Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
LFM2-24B-A2B has the cleaner overall profile here, landing at 38 versus 35. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
LFM2-24B-A2B's sharpest advantage is in mathematics, where it averages 50.4 against 44.9. The single biggest benchmark swing on the page is HumanEval, 42 to 28.
MiniMax M1 80k gives you the larger context window at 80K, compared with 32K for LFM2-24B-A2B.
Pick LFM2-24B-A2B if you want the stronger benchmark profile. MiniMax M1 80k only becomes the better choice if you need the larger 80K context window.
LFM2-24B-A2B
33.4
MiniMax M1 80k
32.1
LFM2-24B-A2B
18
MiniMax M1 80k
13.8
LFM2-24B-A2B
41.7
MiniMax M1 80k
39
LFM2-24B-A2B
46.6
MiniMax M1 80k
41.7
LFM2-24B-A2B
35.6
MiniMax M1 80k
31.3
LFM2-24B-A2B
68
MiniMax M1 80k
68
LFM2-24B-A2B
61.4
MiniMax M1 80k
59.1
LFM2-24B-A2B
50.4
MiniMax M1 80k
44.9
LFM2-24B-A2B is ahead overall, 38 to 35. The biggest single separator in this matchup is HumanEval, where the scores are 42 and 28.
LFM2-24B-A2B has the edge for knowledge tasks in this comparison, averaging 35.6 versus 31.3. 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 13.8. 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 44.9. 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 41.7. 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 32.1. 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 39. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
LFM2-24B-A2B and MiniMax M1 80k are effectively tied for instruction following here, both landing at 68 on average.
LFM2-24B-A2B has the edge for multilingual tasks in this comparison, averaging 61.4 versus 59.1. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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