Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Mistral 7B v0.3 finishes one point ahead overall, 32 to 31. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
Mistral 7B v0.3's sharpest advantage is in coding, where it averages 13.2 against 7.2. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 24 to 33. Ministral 3 3B (Reasoning) does hit back in agentic, so the answer changes if that is the part of the workload you care about most.
Ministral 3 3B (Reasoning) is the reasoning model in the pair, while Mistral 7B v0.3 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. Ministral 3 3B (Reasoning) gives you the larger context window at 128K, compared with 32K for Mistral 7B v0.3.
Pick Mistral 7B v0.3 if you want the stronger benchmark profile. Ministral 3 3B (Reasoning) only becomes the better choice if agentic is the priority or you need the larger 128K context window.
Mistral 7B v0.3
26.4
Ministral 3 3B (Reasoning)
34
Mistral 7B v0.3
13.2
Ministral 3 3B (Reasoning)
7.2
Mistral 7B v0.3
32.4
Ministral 3 3B (Reasoning)
30.4
Mistral 7B v0.3
36.1
Ministral 3 3B (Reasoning)
35.3
Mistral 7B v0.3
30
Ministral 3 3B (Reasoning)
25.2
Mistral 7B v0.3
68
Ministral 3 3B (Reasoning)
68
Mistral 7B v0.3
60.7
Ministral 3 3B (Reasoning)
59.7
Mistral 7B v0.3
43
Ministral 3 3B (Reasoning)
40.9
Mistral 7B v0.3 is ahead overall, 32 to 31. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 24 and 33.
Mistral 7B v0.3 has the edge for knowledge tasks in this comparison, averaging 30 versus 25.2. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Mistral 7B v0.3 has the edge for coding in this comparison, averaging 13.2 versus 7.2. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
Mistral 7B v0.3 has the edge for math in this comparison, averaging 43 versus 40.9. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Mistral 7B v0.3 has the edge for reasoning in this comparison, averaging 36.1 versus 35.3. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
Ministral 3 3B (Reasoning) has the edge for agentic tasks in this comparison, averaging 34 versus 26.4. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Mistral 7B v0.3 has the edge for multimodal and grounded tasks in this comparison, averaging 32.4 versus 30.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
Mistral 7B v0.3 and Ministral 3 3B (Reasoning) are effectively tied for instruction following here, both landing at 68 on average.
Mistral 7B v0.3 has the edge for multilingual tasks in this comparison, averaging 60.7 versus 59.7. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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