Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
LFM2-24B-A2B is clearly ahead on the aggregate, 38 to 27. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
LFM2-24B-A2B's sharpest advantage is in reasoning, where it averages 46.6 against 30.1. The single biggest benchmark swing on the page is HumanEval, 42 to 15.
LFM2-24B-A2B is also the more expensive model on tokens at $0.03 input / $0.12 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Ministral 3 3B. That is roughly Infinityx on output cost alone. Ministral 3 3B gives you the larger context window at 128K, compared with 32K for LFM2-24B-A2B.
Pick LFM2-24B-A2B if you want the stronger benchmark profile. Ministral 3 3B only becomes the better choice if you want the cheaper token bill or you need the larger 128K context window.
LFM2-24B-A2B
33.4
Ministral 3 3B
22.9
LFM2-24B-A2B
18
Ministral 3 3B
6.2
LFM2-24B-A2B
41.7
Ministral 3 3B
30.4
LFM2-24B-A2B
46.6
Ministral 3 3B
30.1
LFM2-24B-A2B
35.6
Ministral 3 3B
24.5
LFM2-24B-A2B
68
Ministral 3 3B
67
LFM2-24B-A2B
61.4
Ministral 3 3B
59.7
LFM2-24B-A2B
50.4
Ministral 3 3B
36
LFM2-24B-A2B is ahead overall, 38 to 27. The biggest single separator in this matchup is HumanEval, where the scores are 42 and 15.
LFM2-24B-A2B has the edge for knowledge tasks in this comparison, averaging 35.6 versus 24.5. Inside this category, MMLU is the benchmark that creates the most daylight between them.
LFM2-24B-A2B has the edge for coding in this comparison, averaging 18 versus 6.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
LFM2-24B-A2B has the edge for math in this comparison, averaging 50.4 versus 36. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
LFM2-24B-A2B has the edge for reasoning in this comparison, averaging 46.6 versus 30.1. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
LFM2-24B-A2B has the edge for agentic tasks in this comparison, averaging 33.4 versus 22.9. Inside this category, OSWorld-Verified is the benchmark that creates the most daylight between them.
LFM2-24B-A2B has the edge for multimodal and grounded tasks in this comparison, averaging 41.7 versus 30.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
LFM2-24B-A2B has the edge for instruction following in this comparison, averaging 68 versus 67. Inside this category, IFEval is the benchmark that creates the most daylight between them.
LFM2-24B-A2B has the edge for multilingual tasks in this comparison, averaging 61.4 versus 59.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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