Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Ministral 3 14B (Reasoning) is clearly ahead on the aggregate, 60 to 49. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Ministral 3 14B (Reasoning)'s sharpest advantage is in mathematics, where it averages 75.2 against 59.4. The single biggest benchmark swing on the page is MuSR, 70 to 46.
Gemini 2.5 Flash is also the more expensive model on tokens at $0.15 input / $0.60 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Ministral 3 14B (Reasoning). That is roughly Infinityx on output cost alone. Ministral 3 14B (Reasoning) is the reasoning model in the pair, while Gemini 2.5 Flash 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. Gemini 2.5 Flash gives you the larger context window at 1M, compared with 128K for Ministral 3 14B (Reasoning).
Pick Ministral 3 14B (Reasoning) if you want the stronger benchmark profile. Gemini 2.5 Flash only becomes the better choice if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model.
Ministral 3 14B (Reasoning)
58.5
Gemini 2.5 Flash
46.5
Ministral 3 14B (Reasoning)
35
Gemini 2.5 Flash
21.7
Ministral 3 14B (Reasoning)
71.5
Gemini 2.5 Flash
67.7
Ministral 3 14B (Reasoning)
69.2
Gemini 2.5 Flash
59.2
Ministral 3 14B (Reasoning)
52.1
Gemini 2.5 Flash
40.5
Ministral 3 14B (Reasoning)
81
Gemini 2.5 Flash
79
Ministral 3 14B (Reasoning)
77.8
Gemini 2.5 Flash
70.8
Ministral 3 14B (Reasoning)
75.2
Gemini 2.5 Flash
59.4
Ministral 3 14B (Reasoning) is ahead overall, 60 to 49. The biggest single separator in this matchup is MuSR, where the scores are 70 and 46.
Ministral 3 14B (Reasoning) has the edge for knowledge tasks in this comparison, averaging 52.1 versus 40.5. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Ministral 3 14B (Reasoning) has the edge for coding in this comparison, averaging 35 versus 21.7. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
Ministral 3 14B (Reasoning) has the edge for math in this comparison, averaging 75.2 versus 59.4. Inside this category, AIME 2023 is the benchmark that creates the most daylight between them.
Ministral 3 14B (Reasoning) has the edge for reasoning in this comparison, averaging 69.2 versus 59.2. Inside this category, MuSR is the benchmark that creates the most daylight between them.
Ministral 3 14B (Reasoning) has the edge for agentic tasks in this comparison, averaging 58.5 versus 46.5. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Ministral 3 14B (Reasoning) has the edge for multimodal and grounded tasks in this comparison, averaging 71.5 versus 67.7. Inside this category, OfficeQA Pro is the benchmark that creates the most daylight between them.
Ministral 3 14B (Reasoning) has the edge for instruction following in this comparison, averaging 81 versus 79. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Ministral 3 14B (Reasoning) has the edge for multilingual tasks in this comparison, averaging 77.8 versus 70.8. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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