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 59. 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 multimodal & grounded, where it averages 79.6 against 62. The single biggest benchmark swing on the page is MMMU-Pro, 80 to 57. MiniMax M2.5 does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.
Seed 1.6 is also the more expensive model on tokens at $0.25 input / $2.00 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M2.5. Seed 1.6 is the reasoning model in the pair, while MiniMax M2.5 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 MiniMax M2.5.
Pick Seed 1.6 if you want the stronger benchmark profile. MiniMax M2.5 only becomes the better choice if mathematics is the priority or you want the cheaper token bill.
Seed 1.6
62.3
MiniMax M2.5
53.4
Seed 1.6
42.4
MiniMax M2.5
38.7
Seed 1.6
79.6
MiniMax M2.5
62
Seed 1.6
74.5
MiniMax M2.5
69.6
Seed 1.6
56.4
MiniMax M2.5
55.3
Seed 1.6
87
MiniMax M2.5
85
Seed 1.6
83.4
MiniMax M2.5
82.1
Seed 1.6
75.9
MiniMax M2.5
76.1
Seed 1.6 is ahead overall, 65 to 59. The biggest single separator in this matchup is MMMU-Pro, where the scores are 80 and 57.
Seed 1.6 has the edge for knowledge tasks in this comparison, averaging 56.4 versus 55.3. 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 38.7. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
MiniMax M2.5 has the edge for math in this comparison, averaging 76.1 versus 75.9. 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 69.6. Inside this category, LongBench v2 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 53.4. 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 62. 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 85. 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 82.1. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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