Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Mistral Large 3 is clearly ahead on the aggregate, 61 to 36. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Mistral Large 3's sharpest advantage is in multimodal & grounded, where it averages 75.5 against 33.4. The single biggest benchmark swing on the page is MMMU-Pro, 75 to 28.
Mistral Large 3 is also the more expensive model on tokens at $2.00 input / $6.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Ministral 3 8B (Reasoning). That is roughly Infinityx on output cost alone. Ministral 3 8B (Reasoning) is the reasoning model in the pair, while Mistral Large 3 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 Mistral Large 3 if you want the stronger benchmark profile. Ministral 3 8B (Reasoning) only becomes the better choice if you want the cheaper token bill or you want the stronger reasoning-first profile.
Mistral Large 3
52.5
Ministral 3 8B (Reasoning)
38.5
Mistral Large 3
41
Ministral 3 8B (Reasoning)
15.2
Mistral Large 3
75.5
Ministral 3 8B (Reasoning)
33.4
Mistral Large 3
70.6
Ministral 3 8B (Reasoning)
42.1
Mistral Large 3
57.1
Ministral 3 8B (Reasoning)
30
Mistral Large 3
83
Ministral 3 8B (Reasoning)
70
Mistral Large 3
78.8
Ministral 3 8B (Reasoning)
61.7
Mistral Large 3
77.3
Ministral 3 8B (Reasoning)
47.8
Mistral Large 3 is ahead overall, 61 to 36. The biggest single separator in this matchup is MMMU-Pro, where the scores are 75 and 28.
Mistral Large 3 has the edge for knowledge tasks in this comparison, averaging 57.1 versus 30. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Mistral Large 3 has the edge for coding in this comparison, averaging 41 versus 15.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
Mistral Large 3 has the edge for math in this comparison, averaging 77.3 versus 47.8. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Mistral Large 3 has the edge for reasoning in this comparison, averaging 70.6 versus 42.1. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
Mistral Large 3 has the edge for agentic tasks in this comparison, averaging 52.5 versus 38.5. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
Mistral Large 3 has the edge for multimodal and grounded tasks in this comparison, averaging 75.5 versus 33.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Mistral Large 3 has the edge for instruction following in this comparison, averaging 83 versus 70. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Mistral Large 3 has the edge for multilingual tasks in this comparison, averaging 78.8 versus 61.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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