Claude Opus 4.6 vs Mistral Medium 3.1

Summary from our 12-test suite: Claude Opus 4.6 wins 4 tests, Mistral Medium 3.1 wins 2, and 6 tests tie. Score-by-score (our testing):

• Tool calling: Opus 5 vs Mistral 4. Opus is tied for 1st (tied with 16 others) while Mistral ranks 18 of 54 — in practice Opus is stronger at choosing correct functions, arguments, and sequencing.
• Faithfulness: Opus 5 vs Mistral 4. Opus is tied for 1st (rank 1 of 55 with 32 ties); Mistral ranks 34 of 55. Expect fewer source hallucinations from Opus in our tests.
• Safety calibration: Opus 5 vs Mistral 2. Opus tied for 1st; Mistral sits lower (rank 12 of 55). In our safety tests Opus refused harmful requests more reliably while permitting legitimate ones.
• Creative problem solving: Opus 5 vs Mistral 3. Opus ranks tied for 1st; Mistral ranks 30 of 54 — Opus produced more non-obvious, feasible ideas in our tasks.
• Constrained rewriting: Opus 3 vs Mistral 5. Mistral is tied for 1st; it handles hard character-limit compression better in our rewriting tests.
• Classification: Opus 3 vs Mistral 4. Mistral ties for 1st (with 29 others) — it is stronger at accurate routing/categorization in our suite. Ties (no clear winner in our tests): structured_output (both 4, rank 26), strategic_analysis (both 5, tied for 1st), long_context (both 5, tied for 1st), persona_consistency (both 5, tied for 1st), agentic_planning (both 5, tied for 1st), multilingual (both 5, tied for 1st). External benchmarks: Beyond our internal suite, Claude Opus 4.6 scores 78.7% on SWE-bench Verified (Epoch AI) and 94.4% on AIME 2025 (Epoch AI), and ranks 1 of 12 on SWE-bench Verified in those external tests. Mistral Medium 3.1 has no external SWE-bench or AIME scores in the payload. What this means for real tasks: pick Opus when function orchestration, fidelity to source, and refusal behavior matter; pick Mistral when you need tight rewriting, classification, or are optimizing for cost at scale.

Prices in the payload are per million tokens: Claude Opus 4.6 charges $5 input / $25 output per M tokens; Mistral Medium 3.1 charges $0.40 input / $2 output per M tokens. With an equal split of tokens (50% input, 50% output) that means: 1M tokens/month = $15 (Opus) vs $1.20 (Mistral); 10M = $150 vs $12; 100M = $1,500 vs $120. If your workload is output-heavy (80% output), 1M tokens costs $21 (Opus) vs $1.68 (Mistral). The payload shows a priceRatio of 12.5 — Opus’s output cost is 12.5× Mistral’s. Teams doing low-volume, high-value tasks (e.g., multi-step agents, sensitive production pipelines) may justify Opus’s premium; teams running large-scale chat, classification, or bulk rewriting should prioritize Mistral to cut operating costs.

Choose Claude Opus 4.6 if you need: reliable tool calling and agentic workflows, top-tier faithfulness and safety, or highest-quality creative problem solving — and you can absorb $25/M-token output costs. Choose Mistral Medium 3.1 if you need: low-cost inference (input $0.40 / output $2 per M tokens), best-in-class constrained rewriting and classification in our tests, or if you’re operating at 10M+ tokens/month where the 12.5× output cost gap dominates your budget.