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 36. 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 coding, where it averages 45.9 against 15.2. The single biggest benchmark swing on the page is MMLU, 66 to 30.
GLM-4.7-Flash gives you the larger context window at 200K, compared with 128K for Ministral 3 8B (Reasoning).
Pick GLM-4.7-Flash if you want the stronger benchmark profile. Ministral 3 8B (Reasoning) only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
GLM-4.7-Flash
61.3
Ministral 3 8B (Reasoning)
38.5
GLM-4.7-Flash
45.9
Ministral 3 8B (Reasoning)
15.2
GLM-4.7-Flash
62.5
Ministral 3 8B (Reasoning)
33.4
GLM-4.7-Flash
69.7
Ministral 3 8B (Reasoning)
42.1
GLM-4.7-Flash
54.1
Ministral 3 8B (Reasoning)
30
GLM-4.7-Flash
84
Ministral 3 8B (Reasoning)
70
GLM-4.7-Flash
81.8
Ministral 3 8B (Reasoning)
61.7
GLM-4.7-Flash
74
Ministral 3 8B (Reasoning)
47.8
GLM-4.7-Flash is ahead overall, 62 to 36. The biggest single separator in this matchup is MMLU, where the scores are 66 and 30.
GLM-4.7-Flash has the edge for knowledge tasks in this comparison, averaging 54.1 versus 30. Inside this category, MMLU 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 15.2. Inside this category, HumanEval 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 47.8. Inside this category, AIME 2023 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 42.1. Inside this category, SimpleQA 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 38.5. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GLM-4.7-Flash has the edge for multimodal and grounded tasks in this comparison, averaging 62.5 versus 33.4. 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 70. 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 61.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
Get notified when new models drop, benchmark scores change, or the leaderboard shifts. One email per week.
Free. No spam. Unsubscribe anytime. We only store derived location metadata for consent routing.