Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Qwen3.5 397B (Reasoning) is clearly ahead on the aggregate, 75 to 30. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.5 397B (Reasoning)'s sharpest advantage is in mathematics, where it averages 92.5 against 37. The single biggest benchmark swing on the page is HumanEval, 83 to 14.
Qwen3.5 397B (Reasoning) 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. Qwen3.5 397B (Reasoning) gives you the larger context window at 128K, compared with 32K for LFM2.5-1.2B-Instruct.
Pick Qwen3.5 397B (Reasoning) 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.
Qwen3.5 397B (Reasoning)
74.8
LFM2.5-1.2B-Instruct
25.7
Qwen3.5 397B (Reasoning)
62.3
LFM2.5-1.2B-Instruct
7.2
Qwen3.5 397B (Reasoning)
70.8
LFM2.5-1.2B-Instruct
32.4
Qwen3.5 397B (Reasoning)
84.2
LFM2.5-1.2B-Instruct
32.1
Qwen3.5 397B (Reasoning)
70.1
LFM2.5-1.2B-Instruct
26
Qwen3.5 397B (Reasoning)
89
LFM2.5-1.2B-Instruct
80
Qwen3.5 397B (Reasoning)
87.8
LFM2.5-1.2B-Instruct
60.7
Qwen3.5 397B (Reasoning)
92.5
LFM2.5-1.2B-Instruct
37
Qwen3.5 397B (Reasoning) is ahead overall, 75 to 30. The biggest single separator in this matchup is HumanEval, where the scores are 83 and 14.
Qwen3.5 397B (Reasoning) has the edge for knowledge tasks in this comparison, averaging 70.1 versus 26. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Qwen3.5 397B (Reasoning) has the edge for coding in this comparison, averaging 62.3 versus 7.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
Qwen3.5 397B (Reasoning) has the edge for math in this comparison, averaging 92.5 versus 37. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Qwen3.5 397B (Reasoning) has the edge for reasoning in this comparison, averaging 84.2 versus 32.1. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
Qwen3.5 397B (Reasoning) has the edge for agentic tasks in this comparison, averaging 74.8 versus 25.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Qwen3.5 397B (Reasoning) has the edge for multimodal and grounded tasks in this comparison, averaging 70.8 versus 32.4. Inside this category, OfficeQA Pro is the benchmark that creates the most daylight between them.
Qwen3.5 397B (Reasoning) has the edge for instruction following in this comparison, averaging 89 versus 80. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Qwen3.5 397B (Reasoning) has the edge for multilingual tasks in this comparison, averaging 87.8 versus 60.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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