Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Llama 4 Behemoth is clearly ahead on the aggregate, 40 to 32. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Llama 4 Behemoth's sharpest advantage is in multimodal & grounded, where it averages 55.1 against 32.4. The single biggest benchmark swing on the page is MMMU-Pro, 60 to 27. Ministral 3 8B does hit back in instruction following, so the answer changes if that is the part of the workload you care about most.
Ministral 3 8B gives you the larger context window at 128K, compared with 32K for Llama 4 Behemoth.
Pick Llama 4 Behemoth if you want the stronger benchmark profile. Ministral 3 8B only becomes the better choice if instruction following is the priority or you need the larger 128K context window.
Llama 4 Behemoth
34.6
Ministral 3 8B
28.9
Llama 4 Behemoth
14.1
Ministral 3 8B
14.2
Llama 4 Behemoth
55.1
Ministral 3 8B
32.4
Llama 4 Behemoth
47.1
Ministral 3 8B
36.1
Llama 4 Behemoth
36.7
Ministral 3 8B
28
Llama 4 Behemoth
68
Ministral 3 8B
69
Llama 4 Behemoth
62.8
Ministral 3 8B
61.7
Llama 4 Behemoth
52.9
Ministral 3 8B
43.3
Llama 4 Behemoth is ahead overall, 40 to 32. The biggest single separator in this matchup is MMMU-Pro, where the scores are 60 and 27.
Llama 4 Behemoth has the edge for knowledge tasks in this comparison, averaging 36.7 versus 28. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Ministral 3 8B has the edge for coding in this comparison, averaging 14.2 versus 14.1. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
Llama 4 Behemoth has the edge for math in this comparison, averaging 52.9 versus 43.3. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Llama 4 Behemoth has the edge for reasoning in this comparison, averaging 47.1 versus 36.1. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
Llama 4 Behemoth has the edge for agentic tasks in this comparison, averaging 34.6 versus 28.9. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Llama 4 Behemoth has the edge for multimodal and grounded tasks in this comparison, averaging 55.1 versus 32.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Ministral 3 8B has the edge for instruction following in this comparison, averaging 69 versus 68. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Llama 4 Behemoth has the edge for multilingual tasks in this comparison, averaging 62.8 versus 61.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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