Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Kimi K2.5 is clearly ahead on the aggregate, 60 to 53. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Kimi K2.5's sharpest advantage is in coding, where it averages 38.9 against 24.7. The single biggest benchmark swing on the page is SWE-bench Verified, 42 to 22. Seed-2.0-Mini does hit back in multimodal & grounded, so the answer changes if that is the part of the workload you care about most.
Kimi K2.5 is also the more expensive model on tokens at $0.50 input / $2.80 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for Seed-2.0-Mini. That is roughly 7.0x on output cost alone. Seed-2.0-Mini gives you the larger context window at 256K, compared with 128K for Kimi K2.5.
Pick Kimi K2.5 if you want the stronger benchmark profile. Seed-2.0-Mini only becomes the better choice if multimodal & grounded is the priority or you want the cheaper token bill.
Kimi K2.5
52.3
Seed-2.0-Mini
46.2
Kimi K2.5
38.9
Seed-2.0-Mini
24.7
Kimi K2.5
64.6
Seed-2.0-Mini
73.1
Kimi K2.5
71.7
Seed-2.0-Mini
64.8
Kimi K2.5
57.2
Seed-2.0-Mini
44.6
Kimi K2.5
85
Seed-2.0-Mini
80
Kimi K2.5
79.8
Seed-2.0-Mini
71.8
Kimi K2.5
78.7
Seed-2.0-Mini
65.1
Kimi K2.5 is ahead overall, 60 to 53. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 42 and 22.
Kimi K2.5 has the edge for knowledge tasks in this comparison, averaging 57.2 versus 44.6. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Kimi K2.5 has the edge for coding in this comparison, averaging 38.9 versus 24.7. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Kimi K2.5 has the edge for math in this comparison, averaging 78.7 versus 65.1. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Kimi K2.5 has the edge for reasoning in this comparison, averaging 71.7 versus 64.8. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
Kimi K2.5 has the edge for agentic tasks in this comparison, averaging 52.3 versus 46.2. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Seed-2.0-Mini has the edge for multimodal and grounded tasks in this comparison, averaging 73.1 versus 64.6. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Kimi K2.5 has the edge for instruction following in this comparison, averaging 85 versus 80. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Kimi K2.5 has the edge for multilingual tasks in this comparison, averaging 79.8 versus 71.8. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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