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 38. 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 50.4. The single biggest benchmark swing on the page is MMLU, 77 to 46.
Kimi K2.5 is also the more expensive model on tokens at $0.50 input / $2.80 output per 1M tokens, versus $0.03 input / $0.12 output per 1M tokens for LFM2-24B-A2B. That is roughly 23.3x on output cost alone. Kimi K2.5 gives you the larger context window at 128K, compared with 32K for LFM2-24B-A2B.
Pick Kimi K2.5 if you want the stronger benchmark profile. LFM2-24B-A2B only becomes the better choice if you want the cheaper token bill.
Kimi K2.5
52.3
LFM2-24B-A2B
33.4
Kimi K2.5
38.9
LFM2-24B-A2B
18
Kimi K2.5
64.6
LFM2-24B-A2B
41.7
Kimi K2.5
71.7
LFM2-24B-A2B
46.6
Kimi K2.5
57.2
LFM2-24B-A2B
35.6
Kimi K2.5
85
LFM2-24B-A2B
68
Kimi K2.5
79.8
LFM2-24B-A2B
61.4
Kimi K2.5
78.7
LFM2-24B-A2B
50.4
Kimi K2.5 is ahead overall, 60 to 38. The biggest single separator in this matchup is MMLU, where the scores are 77 and 46.
Kimi K2.5 has the edge for knowledge tasks in this comparison, averaging 57.2 versus 35.6. 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 18. 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 50.4. 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 46.6. 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 33.4. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Kimi K2.5 has the edge for multimodal and grounded tasks in this comparison, averaging 64.6 versus 41.7. Inside this category, OfficeQA 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 68. 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 61.4. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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