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 55. 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 agentic, where it averages 62.3 against 48.4. The single biggest benchmark swing on the page is MRCRv2, 78 to 60.
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 Ministral 3 14B. That is roughly Infinityx on output cost alone. Seed 1.6 is the reasoning model in the pair, while Ministral 3 14B 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 Ministral 3 14B.
Pick Seed 1.6 if you want the stronger benchmark profile. Ministral 3 14B only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
Seed 1.6
62.3
Ministral 3 14B
48.4
Seed 1.6
42.4
Ministral 3 14B
33
Seed 1.6
79.6
Ministral 3 14B
70.5
Seed 1.6
74.5
Ministral 3 14B
63.6
Seed 1.6
56.4
Ministral 3 14B
50.1
Seed 1.6
87
Ministral 3 14B
80
Seed 1.6
83.4
Ministral 3 14B
76.8
Seed 1.6
75.9
Ministral 3 14B
69.7
Seed 1.6 is ahead overall, 65 to 55. The biggest single separator in this matchup is MRCRv2, where the scores are 78 and 60.
Seed 1.6 has the edge for knowledge tasks in this comparison, averaging 56.4 versus 50.1. 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 33. Inside this category, SWE-bench Pro 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 69.7. Inside this category, MATH-500 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 63.6. 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 48.4. 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 70.5. 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 80. 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 76.8. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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