Mistral AIMinistral 3 14BVSOpenAIGPT-5 mini
Our Take
Standardized reasoning and coding benchmarks are currently pending verification for one or both of these models. We recommend testing Ministral 3 14B and GPT-5 mini directly in their respective provider playgrounds to see which fits your specific prompt styles best.
Was this recommendation helpful?
Benchmarks & Scores
Coding (swe-bench-pro)
N/Acomplex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)
N/Agraduate-level science QA
Cost & Context
Cost (per 1M tokens)3.4x cheaper
$0.20Input: $0.20 | Output: $0.20Context Window
262.14k tokensBenchmarks & Scores
Coding (swe-bench-pro)
45.7%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)
81.6%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$0.69Input: $0.25 | Output: $2.00Context WindowLarger
400k tokensFrequently Asked Questions about Ministral 3 14B vs GPT-5 mini
Ministral 3 14B is cheaper than GPT-5 mini. Ministral 3 14B has a blended cost of $0.20/1M tokens, which is about 3.4x cheaper than GPT-5 mini at $0.69/1M tokens.
Related Matchups
Explore similar comparisons for Ministral 3 14B and GPT-5 mini.
Do you want to find a model for your constraints?
Use our interactive model finder to filter LLMs by reasoning capability, coding performance, cost, and context length.