GPT-5.1 vs Ministral 3 8B 2512

Summary from our 12-test suite: GPT-5.1 wins 7 tests, Ministral 3 8B 2512 wins 1, and 4 are ties. Detailed results (our scores):

• Strategic analysis: GPT-5.1 5 vs Ministral 3 8B 2512 3 — GPT-5.1 (ranked tied for 1st in our pool) handles nuanced tradeoffs and numeric reasoning better, useful for financial modeling or policy tradeoff work.
• Creative problem solving: 4 vs 3 — GPT-5.1 provides more specific, feasible ideas in our prompts (rank 9 of 54).
• Faithfulness: 5 vs 4 — GPT-5.1 tied for 1st (with 32 others), meaning it sticks closer to source material and reduces hallucination risk in source-driven tasks.
• Long context: 5 vs 4 — GPT-5.1 tied for 1st on retrieval at 30K+ tokens in our tests, so it’s stronger on long documents and multi-page context.
• Safety calibration: 2 vs 1 — GPT-5.1 refuses harmful requests more reliably in our suite (rank 12 of 55 vs rank 32 for Ministral).
• Agentic planning: 4 vs 3 — GPT-5.1 decomposes goals and recovery paths more effectively (rank 16 vs 42).
• Multilingual: 5 vs 4 — GPT-5.1 produced higher-quality non-English outputs in our tests (tied for top tier).
• Constrained rewriting: 4 vs 5 — Ministral 3 8B 2512 wins here (tied for 1st with 4 others); it compresses and adheres to hard character limits better, which matters for token-limited UIs and microcopy.
• Ties: structured output (4/4), tool calling (4/4), classification (4/4), persona consistency (5/5) — both models are equally capable in JSON/schema adherence, function selection, routing, and staying in character per our tests. External benchmarks: Beyond our internal suite, GPT-5.1 scores 68% on SWE-bench Verified and 88.6% on AIME 2025 (Epoch AI), which corroborates its strength on coding and high-level math tasks; Ministral 3 8B 2512 has no external SWE-bench/AIME scores in the payload. Practical meaning: GPT-5.1 is the safer choice where accuracy, long-context retrieval, and complex reasoning matter; Ministral is the cost-efficient choice for tight-output constraints and high-volume deployments.

Per the payload, GPT-5.1 costs $1.25 per input mtok and $10.00 per output mtok; Ministral 3 8B 2512 costs $0.15 per input mtok and $0.15 per output mtok. At 1M tokens/month (1,000 mtok): GPT-5.1 input = $1,250, output = $10,000, total ≈ $11,250. Ministral: input = $150, output = $150, total = $300. At 10M tokens/month: GPT-5.1 ≈ $112,500; Ministral ≈ $3,000. At 100M tokens/month: GPT-5.1 ≈ $1,125,000; Ministral ≈ $30,000. The payload's priceRatio is ~66.7x — GPT-5.1 is roughly sixty-six times more expensive per token output. Teams with heavy inference volumes, slim margins, or free/low-cost consumer tiers should care deeply about this gap; research prototypes, high-reliability enterprise features, or tasks that need top-tier reasoning may justify GPT-5.1's cost.

Choose GPT-5.1 if you need best-in-class faithfulness, long-context retrieval, strategic analysis, multilingual quality, or safer refusals — and you can afford $1,250+/1M-token input plus $10,000+/1M-token output ($11,250 total for 1M tokens). Choose Ministral 3 8B 2512 if budget or scale is the priority (≈$300 total at 1M tokens), you need excellent constrained rewriting, or you require a balanced vision+text model for high-volume inference where marginal cost matters.