GPT-5.1 vs Ministral 3 14B 2512

Summary of head-to-head results from our 12-test suite: GPT-5.1 wins 6 tests, Ministral 3 14B 2512 wins 0, and 6 tests tie. Wins for GPT-5.1 (with scores):

• Faithfulness 5 vs 4 — GPT-5.1 tied for 1st of 55 models (tied with 32 others); Ministral ranks 34 of 55. This matters when you need strict adherence to source material and reduced hallucination.
• Long context 5 vs 4 — GPT-5.1 tied for 1st of 55 (36 models share top score); Ministral ranks 38 of 55. Expect GPT-5.1 to retrieve and reason across 30K+ tokens more reliably.
• Strategic analysis 5 vs 4 — GPT-5.1 tied for 1st of 54; Ministral ranks 27 of 54. For nuanced tradeoff reasoning with numbers, GPT-5.1 shows clearer advantage.
• Agentic planning 4 vs 3 — GPT-5.1 rank 16 of 54; Ministral rank 42 of 54. GPT-5.1 is better at goal decomposition and failure recovery in our tests.
• Multilingual 5 vs 4 — GPT-5.1 tied for 1st of 55; Ministral rank 36 of 55. For non-English parity, GPT-5.1 performs better.
• Safety calibration 2 vs 1 — GPT-5.1 rank 12 of 55; Ministral rank 32 of 55. GPT-5.1 is more likely to refuse harmful prompts while allowing legitimate ones. Ties (identical scores): structured output 4/4 (both rank 26 of 54), constrained rewriting 4/4 (both rank 6 of 53), creative problem solving 4/4 (both rank 9 of 54), tool calling 4/4 (both rank 18 of 54), classification 4/4 (both tied for 1st), persona consistency 5/5 (both tied for 1st). Practical takeaways:
• If your workflow hinges on JSON/schema compliance, classification routing, or persona consistency, both models are equivalently capable in our suite.
• GPT-5.1’s external benchmark signals: it scores 68 on SWE-bench Verified and 88.6 on AIME 2025 (both from Epoch AI). On SWE-bench Verified GPT-5.1 ranks 7 of 12 (sole holder) and on AIME 2025 it ranks 7 of 23 (sole holder). Ministral 3 14B 2512 has no SWE-bench or AIME scores in this payload. These external results support GPT-5.1’s advantages on coding/math-style tasks in our data.

Pricing per mTok: GPT-5.1 input $1.25 / output $10.00; Ministral 3 14B 2512 input $0.20 / output $0.20. Per-million-token math (1 mTok = 1,000 tokens):

• Per 1M tokens (example 50/50 split input/output): GPT-5.1 = $5,625; Ministral = $200.
• Per 10M tokens (50/50): GPT-5.1 = $56,250; Ministral = $2,000.
• Per 100M tokens (50/50): GPT-5.1 = $562,500; Ministral = $20,000. If you bill or operate at millions of tokens per month, the difference is material: GPT-5.1 is roughly 28x more expensive under the 50/50 example on total spend and the payload’s priceRatio is 50 (reflecting the large cost gap on output price). Teams with tight cost constraints, high-volume chatbots, or broad A/B testing should prioritize Ministral 3 14B 2512. Teams that need top-tier faithfulness, long-context handling, multilingual parity, or higher-stakes decisioning should budget for GPT-5.1 despite the higher bills.

Choose GPT-5.1 if you need: high faithfulness and reduced hallucinations (5 vs 4), top-tier long-context retrieval (5 vs 4), stronger multilingual parity, better strategic analysis, or if external coding/math scores (SWE-bench 68, AIME 88.6 — Epoch AI) matter and your budget can absorb $5,625+/month at 1M tokens (50/50). Choose Ministral 3 14B 2512 if you need: the lowest per-token cost (input/output $0.20/mTok), competitive structured output, classification and persona consistency (ties with GPT-5.1), and strong creative problem solving and tool-calling at a fraction of the price — ideal for high-volume chat, prototype scaling, or cost-conscious production.