GPT-4o vs Ministral 3 14B 2512

Across our 12-test suite, Ministral 3 14B 2512 wins 3 benchmarks while GPT-4o wins 1; the rest are ties (8). Detailed walk-through: - Creative problem solving: Ministral 3 scores 4 vs GPT-4o 3; Ministral ranks 9 of 54 (rankingsB.creative problem solving) vs GPT-4o rank 30, meaning Ministral is notably stronger at producing non-obvious, specific, feasible ideas. - Constrained rewriting: Ministral 3 scores 4 vs GPT-4o 3; Ministral ranks 6 of 53 vs GPT-4o rank 31 — better at strict compression and character-limited rewriting. - Strategic analysis: Ministral 3 scores 4 vs GPT-4o 2; Ministral ranks 27 of 54 vs GPT-4o 44, so for nuanced tradeoff reasoning and numeric strategy, Ministral is superior in our tests. - Agentic planning: GPT-4o wins 4 vs Ministral 3; GPT-4o ranks 16 of 54 on agentic planning while Ministral ranks 42, indicating GPT-4o better decomposes goals and plans recoveries in our benchmarks. - Ties (both models equal): structured output (4), tool calling (4), faithfulness (4), classification (4), long context (4), safety calibration (1), persona consistency (5), multilingual (4). For tool calling both tie at 4 and share rank 18 of 54, indicating similar function-selection and sequencing behavior in our tests. Context windows differ: GPT-4o has 128k and Ministral 3 has 262k; both scored 4 on long context (rank 38), so in retrieval accuracy at 30k+ tokens they performed comparably in our suite. External benchmarks (Epoch AI): GPT-4o has published external scores in our payload — 31% on SWE-bench Verified, 53.3% on MATH Level 5, and 6.4% on AIME 2025 (all reported as Epoch AI scores). Ministral 3 14B 2512 has no external scores in the provided data. These external numbers for GPT-4o place it low on SWE-bench Verified in our set (rank 12 of 12) and indicate mixed math performance — useful context but treated as supplementary to our 12-test results.

Cost per 1k tokens (input+output): GPT-4o = $2.5 + $10 = $12.50/mtok; Ministral 3 14B 2512 = $0.2 + $0.2 = $0.40/mtok. At 1M tokens/month (1,000 mtok) that’s $12,500 for GPT-4o vs $400 for Ministral. At 10M tokens: $125,000 vs $4,000. At 100M tokens: $1,250,000 vs $40,000. The output-cost ratio (GPT-4o $10 vs Ministral $0.2) is 50× (priceRatio=50). Teams with high-volume inference, tight margins, or large-scale production pipelines should care deeply about the cost gap; low-volume integrators or workflows that need GPT-4o’s agentic planning or file input support may accept the premium.

Choose GPT-4o if you need the model's agentic planning performance (scores 4 vs 3), file-input modality (text+image+file->text), or specific features listed in its parameter set, and you can absorb the large price premium. Choose Ministral 3 14B 2512 if you need cheaper at-scale inference (combined $0.40/mtok), stronger creative problem solving, constrained rewriting, or strategic analysis in our tests, or if you must optimize costs for 1M–100M token monthly volumes.