Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
o3-mini is clearly ahead on the aggregate, 71 to 38. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
o3-mini's sharpest advantage is in coding, where it averages 55.6 against 18. The single biggest benchmark swing on the page is MMLU, 86.9 to 46.
o3-mini is also the more expensive model on tokens at $1.10 input / $4.40 output per 1M tokens, versus $0.03 input / $0.12 output per 1M tokens for LFM2-24B-A2B. That is roughly 36.7x on output cost alone. o3-mini 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. o3-mini gives you the larger context window at 200K, compared with 32K for LFM2-24B-A2B.
Pick o3-mini if you want the stronger benchmark profile. LFM2-24B-A2B only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
o3-mini
66.6
LFM2-24B-A2B
33.4
o3-mini
55.6
LFM2-24B-A2B
18
o3-mini
74.4
LFM2-24B-A2B
41.7
o3-mini
81.1
LFM2-24B-A2B
46.6
o3-mini
70.8
LFM2-24B-A2B
35.6
o3-mini
93.9
LFM2-24B-A2B
68
o3-mini
73
LFM2-24B-A2B
61.4
o3-mini
87.3
LFM2-24B-A2B
50.4
o3-mini is ahead overall, 71 to 38. The biggest single separator in this matchup is MMLU, where the scores are 86.9 and 46.
o3-mini has the edge for knowledge tasks in this comparison, averaging 70.8 versus 35.6. Inside this category, MMLU is the benchmark that creates the most daylight between them.
o3-mini has the edge for coding in this comparison, averaging 55.6 versus 18. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
o3-mini has the edge for math in this comparison, averaging 87.3 versus 50.4. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
o3-mini has the edge for reasoning in this comparison, averaging 81.1 versus 46.6. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
o3-mini has the edge for agentic tasks in this comparison, averaging 66.6 versus 33.4. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
o3-mini has the edge for multimodal and grounded tasks in this comparison, averaging 74.4 versus 41.7. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
o3-mini has the edge for instruction following in this comparison, averaging 93.9 versus 68. Inside this category, IFEval is the benchmark that creates the most daylight between them.
o3-mini has the edge for multilingual tasks in this comparison, averaging 73 versus 61.4. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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