Claude Opus 4.6 vs Mistral Small 4

Summary of our 12-test comparison (our scores unless noted):

• Claude Opus 4.6 wins strategic_analysis (5 vs 4). In rankings Opus is tied for 1st (tied with 25 others out of 54), indicating best-in-class nuanced tradeoff reasoning for finance, policy or planning prompts.
• Claude wins creative_problem_solving (5 vs 4); Opus ranks tied for 1st on creative tasks, useful for non-obvious feasible ideas.
• Claude wins agentic_planning (5 vs 4); tied for 1st with 14 others, meaning stronger goal decomposition and failure recovery in our tests.
• Claude wins tool_calling (5 vs 4); Opus is tied for 1st with 16 others out of 54, so it selects functions, args and sequencing more reliably in agent flows.
• Claude wins faithfulness (5 vs 4); Opus ties for 1st (with 32 others) which matters when sticking to source material and avoiding hallucinations.
• Claude wins long_context (5 vs 4); Opus is tied for 1st (with 36 others out of 55), giving it an edge on retrieval/analysis at 30K+ token contexts.
• Claude wins safety_calibration (5 vs 2); in our tests Opus more consistently refuses harmful prompts while allowing legitimate ones.
• Claude wins classification (3 vs 2) and ranks higher (rank 31 of 53 vs Mistral rank 51 of 53), so routing and tagging are more accurate with Opus in our suite.
• Mistral Small 4 wins structured_output (5 vs 4); Mistral is tied for 1st with 24 others out of 54 on JSON/schema compliance, so it better adheres to strict format requirements in our tests.
• Ties: constrained_rewriting (3), persona_consistency (5), multilingual (5) — both models performed equally on compression-within-limits, character/persona maintenance, and non-English quality in our testing. External third‑party benchmarks (Epoch AI): Claude Opus 4.6 scores 78.7% on SWE-bench Verified (Epoch AI) and ranks 1 of 12 on that external test; it also scores 94.4% on AIME 2025 (Epoch AI) and ranks 4 of 23 per our data. Mistral Small 4 has no external SWE-bench or AIME scores in the payload. Overall interpretation: Opus 4.6 dominates agentic, long-context, safety and faithfulness tasks in our suite and shows top coding/engineering signals on SWE-bench (Epoch AI); Mistral Small 4 is the stand‑out for structured format fidelity and a much lower cost per token.

Prices in the payload are per mTok: Claude Opus 4.6 charges $5 input / $25 output per mTok; Mistral Small 4 charges $0.15 input / $0.60 output per mTok. Assuming the common billing unit of 1 mTok = 1,000 tokens and a 50/50 split of input/output tokens: for 1M tokens/month (1,000 mTok total -> 500 mTok input + 500 mTok output) Claude costs 500*$5 + 500*$25 = $15,000/month; Mistral costs 500*$0.15 + 500*$0.60 = $375/month. At 10M tokens/month those totals scale to $150,000 vs $3,750; at 100M tokens/month they scale to $1,500,000 vs $37,500. The ~41.67x output-price ratio (25 / 0.6) means high-volume, output-heavy applications (large content generation, many API calls) should prioritize Mistral to control costs; teams that need Opus 4.6’s top-tier safety, long-context, tool-calling and SWE-bench performance should budget accordingly.

Choose Claude Opus 4.6 if: you need best-in-class agentic planning, tool-calling, long-context work, high faithfulness and safety (Opus wins 8 of 12 benchmarks, scores 78.7% on SWE-bench (Epoch AI) and 94.4% on AIME 2025). Ideal for coding, complex workflows, multi-step automation and high-risk content where errors are costly. Choose Mistral Small 4 if: you need strict JSON/schema compliance or large-scale, cost-sensitive inference — it wins structured_output, and its input/output rates ($0.15/$0.60 per mTok) make it ~40x cheaper on output than Opus. Prefer Mistral for high-volume chat, templated generation, or when budget trumps top-tier agent capabilities.