Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GLM-4.7-Flash is clearly ahead on the aggregate, 62 to 55. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-4.7-Flash's sharpest advantage is in agentic, where it averages 61.3 against 48.4. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 64 to 48. Ministral 3 14B 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-Flash is the reasoning model in the pair, while Ministral 3 14B is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. GLM-4.7-Flash gives you the larger context window at 200K, compared with 128K for Ministral 3 14B.
Pick GLM-4.7-Flash if you want the stronger benchmark profile. Ministral 3 14B only becomes the better choice if multimodal & grounded is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
GLM-4.7-Flash
61.3
Ministral 3 14B
48.4
GLM-4.7-Flash
45.9
Ministral 3 14B
33
GLM-4.7-Flash
62.5
Ministral 3 14B
70.5
GLM-4.7-Flash
69.7
Ministral 3 14B
63.6
GLM-4.7-Flash
54.1
Ministral 3 14B
50.1
GLM-4.7-Flash
84
Ministral 3 14B
80
GLM-4.7-Flash
81.8
Ministral 3 14B
76.8
GLM-4.7-Flash
74
Ministral 3 14B
69.7
GLM-4.7-Flash is ahead overall, 62 to 55. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 64 and 48.
GLM-4.7-Flash has the edge for knowledge tasks in this comparison, averaging 54.1 versus 50.1. Inside this category, HLE is the benchmark that creates the most daylight between them.
GLM-4.7-Flash has the edge for coding in this comparison, averaging 45.9 versus 33. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
GLM-4.7-Flash has the edge for math in this comparison, averaging 74 versus 69.7. Inside this category, MATH-500 is the benchmark that creates the most daylight between them.
GLM-4.7-Flash has the edge for reasoning in this comparison, averaging 69.7 versus 63.6. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
GLM-4.7-Flash has the edge for agentic tasks in this comparison, averaging 61.3 versus 48.4. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Ministral 3 14B has the edge for multimodal and grounded tasks in this comparison, averaging 70.5 versus 62.5. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GLM-4.7-Flash has the edge for instruction following in this comparison, averaging 84 versus 80. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GLM-4.7-Flash has the edge for multilingual tasks in this comparison, averaging 81.8 versus 76.8. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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