Claude Opus 4.6 vs Devstral 2 2512

Summary of our 12-test head-to-head (scores are from our testing, 1-5 scale unless noted): - Claude Opus 4.6 wins (7 tests): strategic_analysis 5 vs 4 (Claude tied for 1st of 54, tied with 25 others), creative_problem_solving 5 vs 4 (Claude tied for 1st of 54), agentic_planning 5 vs 4 (Claude tied for 1st of 54), tool_calling 5 vs 4 (Claude tied for 1st of 54), faithfulness 5 vs 4 (Claude tied for 1st of 55), persona_consistency 5 vs 4 (Claude tied for 1st of 53), safety_calibration 5 vs 1 (Claude tied for 1st of 55). Practical meaning: Claude’s strengths are nuanced reasoning, agentic decomposition and recovery, function selection and sequencing, and calibrated refusal behavior — important for production agents and safety-critical workflows. - Devstral 2 2512 wins (2 tests): structured_output 5 vs 4 (Devstral tied for 1st of 54) and constrained_rewriting 5 vs 3 (Devstral tied for 1st of 53). Practical meaning: Devstral is superior when you need strict JSON/schema compliance and tight compression within hard character limits. - Ties (3 tests): classification 3 vs 3, long_context 5 vs 5 (both tied for 1st with many models), multilingual 5 vs 5 (both tied for 1st). Practical meaning: both models handle long contexts (30K+ tokens) and multilingual tasks at parity on our tests. - External third-party benchmarks: Claude Opus 4.6 scores 78.7% on SWE-bench Verified (Epoch AI), ranking 1 of 12 (sole holder), and 94.4% on AIME 2025 (Epoch AI), ranking 4 of 23. Devstral has no SWE-bench or AIME scores in the payload. In short: Claude dominates the majority of our internal tests and posts top results on external coding/math benchmarks; Devstral’s clear advantages are structured-output fidelity and constrained rewriting at lower cost.

Payload prices: Claude Opus 4.6 charges $5 per 1K? (input_cost_per_mtok = 5) and $25 per 1M output tokens; Devstral 2 2512 charges $0.4 input and $2 output per 1M. PriceRatio is 12.5. To make costs concrete, assume a 50/50 split of input vs output tokens (common for conversational/agent workloads): - At 1M total tokens/month: Claude = 0.5M input * $5 + 0.5M output * $25 = $2.50 + $12.50 = $15.00/month. Devstral = 0.5M * $0.4 + 0.5M * $2 = $0.20 + $1.00 = $1.20/month. - At 10M tokens/month: Claude = $150/month; Devstral = $12/month. - At 100M tokens/month: Claude = $1,500/month; Devstral = $120/month. The gap grows linearly; at 100M tokens Claude costs $1,380 more monthly under this 50/50 assumption. High-volume deployers, startups, and cost-conscious API customers should care — Devstral reduces token bill by ~12.5× under identical token usage. If your workload is output-heavy (e.g., long generated reports), Claude’s $25/million output rate will dominate costs even faster.

Choose Claude Opus 4.6 if: - You need top-tier agentic planning, tool-calling, faithfulness, and safety calibration for production agents or safety-sensitive workloads. Claude won 7 of 12 benchmarks (including safety_calibration 5 vs 1) and ranks top in multiple categories in our testing. Choose Devstral 2 2512 if: - Your priority is cost efficiency and strict structured output or aggressive constrained rewriting (Devstral scores 5 on structured_output and constrained_rewriting). Devstral is ~12.5× cheaper per-token and is the practical choice for high-volume, schema-driven pipelines.