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 65. 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 41.1. The single biggest benchmark swing on the page is SWE-bench Pro, 67 to 43.
GLM-5 (Reasoning) gives you the larger context window at 200K, compared with 128K for Mercury 2.
Pick GLM-5 (Reasoning) if you want the stronger benchmark profile. Mercury 2 only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
GLM-5 (Reasoning)
78.3
Mercury 2
63.7
GLM-5 (Reasoning)
62.5
Mercury 2
41.1
GLM-5 (Reasoning)
78.5
Mercury 2
68.3
GLM-5 (Reasoning)
88.9
Mercury 2
80.1
GLM-5 (Reasoning)
72
Mercury 2
57.2
GLM-5 (Reasoning)
92
Mercury 2
84
GLM-5 (Reasoning)
86.4
Mercury 2
79.7
GLM-5 (Reasoning)
94.4
Mercury 2
80.9
GLM-5 (Reasoning) is ahead overall, 78 to 65. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 67 and 43.
GLM-5 (Reasoning) has the edge for knowledge tasks in this comparison, averaging 72 versus 57.2. Inside this category, HLE 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 41.1. Inside this category, SWE-bench Pro 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 80.9. 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 80.1. Inside this category, MRCRv2 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 63.7. 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 68.3. Inside this category, OfficeQA 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 84. 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 79.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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