Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Qwen3.5 397B is clearly ahead on the aggregate, 62 to 33. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.5 397B's sharpest advantage is in mathematics, where it averages 81.6 against 42.3. The single biggest benchmark swing on the page is HumanEval, 75 to 17.
LFM2.5-1.2B-Thinking is the reasoning model in the pair, while Qwen3.5 397B 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 gives you the larger context window at 128K, compared with 32K for LFM2.5-1.2B-Thinking.
Pick Qwen3.5 397B if you want the stronger benchmark profile. LFM2.5-1.2B-Thinking only becomes the better choice if you want the stronger reasoning-first profile.
Qwen3.5 397B
56.9
LFM2.5-1.2B-Thinking
34.1
Qwen3.5 397B
40.7
LFM2.5-1.2B-Thinking
8.2
Qwen3.5 397B
61.4
LFM2.5-1.2B-Thinking
32.4
Qwen3.5 397B
75.9
LFM2.5-1.2B-Thinking
38.4
Qwen3.5 397B
59.3
LFM2.5-1.2B-Thinking
27
Qwen3.5 397B
82
LFM2.5-1.2B-Thinking
72
Qwen3.5 397B
78.8
LFM2.5-1.2B-Thinking
60.7
Qwen3.5 397B
81.6
LFM2.5-1.2B-Thinking
42.3
Qwen3.5 397B is ahead overall, 62 to 33. The biggest single separator in this matchup is HumanEval, where the scores are 75 and 17.
Qwen3.5 397B has the edge for knowledge tasks in this comparison, averaging 59.3 versus 27. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Qwen3.5 397B has the edge for coding in this comparison, averaging 40.7 versus 8.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
Qwen3.5 397B has the edge for math in this comparison, averaging 81.6 versus 42.3. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Qwen3.5 397B has the edge for reasoning in this comparison, averaging 75.9 versus 38.4. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
Qwen3.5 397B has the edge for agentic tasks in this comparison, averaging 56.9 versus 34.1. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
Qwen3.5 397B has the edge for multimodal and grounded tasks in this comparison, averaging 61.4 versus 32.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Qwen3.5 397B has the edge for instruction following in this comparison, averaging 82 versus 72. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Qwen3.5 397B has the edge for multilingual tasks in this comparison, averaging 78.8 versus 60.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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