GPT-4.1 vs Ministral 3 8B 2512

Summary of our 12-test comparison (scores are our 1–5 internal scale unless otherwise noted). Wins/ties: GPT-4.1 wins 6 categories, Ministral wins 0, and 6 are ties. Detailed walk-through:

• Tool calling: GPT-4.1 5 vs Ministral 4. GPT-4.1 is tied for 1st (with 16 others) out of 54; Ministral ranks 18/54. This means GPT-4.1 is measurably better at selecting functions, arguments, and sequencing for agentic workflows.
• Long context: GPT-4.1 5 vs Ministral 4. GPT-4.1 is tied for 1st of 55 (36 others share top score); Ministral ranks 38/55. For tasks needing retrieval or reasoning over 30k+ tokens, GPT-4.1 is substantially stronger.
• Faithfulness: GPT-4.1 5 vs Ministral 4. GPT-4.1 ties for 1st among 55 models; Ministral ranks 34/55. Expect fewer hallucinations and stronger adherence to provided sources with GPT-4.1 in our tests.
• Strategic analysis: GPT-4.1 5 vs Ministral 3. GPT-4.1 is tied for 1st of 54; Ministral ranks 36/54. For nuanced tradeoff reasoning and numeric decision-making, GPT-4.1 outperforms.
• Agentic planning: GPT-4.1 4 vs Ministral 3. GPT-4.1 ranks 16/54; Ministral ranks 42/54. GPT-4.1 better decomposes goals and plans recoveries.
• Multilingual: GPT-4.1 5 vs Ministral 4. GPT-4.1 tied for 1st of 55; Ministral tied at rank 36/55. GPT-4.1 gives stronger non‑English parity in our tests. Ties (no clear winner in our tests): structured output (4/4), constrained rewriting (5/5), creative problem solving (3/3), classification (4/4), safety calibration (1/1), persona consistency (5/5). These ties indicate both models produce comparable results on format adherence, tight rewrites, creative idea generation, basic classification, refusal behavior, and persona stability. External benchmarks (supplementary): GPT-4.1 scores 48.5% on SWE-bench Verified, 83% on MATH Level 5, and 38.3% on AIME 2025 (Epoch AI). Ministral 3 8B 2512 has no external percentages in the payload. Use these Epoch AI numbers as supplementary evidence for coding/math performance; do not conflate them with our 1–5 internal scores.

Raw per‑1k-token prices: GPT-4.1 input $2.00 / output $8.00 per mTok; Ministral 3 8B 2512 input $0.15 / output $0.15 per mTok. Translate to volumes (per 1,000,000 tokens): GPT-4.1 = $2,000 input or $8,000 output; Ministral = $150 input or $150 output. For a balanced 50/50 input/output split per total tokens: 1M tokens costs GPT-4.1 $5,000 vs Ministral $150; 10M tokens costs GPT-4.1 $50,000 vs Ministral $1,500; 100M tokens costs GPT-4.1 $500,000 vs Ministral $15,000. The priceRatio in the payload (≈53.33) reflects this gap: GPT-4.1 is ~53x more expensive on comparable token usage. If your app needs many millions of tokens monthly (chat-heavy consumer apps, high-volume summarization, or large dataset inference), the cost difference is decisive; if accuracy on tool calling/long-context matters and budget is secondary, GPT-4.1 justifies the spend.

Choose GPT-4.1 if: you prioritize tool calling, long-context reasoning, faithfulness, multilingual parity, or strategic/agentic planning for developer-facing products, and you can absorb the higher compute costs (GPT-4.1 wins 6 categories in our tests). Choose Ministral 3 8B 2512 if: budget or inference scale is the binding constraint — it costs $0.15/mTok vs GPT-4.1’s $2/$8/mTok and delivers comparable results on structured outputs, constrained rewriting, classification, creative prompts, safety calibration, and persona. If you need a compromise, run critical flows on GPT-4.1 and lower-cost bulk inference (summaries, retrieval augmentation, or browsing logs) on Ministral 3 8B 2512 to control monthly spend.