Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
o1-preview is clearly ahead on the aggregate, 77 to 30. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
o1-preview's sharpest advantage is in coding, where it averages 64.6 against 7.2. The single biggest benchmark swing on the page is HumanEval, 86 to 14.
o1-preview is the reasoning model in the pair, while LFM2.5-1.2B-Instruct 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. o1-preview gives you the larger context window at 200K, compared with 32K for LFM2.5-1.2B-Instruct.
Pick o1-preview if you want the stronger benchmark profile. LFM2.5-1.2B-Instruct only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
o1-preview
75.4
LFM2.5-1.2B-Instruct
25.7
o1-preview
64.6
LFM2.5-1.2B-Instruct
7.2
o1-preview
75.6
LFM2.5-1.2B-Instruct
32.4
o1-preview
86.8
LFM2.5-1.2B-Instruct
32.1
o1-preview
71.3
LFM2.5-1.2B-Instruct
26
o1-preview
88
LFM2.5-1.2B-Instruct
80
o1-preview
87.4
LFM2.5-1.2B-Instruct
60.7
o1-preview
93.5
LFM2.5-1.2B-Instruct
37
o1-preview is ahead overall, 77 to 30. The biggest single separator in this matchup is HumanEval, where the scores are 86 and 14.
o1-preview has the edge for knowledge tasks in this comparison, averaging 71.3 versus 26. Inside this category, MMLU is the benchmark that creates the most daylight between them.
o1-preview has the edge for coding in this comparison, averaging 64.6 versus 7.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
o1-preview has the edge for math in this comparison, averaging 93.5 versus 37. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
o1-preview has the edge for reasoning in this comparison, averaging 86.8 versus 32.1. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
o1-preview has the edge for agentic tasks in this comparison, averaging 75.4 versus 25.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
o1-preview has the edge for multimodal and grounded tasks in this comparison, averaging 75.6 versus 32.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
o1-preview has the edge for instruction following in this comparison, averaging 88 versus 80. Inside this category, IFEval is the benchmark that creates the most daylight between them.
o1-preview has the edge for multilingual tasks in this comparison, averaging 87.4 versus 60.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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