.
Qwen2.5-1M
64.7
Seed 1.6 Flash
54.5
Qwen2.5-1M
44.8
Seed 1.6 Flash
27.6
Qwen2.5-1M
68.4
Seed 1.6 Flash
73.1
Qwen2.5-1M
80.9
Seed 1.6 Flash
66.8
Qwen2.5-1M
60.4
Seed 1.6 Flash
47.3
Qwen2.5-1M
84
Seed 1.6 Flash
81
Qwen2.5-1M
80.4
Seed 1.6 Flash
72.8
Qwen2.5-1M
83.6
Seed 1.6 Flash
67.1
Qwen2.5-1M is ahead overall, 66 to 56. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 47 and 24.
Qwen2.5-1M has the edge for knowledge tasks in this comparison, averaging 60.4 versus 47.3. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Qwen2.5-1M has the edge for coding in this comparison, averaging 44.8 versus 27.6. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Qwen2.5-1M has the edge for math in this comparison, averaging 83.6 versus 67.1. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Qwen2.5-1M has the edge for reasoning in this comparison, averaging 80.9 versus 66.8. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
Qwen2.5-1M has the edge for agentic tasks in this comparison, averaging 64.7 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 68.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Qwen2.5-1M has the edge for instruction following in this comparison, averaging 84 versus 81. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Qwen2.5-1M has the edge for multilingual tasks in this comparison, averaging 80.4 versus 72.8. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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