Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-4.1 is clearly ahead on the aggregate, 65 to 60. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-4.1's sharpest advantage is in coding, where it averages 51.7 against 35. The single biggest benchmark swing on the page is AIME 2024, 26.4 to 75. Ministral 3 14B (Reasoning) does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.
GPT-4.1 is also the more expensive model on tokens at $2.00 input / $8.00 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 GPT-4.1 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. GPT-4.1 gives you the larger context window at 1M, compared with 128K for Ministral 3 14B (Reasoning).
Pick GPT-4.1 if you want the stronger benchmark profile. Ministral 3 14B (Reasoning) only becomes the better choice if mathematics is the priority or you want the cheaper token bill.
GPT-4.1
64.7
Ministral 3 14B (Reasoning)
58.5
GPT-4.1
51.7
Ministral 3 14B (Reasoning)
35
GPT-4.1
73.6
Ministral 3 14B (Reasoning)
71.5
GPT-4.1
80.9
Ministral 3 14B (Reasoning)
69.2
GPT-4.1
63.3
Ministral 3 14B (Reasoning)
52.1
GPT-4.1
87.4
Ministral 3 14B (Reasoning)
81
GPT-4.1
69
Ministral 3 14B (Reasoning)
77.8
GPT-4.1
26.4
Ministral 3 14B (Reasoning)
75.2
GPT-4.1 is ahead overall, 65 to 60. The biggest single separator in this matchup is AIME 2024, where the scores are 26.4 and 75.
GPT-4.1 has the edge for knowledge tasks in this comparison, averaging 63.3 versus 52.1. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-4.1 has the edge for coding in this comparison, averaging 51.7 versus 35. Inside this category, SWE-bench Verified 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 26.4. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
GPT-4.1 has the edge for reasoning in this comparison, averaging 80.9 versus 69.2. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
GPT-4.1 has the edge for agentic tasks in this comparison, averaging 64.7 versus 58.5. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
GPT-4.1 has the edge for multimodal and grounded tasks in this comparison, averaging 73.6 versus 71.5. Inside this category, OfficeQA Pro is the benchmark that creates the most daylight between them.
GPT-4.1 has the edge for instruction following in this comparison, averaging 87.4 versus 81. 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 69. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
Get notified when new models drop, benchmark scores change, or the leaderboard shifts. One email per week.
Free. No spam. Unsubscribe anytime. We only store derived location metadata for consent routing.