Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GLM-4.7 is clearly ahead on the aggregate, 67 to 60. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-4.7's sharpest advantage is in coding, where it averages 46.6 against 35. The single biggest benchmark swing on the page is HumanEval, 78 to 62. Ministral 3 14B (Reasoning) does hit back in multimodal & grounded, 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 Ministral 3 14B (Reasoning).
Pick GLM-4.7 if you want the stronger benchmark profile. Ministral 3 14B (Reasoning) only becomes the better choice if multimodal & grounded is the priority.
GLM-4.7
66.1
Ministral 3 14B (Reasoning)
58.5
GLM-4.7
46.6
Ministral 3 14B (Reasoning)
35
GLM-4.7
70.5
Ministral 3 14B (Reasoning)
71.5
GLM-4.7
80.2
Ministral 3 14B (Reasoning)
69.2
GLM-4.7
61.8
Ministral 3 14B (Reasoning)
52.1
GLM-4.7
85
Ministral 3 14B (Reasoning)
81
GLM-4.7
79.1
Ministral 3 14B (Reasoning)
77.8
GLM-4.7
85
Ministral 3 14B (Reasoning)
75.2
GLM-4.7 is ahead overall, 67 to 60. The biggest single separator in this matchup is HumanEval, where the scores are 78 and 62.
GLM-4.7 has the edge for knowledge tasks in this comparison, averaging 61.8 versus 52.1. 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 35. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
GLM-4.7 has the edge for math in this comparison, averaging 85 versus 75.2. 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 69.2. Inside this category, LongBench v2 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 58.5. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
Ministral 3 14B (Reasoning) has the edge for multimodal and grounded tasks in this comparison, averaging 71.5 versus 70.5. Inside this category, MMMU-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 81. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GLM-4.7 has the edge for multilingual tasks in this comparison, averaging 79.1 versus 77.8. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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