GPT-4.1 Nano vs Ministral 3 14B 2512

Win/loss summary in our 12-test suite: GPT-4.1 Nano wins 4 tests (structured output 5 vs 4, faithfulness 5 vs 4, safety calibration 2 vs 1, agentic planning 4 vs 3), Ministral 3 14B 2512 wins 4 tests (strategic analysis 4 vs 2, creative problem solving 4 vs 2, classification 4 vs 3, persona consistency 5 vs 4), and 4 tests tie (constrained rewriting, tool calling, long context, multilingual at equal scores). Key specifics and practical meaning: - Structured output: GPT-4.1 Nano scores 5 vs 4 and is tied for 1st with 24 others out of 54 on structured output in our rankings — meaning it is more reliable for JSON schema compliance and strict format adherence. - Faithfulness: GPT-4.1 Nano scores 5 vs 4 and is tied for 1st with 32 others out of 55 on faithfulness — better for sticking to source material and avoiding hallucinations in our tests. - Safety calibration: GPT-4.1 Nano 2 vs Ministral 1; GPT-4.1 Nano ranks 12 of 55 (20 models share this score) vs Ministral rank 32 — GPT-4.1 Nano refused more unsafe requests appropriately in our tests. - Agentic planning: GPT-4.1 Nano 4 (rank 16/54) vs Ministral 3 (rank 42/54) — GPT-4.1 Nano performed better on goal decomposition and failure recovery. - Classification: Ministral 4 vs GPT-4.1 Nano 3; Ministral ties for 1st with 29 others out of 53 — better for routing and categorization tasks in our evaluation. - Creative problem solving and strategic analysis: Ministral scores 4 vs GPT-4.1 Nano 2 and ranks substantially higher (creative rank 9/54 vs 47/54), indicating Ministral produces more non-obvious, feasible ideas and better nuanced tradeoff reasoning in our tests. - Persona consistency: Ministral 5 vs GPT-4.1 Nano 4 and is tied for 1st with 36 others — stronger at maintaining character and resisting injection in chat. - Ties (constrained rewriting, tool calling, long context, multilingual): both models score equally; for example tool calling is 4/5 each and both rank 18 of 54 (29 models share that score), so expect similar capability selecting functions and sequencing. - Math/competition: GPT-4.1 Nano reports 70 on MATH Level 5 and 28.9 on AIME 2025 (Epoch AI) in our data; it ranks 11 of 14 and 20 of 23 respectively in our comparisons. Ministral has no MATH/AIME entries in the payload. Overall: GPT-4.1 Nano is stronger where format compliance, faithfulness, and safety matter; Ministral 3 14B 2512 is stronger for classification, creativity, strategy, and persona-driven chat.

Costs per 1k tokens: GPT-4.1 Nano input $0.10 / output $0.40; Ministral 3 14B 2512 input $0.20 / output $0.20. Output-only cost at 1M tokens/month (1,000 mTok): GPT-4.1 Nano = $400, Ministral = $200. At 10M: GPT-4.1 Nano = $4,000, Ministral = $2,000. At 100M: GPT-4.1 Nano = $40,000, Ministral = $20,000. If you assume equal input + output volume, add input costs: 1M in+1M out → GPT-4.1 Nano $500 vs Ministral $400; 10M → $5,000 vs $4,000; 100M → $50,000 vs $40,000. In short: GPT-4.1 Nano typically costs ~2x more on output tokens (payload priceRatio=2). Teams with heavy generation volumes (bots, summary pipelines, content farms) should care — Ministral 3 14B 2512 cuts raw token spend roughly in half for output-heavy workloads. Buyers trading cost for stricter format, faithfulness, and safety may accept GPT-4.1 Nano’s higher output price.

Choose GPT-4.1 Nano if you need: - Reliable structured outputs (5/5 structured output, tied for 1st), tight faithfulness (5/5), better safety calibration, and stronger agentic planning — ideal for production APIs, data pipelines, and systems where hallucinations or malformed outputs are costly. Choose Ministral 3 14B 2512 if you need: - Lower output costs (output $0.20/1k vs $0.40/1k), better classification (4 vs 3), creative problem solving (4 vs 2), strategic analysis (4 vs 2), and persona consistency (5 vs 4) — ideal for high-volume generation, chatbots with strong character, and tasks prioritizing creativity and classification over strict schema compliance.