Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GLM-4.5-Air is clearly ahead on the aggregate, 35 to 30. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-4.5-Air's sharpest advantage is in reasoning, where it averages 42.6 against 32.1. The single biggest benchmark swing on the page is MRCRv2, 51 to 37. LFM2.5-1.2B-Instruct does hit back in instruction following, so the answer changes if that is the part of the workload you care about most.
GLM-4.5-Air gives you the larger context window at 128K, compared with 32K for LFM2.5-1.2B-Instruct.
Pick GLM-4.5-Air if you want the stronger benchmark profile. LFM2.5-1.2B-Instruct only becomes the better choice if instruction following is the priority.
GLM-4.5-Air
30.3
LFM2.5-1.2B-Instruct
25.7
GLM-4.5-Air
14.6
LFM2.5-1.2B-Instruct
7.2
GLM-4.5-Air
39.6
LFM2.5-1.2B-Instruct
32.4
GLM-4.5-Air
42.6
LFM2.5-1.2B-Instruct
32.1
GLM-4.5-Air
31.1
LFM2.5-1.2B-Instruct
26
GLM-4.5-Air
68
LFM2.5-1.2B-Instruct
80
GLM-4.5-Air
59.1
LFM2.5-1.2B-Instruct
60.7
GLM-4.5-Air
44.4
LFM2.5-1.2B-Instruct
37
GLM-4.5-Air is ahead overall, 35 to 30. The biggest single separator in this matchup is MRCRv2, where the scores are 51 and 37.
GLM-4.5-Air has the edge for knowledge tasks in this comparison, averaging 31.1 versus 26. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GLM-4.5-Air has the edge for coding in this comparison, averaging 14.6 versus 7.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
GLM-4.5-Air has the edge for math in this comparison, averaging 44.4 versus 37. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
GLM-4.5-Air has the edge for reasoning in this comparison, averaging 42.6 versus 32.1. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
GLM-4.5-Air has the edge for agentic tasks in this comparison, averaging 30.3 versus 25.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GLM-4.5-Air has the edge for multimodal and grounded tasks in this comparison, averaging 39.6 versus 32.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
LFM2.5-1.2B-Instruct has the edge for instruction following in this comparison, averaging 80 versus 68. Inside this category, IFEval is the benchmark that creates the most daylight between them.
LFM2.5-1.2B-Instruct has the edge for multilingual tasks in this comparison, averaging 60.7 versus 59.1. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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