Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
LFM2-24B-A2B has the cleaner overall profile here, landing at 38 versus 35. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
LFM2-24B-A2B's sharpest advantage is in mathematics, where it averages 50.4 against 44.4. The single biggest benchmark swing on the page is HumanEval, 42 to 27.
GLM-4.5-Air gives you the larger context window at 128K, compared with 32K for LFM2-24B-A2B.
Pick LFM2-24B-A2B if you want the stronger benchmark profile. GLM-4.5-Air only becomes the better choice if you need the larger 128K context window.
LFM2-24B-A2B
33.4
GLM-4.5-Air
30.3
LFM2-24B-A2B
18
GLM-4.5-Air
14.6
LFM2-24B-A2B
41.7
GLM-4.5-Air
39.6
LFM2-24B-A2B
46.6
GLM-4.5-Air
42.6
LFM2-24B-A2B
35.6
GLM-4.5-Air
31.1
LFM2-24B-A2B
68
GLM-4.5-Air
68
LFM2-24B-A2B
61.4
GLM-4.5-Air
59.1
LFM2-24B-A2B
50.4
GLM-4.5-Air
44.4
LFM2-24B-A2B is ahead overall, 38 to 35. The biggest single separator in this matchup is HumanEval, where the scores are 42 and 27.
LFM2-24B-A2B has the edge for knowledge tasks in this comparison, averaging 35.6 versus 31.1. 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 14.6. 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 44.4. 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 42.6. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
LFM2-24B-A2B has the edge for agentic tasks in this comparison, averaging 33.4 versus 30.3. Inside this category, OSWorld-Verified is the benchmark that creates the most daylight between them.
LFM2-24B-A2B has the edge for multimodal and grounded tasks in this comparison, averaging 41.7 versus 39.6. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
LFM2-24B-A2B and GLM-4.5-Air are effectively tied for instruction following here, both landing at 68 on average.
LFM2-24B-A2B has the edge for multilingual tasks in this comparison, averaging 61.4 versus 59.1. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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