Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GLM-5 (Reasoning) is clearly ahead on the aggregate, 78 to 33. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-5 (Reasoning)'s sharpest advantage is in coding, where it averages 62.5 against 8.2. The single biggest benchmark swing on the page is HumanEval, 88 to 17.
GLM-5 (Reasoning) gives you the larger context window at 200K, compared with 32K for LFM2.5-1.2B-Thinking.
Pick GLM-5 (Reasoning) if you want the stronger benchmark profile. LFM2.5-1.2B-Thinking only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
GLM-5 (Reasoning)
78.3
LFM2.5-1.2B-Thinking
34.1
GLM-5 (Reasoning)
62.5
LFM2.5-1.2B-Thinking
8.2
GLM-5 (Reasoning)
78.5
LFM2.5-1.2B-Thinking
32.4
GLM-5 (Reasoning)
88.9
LFM2.5-1.2B-Thinking
38.4
GLM-5 (Reasoning)
72
LFM2.5-1.2B-Thinking
27
GLM-5 (Reasoning)
92
LFM2.5-1.2B-Thinking
72
GLM-5 (Reasoning)
86.4
LFM2.5-1.2B-Thinking
60.7
GLM-5 (Reasoning)
94.4
LFM2.5-1.2B-Thinking
42.3
GLM-5 (Reasoning) is ahead overall, 78 to 33. The biggest single separator in this matchup is HumanEval, where the scores are 88 and 17.
GLM-5 (Reasoning) has the edge for knowledge tasks in this comparison, averaging 72 versus 27. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GLM-5 (Reasoning) has the edge for coding in this comparison, averaging 62.5 versus 8.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
GLM-5 (Reasoning) has the edge for math in this comparison, averaging 94.4 versus 42.3. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
GLM-5 (Reasoning) has the edge for reasoning in this comparison, averaging 88.9 versus 38.4. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
GLM-5 (Reasoning) has the edge for agentic tasks in this comparison, averaging 78.3 versus 34.1. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GLM-5 (Reasoning) has the edge for multimodal and grounded tasks in this comparison, averaging 78.5 versus 32.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GLM-5 (Reasoning) has the edge for instruction following in this comparison, averaging 92 versus 72. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GLM-5 (Reasoning) has the edge for multilingual tasks in this comparison, averaging 86.4 versus 60.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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