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 44.2. The single biggest benchmark swing on the page is HumanEval, 42 to 25.
DeepSeek V3.1 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. DeepSeek V3.1 only becomes the better choice if you need the larger 128K context window.
LFM2-24B-A2B
33.4
DeepSeek V3.1
32.9
LFM2-24B-A2B
18
DeepSeek V3.1
14.8
LFM2-24B-A2B
41.7
DeepSeek V3.1
39.5
LFM2-24B-A2B
46.6
DeepSeek V3.1
40.7
LFM2-24B-A2B
35.6
DeepSeek V3.1
30.5
LFM2-24B-A2B
68
DeepSeek V3.1
67
LFM2-24B-A2B
61.4
DeepSeek V3.1
60.8
LFM2-24B-A2B
50.4
DeepSeek V3.1
44.2
LFM2-24B-A2B is ahead overall, 38 to 35. The biggest single separator in this matchup is HumanEval, where the scores are 42 and 25.
LFM2-24B-A2B has the edge for knowledge tasks in this comparison, averaging 35.6 versus 30.5. 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 14.8. 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 44.2. 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 40.7. 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 32.9. Inside this category, Terminal-Bench 2.0 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 39.5. 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 60.8. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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