Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Llama 3.1 405B is clearly ahead on the aggregate, 59 to 36. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Llama 3.1 405B's sharpest advantage is in multimodal & grounded, where it averages 62.3 against 33.4. The single biggest benchmark swing on the page is GPQA, 70 to 29.
Ministral 3 8B (Reasoning) is the reasoning model in the pair, while Llama 3.1 405B 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.
Pick Llama 3.1 405B if you want the stronger benchmark profile. Ministral 3 8B (Reasoning) only becomes the better choice if you want the stronger reasoning-first profile.
Llama 3.1 405B
53.9
Ministral 3 8B (Reasoning)
38.5
Llama 3.1 405B
40.6
Ministral 3 8B (Reasoning)
15.2
Llama 3.1 405B
62.3
Ministral 3 8B (Reasoning)
33.4
Llama 3.1 405B
68.3
Ministral 3 8B (Reasoning)
42.1
Llama 3.1 405B
53.2
Ministral 3 8B (Reasoning)
30
Llama 3.1 405B
86
Ministral 3 8B (Reasoning)
70
Llama 3.1 405B
80.1
Ministral 3 8B (Reasoning)
61.7
Llama 3.1 405B
74.9
Ministral 3 8B (Reasoning)
47.8
Llama 3.1 405B is ahead overall, 59 to 36. The biggest single separator in this matchup is GPQA, where the scores are 70 and 29.
Llama 3.1 405B has the edge for knowledge tasks in this comparison, averaging 53.2 versus 30. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Llama 3.1 405B has the edge for coding in this comparison, averaging 40.6 versus 15.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
Llama 3.1 405B has the edge for math in this comparison, averaging 74.9 versus 47.8. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Llama 3.1 405B has the edge for reasoning in this comparison, averaging 68.3 versus 42.1. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
Llama 3.1 405B has the edge for agentic tasks in this comparison, averaging 53.9 versus 38.5. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
Llama 3.1 405B has the edge for multimodal and grounded tasks in this comparison, averaging 62.3 versus 33.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Llama 3.1 405B has the edge for instruction following in this comparison, averaging 86 versus 70. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Llama 3.1 405B has the edge for multilingual tasks in this comparison, averaging 80.1 versus 61.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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