Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Qwen2.5-1M finishes one point ahead overall, 66 to 65. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
Qwen2.5-1M's sharpest advantage is in mathematics, where it averages 83.6 against 75.9. The single biggest benchmark swing on the page is MMMU-Pro, 63 to 80. Seed 1.6 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 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.
Pick Qwen2.5-1M if you want the stronger benchmark profile. Seed 1.6 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
62.3
Qwen2.5-1M
44.8
Seed 1.6
42.4
Qwen2.5-1M
68.4
Seed 1.6
79.6
Qwen2.5-1M
80.9
Seed 1.6
74.5
Qwen2.5-1M
60.4
Seed 1.6
56.4
Qwen2.5-1M
84
Seed 1.6
87
Qwen2.5-1M
80.4
Seed 1.6
83.4
Qwen2.5-1M
83.6
Seed 1.6
75.9
Qwen2.5-1M is ahead overall, 66 to 65. The biggest single separator in this matchup is MMMU-Pro, where the scores are 63 and 80.
Qwen2.5-1M has the edge for knowledge tasks in this comparison, averaging 60.4 versus 56.4. 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 42.4. Inside this category, HumanEval 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 75.9. 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 74.5. 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 62.3. Inside this category, BrowseComp 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 68.4. 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 84. 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 80.4. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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