Claude Opus 4.6 vs Ministral 3 14B 2512

Summary (our 12-test suite): Claude Opus 4.6 wins 8 tests, Ministral 3 14B 2512 wins 2, and 2 are ties (structured_output, persona_consistency). Detailed walk-through: - strategic_analysis: Opus 5 vs Ministral 4 — Opus tied for 1st ("tied for 1st with 25 other models out of 54 tested"), so expect strongest nuanced tradeoff reasoning from Opus. - creative_problem_solving: Opus 5 vs 4 — Opus ranks tied for 1st (tied with 7), so better at non-obvious feasible ideas. - agentic_planning: Opus 5 vs 3 — Opus tied for 1st (tied with 14) while Ministral ranks 42/54; Opus is far stronger for goal decomposition and failure recovery. - tool_calling: Opus 5 vs 4 — Opus tied for 1st (tied with 16), meaning better function selection, argument accuracy, and sequencing. - faithfulness: Opus 5 vs 4 — Opus tied for 1st (tied with 32) while Ministral ranks 34/55; Opus is less likely to hallucinate on source-based tasks. - long_context: Opus 5 vs 4 — Opus tied for 1st (tied with 36), so superior on retrieval at 30K+ tokens. - safety_calibration: Opus 5 vs 1 — Opus tied for 1st (tied with 4) versus Ministral rank 32/55; Opus better balances refusal/allow decisions. - multilingual: Opus 5 vs 4 — Opus tied for 1st (tied with 34), so stronger non-English parity. - constrained_rewriting: Opus 3 vs Ministral 4 — Ministral wins and ranks 6/53 (shared), so better at heavy compression within hard character limits. - classification: Opus 3 vs Ministral 4 — Ministral tied for 1st with 29 others out of 53, making it preferable for routing and tagging. - structured_output: both 4 — tie (rank 26 of 54), similar JSON/schema adherence. - persona_consistency: both 5 — tie (Opus tied for 1st with 36 of 53), both resist injection and hold character. External benchmarks: beyond our internal tests, Claude Opus 4.6 scores 78.7% on SWE-bench Verified (Epoch AI) — rank 1 of 12 — supporting its coding strength; Opus also scores 94.4% on AIME 2025 (Epoch AI) and ranks 4 of 23, indicating strong math reasoning on that external measure. Ministral has no SWE-bench or AIME external score in the payload.

Pricing (payload): Claude Opus 4.6 charges $5 input and $25 output per mTok; Ministral 3 14B 2512 charges $0.20 input and $0.20 output per mTok. Translating per million tokens (1 mTok = 1,000 tokens): per 1M input tokens = $5,000 (Opus) vs $200 (Ministral); per 1M output tokens = $25,000 vs $200. If you pay for 1M input + 1M output tokens: Opus ≈ $30,000 vs Ministral ≈ $400. Scale those numbers: 10M input+10M output → Opus ≈ $300,000 vs Ministral ≈ $4,000; 100M+100M → Opus ≈ $3,000,000 vs Ministral ≈ $40,000. Who should care: startups and teams at >10M tokens/month or products with heavy output generation must budget heavily for Opus; cost-sensitive applications, prototypes, and large-volume inference should favor Ministral for its ~125x price advantage (priceRatio=125).

Choose Claude Opus 4.6 if you need best-in-class coding, long-context analysis, tool-calling/agentic workflows, high faithfulness, or strict safety calibration — examples: multi-file code refactors, long document summarization, production agents calling tools and recovering from failures. Choose Ministral 3 14B 2512 if you are highly cost-sensitive, run very large volumes, or your priorities are constrained rewriting and classification at a low price — examples: large-scale classification/reranking, compressed SMS/notification generation, or prototypes where cost dominates. If you need both quality and cost control, prototype on Ministral and move specific critical workflows to Opus where its wins (agentic planning, tool calling, faithfulness, long-context) matter enough to justify the ~125x price gap.