Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Claude 4.1 Opus Thinking is clearly ahead on the aggregate, 44 to 38. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude 4.1 Opus Thinking's sharpest advantage is in multimodal & grounded, where it averages 59.3 against 41.7. The single biggest benchmark swing on the page is MMMU-Pro, 62 to 39. LFM2-24B-A2B does hit back in multilingual, so the answer changes if that is the part of the workload you care about most.
Claude 4.1 Opus Thinking is the reasoning model in the pair, while LFM2-24B-A2B is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Claude 4.1 Opus Thinking gives you the larger context window at 200K, compared with 32K for LFM2-24B-A2B.
Pick Claude 4.1 Opus Thinking if you want the stronger benchmark profile. LFM2-24B-A2B only becomes the better choice if multilingual is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Claude 4.1 Opus Thinking
46.7
LFM2-24B-A2B
33.4
Claude 4.1 Opus Thinking
21.8
LFM2-24B-A2B
18
Claude 4.1 Opus Thinking
59.3
LFM2-24B-A2B
41.7
Claude 4.1 Opus Thinking
49.4
LFM2-24B-A2B
46.6
Claude 4.1 Opus Thinking
34.3
LFM2-24B-A2B
35.6
Claude 4.1 Opus Thinking
66
LFM2-24B-A2B
68
Claude 4.1 Opus Thinking
58.7
LFM2-24B-A2B
61.4
Claude 4.1 Opus Thinking
48.3
LFM2-24B-A2B
50.4
Claude 4.1 Opus Thinking is ahead overall, 44 to 38. The biggest single separator in this matchup is MMMU-Pro, where the scores are 62 and 39.
LFM2-24B-A2B has the edge for knowledge tasks in this comparison, averaging 35.6 versus 34.3. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Claude 4.1 Opus Thinking has the edge for coding in this comparison, averaging 21.8 versus 18. 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 48.3. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Claude 4.1 Opus Thinking has the edge for reasoning in this comparison, averaging 49.4 versus 46.6. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
Claude 4.1 Opus Thinking has the edge for agentic tasks in this comparison, averaging 46.7 versus 33.4. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Claude 4.1 Opus Thinking has the edge for multimodal and grounded tasks in this comparison, averaging 59.3 versus 41.7. 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 66. 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 58.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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