Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Nova Pro is clearly ahead on the aggregate, 38 to 33. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Nova Pro's sharpest advantage is in coding, where it averages 17.2 against 8.2. The single biggest benchmark swing on the page is HumanEval, 33 to 17. LFM2.5-1.2B-Thinking does hit back in instruction following, so the answer changes if that is the part of the workload you care about most.
LFM2.5-1.2B-Thinking is the reasoning model in the pair, while Nova Pro 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. Nova Pro gives you the larger context window at 128K, compared with 32K for LFM2.5-1.2B-Thinking.
Pick Nova Pro if you want the stronger benchmark profile. LFM2.5-1.2B-Thinking only becomes the better choice if instruction following is the priority or you want the stronger reasoning-first profile.
Nova Pro
33.3
LFM2.5-1.2B-Thinking
34.1
Nova Pro
17.2
LFM2.5-1.2B-Thinking
8.2
Nova Pro
41.1
LFM2.5-1.2B-Thinking
32.4
Nova Pro
46.3
LFM2.5-1.2B-Thinking
38.4
Nova Pro
34.2
LFM2.5-1.2B-Thinking
27
Nova Pro
66
LFM2.5-1.2B-Thinking
72
Nova Pro
60.4
LFM2.5-1.2B-Thinking
60.7
Nova Pro
48.6
LFM2.5-1.2B-Thinking
42.3
Nova Pro is ahead overall, 38 to 33. The biggest single separator in this matchup is HumanEval, where the scores are 33 and 17.
Nova Pro has the edge for knowledge tasks in this comparison, averaging 34.2 versus 27. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Nova Pro has the edge for coding in this comparison, averaging 17.2 versus 8.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
Nova Pro has the edge for math in this comparison, averaging 48.6 versus 42.3. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Nova Pro has the edge for reasoning in this comparison, averaging 46.3 versus 38.4. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
LFM2.5-1.2B-Thinking has the edge for agentic tasks in this comparison, averaging 34.1 versus 33.3. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Nova Pro has the edge for multimodal and grounded tasks in this comparison, averaging 41.1 versus 32.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
LFM2.5-1.2B-Thinking has the edge for instruction following in this comparison, averaging 72 versus 66. Inside this category, IFEval is the benchmark that creates the most daylight between them.
LFM2.5-1.2B-Thinking has the edge for multilingual tasks in this comparison, averaging 60.7 versus 60.4. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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