Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Qwen2.5-72B is clearly ahead on the aggregate, 64 to 38. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen2.5-72B's sharpest advantage is in mathematics, where it averages 83.5 against 50.4. The single biggest benchmark swing on the page is AIME 2023, 84 to 46.
Qwen2.5-72B gives you the larger context window at 128K, compared with 32K for LFM2-24B-A2B.
Pick Qwen2.5-72B if you want the stronger benchmark profile. LFM2-24B-A2B only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Qwen2.5-72B
57.7
LFM2-24B-A2B
33.4
Qwen2.5-72B
43.8
LFM2-24B-A2B
18
Qwen2.5-72B
66.7
LFM2-24B-A2B
41.7
Qwen2.5-72B
75.8
LFM2-24B-A2B
46.6
Qwen2.5-72B
59.8
LFM2-24B-A2B
35.6
Qwen2.5-72B
85
LFM2-24B-A2B
68
Qwen2.5-72B
80.8
LFM2-24B-A2B
61.4
Qwen2.5-72B
83.5
LFM2-24B-A2B
50.4
Qwen2.5-72B is ahead overall, 64 to 38. The biggest single separator in this matchup is AIME 2023, where the scores are 84 and 46.
Qwen2.5-72B has the edge for knowledge tasks in this comparison, averaging 59.8 versus 35.6. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Qwen2.5-72B has the edge for coding in this comparison, averaging 43.8 versus 18. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
Qwen2.5-72B has the edge for math in this comparison, averaging 83.5 versus 50.4. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Qwen2.5-72B has the edge for reasoning in this comparison, averaging 75.8 versus 46.6. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
Qwen2.5-72B has the edge for agentic tasks in this comparison, averaging 57.7 versus 33.4. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Qwen2.5-72B has the edge for multimodal and grounded tasks in this comparison, averaging 66.7 versus 41.7. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Qwen2.5-72B 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.
Qwen2.5-72B has the edge for multilingual tasks in this comparison, averaging 80.8 versus 61.4. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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