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 38. 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 50.4. The single biggest benchmark swing on the page is MMLU, 83 to 46.
LFM2-24B-A2B is also the more expensive model on tokens at $0.03 input / $0.12 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.5 397B. That is roughly Infinityx on output cost alone. Qwen3.5 397B gives you the larger context window at 128K, compared with 32K for LFM2-24B-A2B.
Pick Qwen3.5 397B if you want the stronger benchmark profile. LFM2-24B-A2B only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Qwen3.5 397B
56.9
LFM2-24B-A2B
33.4
Qwen3.5 397B
40.7
LFM2-24B-A2B
18
Qwen3.5 397B
61.4
LFM2-24B-A2B
41.7
Qwen3.5 397B
75.9
LFM2-24B-A2B
46.6
Qwen3.5 397B
59.3
LFM2-24B-A2B
35.6
Qwen3.5 397B
82
LFM2-24B-A2B
68
Qwen3.5 397B
78.8
LFM2-24B-A2B
61.4
Qwen3.5 397B
81.6
LFM2-24B-A2B
50.4
Qwen3.5 397B is ahead overall, 62 to 38. The biggest single separator in this matchup is MMLU, where the scores are 83 and 46.
Qwen3.5 397B has the edge for knowledge tasks in this comparison, averaging 59.3 versus 35.6. 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 18. 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 50.4. 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 46.6. 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 33.4. Inside this category, Terminal-Bench 2.0 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 41.7. Inside this category, OfficeQA 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 68. 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 61.4. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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