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 55. 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 mathematics, where it averages 78.7 against 69.7. The single biggest benchmark swing on the page is HumanEval, 69 to 58. Ministral 3 14B 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 $0.00 input / $0.00 output per 1M tokens for Ministral 3 14B. That is roughly Infinityx on output cost alone.
Pick Kimi K2.5 if you want the stronger benchmark profile. Ministral 3 14B only becomes the better choice if multimodal & grounded is the priority or you want the cheaper token bill.
Kimi K2.5
52.3
Ministral 3 14B
48.4
Kimi K2.5
38.9
Ministral 3 14B
33
Kimi K2.5
64.6
Ministral 3 14B
70.5
Kimi K2.5
71.7
Ministral 3 14B
63.6
Kimi K2.5
57.2
Ministral 3 14B
50.1
Kimi K2.5
85
Ministral 3 14B
80
Kimi K2.5
79.8
Ministral 3 14B
76.8
Kimi K2.5
78.7
Ministral 3 14B
69.7
Kimi K2.5 is ahead overall, 60 to 55. The biggest single separator in this matchup is HumanEval, where the scores are 69 and 58.
Kimi K2.5 has the edge for knowledge tasks in this comparison, averaging 57.2 versus 50.1. 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 33. Inside this category, HumanEval 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 69.7. Inside this category, MATH-500 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 63.6. Inside this category, MRCRv2 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 48.4. Inside this category, OSWorld-Verified is the benchmark that creates the most daylight between them.
Ministral 3 14B has the edge for multimodal and grounded tasks in this comparison, averaging 70.5 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 76.8. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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