Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GLM-4.7 has the cleaner overall profile here, landing at 67 versus 65. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
GLM-4.7's sharpest advantage is in coding, where it averages 46.6 against 41.1. The single biggest benchmark swing on the page is SWE-bench Pro, 51 to 43. Mercury 2 does hit back in multilingual, so the answer changes if that is the part of the workload you care about most.
GLM-4.7 gives you the larger context window at 200K, compared with 128K for Mercury 2.
Pick GLM-4.7 if you want the stronger benchmark profile. Mercury 2 only becomes the better choice if multilingual is the priority.
GLM-4.7
66.1
Mercury 2
63.7
GLM-4.7
46.6
Mercury 2
41.1
GLM-4.7
70.5
Mercury 2
68.3
GLM-4.7
80.2
Mercury 2
80.1
GLM-4.7
61.8
Mercury 2
57.2
GLM-4.7
85
Mercury 2
84
GLM-4.7
79.1
Mercury 2
79.7
GLM-4.7
85
Mercury 2
80.9
GLM-4.7 is ahead overall, 67 to 65. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 51 and 43.
GLM-4.7 has the edge for knowledge tasks in this comparison, averaging 61.8 versus 57.2. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GLM-4.7 has the edge for coding in this comparison, averaging 46.6 versus 41.1. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
GLM-4.7 has the edge for math in this comparison, averaging 85 versus 80.9. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
GLM-4.7 has the edge for reasoning in this comparison, averaging 80.2 versus 80.1. Inside this category, BBH is the benchmark that creates the most daylight between them.
GLM-4.7 has the edge for agentic tasks in this comparison, averaging 66.1 versus 63.7. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
GLM-4.7 has the edge for multimodal and grounded tasks in this comparison, averaging 70.5 versus 68.3. Inside this category, OfficeQA Pro is the benchmark that creates the most daylight between them.
GLM-4.7 has the edge for instruction following in this comparison, averaging 85 versus 84. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Mercury 2 has the edge for multilingual tasks in this comparison, averaging 79.7 versus 79.1. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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