Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Qwen2.5-VL-32B 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.
Qwen2.5-VL-32B's sharpest advantage is in multimodal & grounded, where it averages 52.2 against 32.4. The single biggest benchmark swing on the page is MMMU-Pro, 58 to 27. 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 Qwen2.5-VL-32B 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.
Pick Qwen2.5-VL-32B 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.
Qwen2.5-VL-32B
33.5
LFM2.5-1.2B-Thinking
34.1
Qwen2.5-VL-32B
14.3
LFM2.5-1.2B-Thinking
8.2
Qwen2.5-VL-32B
52.2
LFM2.5-1.2B-Thinking
32.4
Qwen2.5-VL-32B
43.2
LFM2.5-1.2B-Thinking
38.4
Qwen2.5-VL-32B
34.7
LFM2.5-1.2B-Thinking
27
Qwen2.5-VL-32B
67
LFM2.5-1.2B-Thinking
72
Qwen2.5-VL-32B
60.4
LFM2.5-1.2B-Thinking
60.7
Qwen2.5-VL-32B
49.7
LFM2.5-1.2B-Thinking
42.3
Qwen2.5-VL-32B is ahead overall, 38 to 33. The biggest single separator in this matchup is MMMU-Pro, where the scores are 58 and 27.
Qwen2.5-VL-32B has the edge for knowledge tasks in this comparison, averaging 34.7 versus 27. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Qwen2.5-VL-32B has the edge for coding in this comparison, averaging 14.3 versus 8.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
Qwen2.5-VL-32B has the edge for math in this comparison, averaging 49.7 versus 42.3. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Qwen2.5-VL-32B has the edge for reasoning in this comparison, averaging 43.2 versus 38.4. Inside this category, SimpleQA 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 33.5. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Qwen2.5-VL-32B has the edge for multimodal and grounded tasks in this comparison, averaging 52.2 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 67. 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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