Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
LFM2-24B-A2B and Qwen2.5-VL-32B finish on the same overall score, so this is less about a single winner and more about where the edge shows up. The headline says tie; the benchmark table is where the real choice happens.
Treat this as a split decision. LFM2-24B-A2B makes more sense if coding is the priority; Qwen2.5-VL-32B is the better fit if multimodal & grounded is the priority.
LFM2-24B-A2B
33.4
Qwen2.5-VL-32B
33.5
LFM2-24B-A2B
18
Qwen2.5-VL-32B
14.3
LFM2-24B-A2B
41.7
Qwen2.5-VL-32B
52.2
LFM2-24B-A2B
46.6
Qwen2.5-VL-32B
43.2
LFM2-24B-A2B
35.6
Qwen2.5-VL-32B
34.7
LFM2-24B-A2B
68
Qwen2.5-VL-32B
67
LFM2-24B-A2B
61.4
Qwen2.5-VL-32B
60.4
LFM2-24B-A2B
50.4
Qwen2.5-VL-32B
49.7
LFM2-24B-A2B and Qwen2.5-VL-32B are tied on overall score, so the right pick depends on which category matters most for your use case.
LFM2-24B-A2B has the edge for knowledge tasks in this comparison, averaging 35.6 versus 34.7. Inside this category, MMLU is the benchmark that creates the most daylight between them.
LFM2-24B-A2B has the edge for coding in this comparison, averaging 18 versus 14.3. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
LFM2-24B-A2B has the edge for math in this comparison, averaging 50.4 versus 49.7. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
LFM2-24B-A2B has the edge for reasoning in this comparison, averaging 46.6 versus 43.2. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
Qwen2.5-VL-32B has the edge for agentic tasks in this comparison, averaging 33.5 versus 33.4. Inside this category, BrowseComp 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 41.7. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
LFM2-24B-A2B has the edge for instruction following in this comparison, averaging 68 versus 67. Inside this category, IFEval is the benchmark that creates the most daylight between them.
LFM2-24B-A2B has the edge for multilingual tasks in this comparison, averaging 61.4 versus 60.4. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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