Claude Sonnet 4.6 vs Devstral 2 2512
Claude Sonnet 4.6 is the better pick for most enterprise and agentic workflows: it wins 8 of 12 internal benchmarks including tool calling, safety, and agentic planning. Devstral 2 2512 outperforms Sonnet on structured output and constrained rewriting and is far cheaper — a clear price-vs-quality tradeoff for high-volume deployments.
anthropic
Claude Sonnet 4.6
Benchmark Scores
External Benchmarks
Pricing
Input
$3.00/MTok
Output
$15.00/MTok
modelpicker.net
mistral
Devstral 2 2512
Benchmark Scores
External Benchmarks
Pricing
Input
$0.400/MTok
Output
$2.00/MTok
modelpicker.net
Benchmark Analysis
Summary of head-to-head results (our 12-test suite). Sonnet 4.6 wins eight categories: strategic_analysis 5 vs 4 (Sonnet ranks tied for 1st of 54; Devstral ranks 27/54), creative_problem_solving 5 vs 4 (Sonnet tied for 1st of 54; Devstral rank 9/54), tool_calling 5 vs 4 (Sonnet tied for 1st of 54; Devstral rank 18/54), faithfulness 5 vs 4 (Sonnet tied for 1st of 55; Devstral rank 34/55), classification 4 vs 3 (Sonnet tied for 1st of 53; Devstral rank 31/53), safety_calibration 5 vs 1 (Sonnet tied for 1st of 55; Devstral rank 32/55), persona_consistency 5 vs 4 (Sonnet tied for 1st of 53; Devstral rank 38/53), and agentic_planning 5 vs 4 (Sonnet tied for 1st of 54; Devstral rank 16/54). Devstral 2 2512 wins structured_output 5 vs 4 (Devstral tied for 1st of 54; Sonnet rank 26/54) and constrained_rewriting 5 vs 3 (Devstral tied for 1st of 53; Sonnet rank 31/53). They tie on long_context (both 5, tied for 1st of 55) and multilingual (both 5, tied for 1st of 55). Practical implications: Sonnet’s 5/5 in tool_calling and agentic_planning means more accurate function selection, argument construction, and multi-step goal decomposition for agentic workflows; its 5/5 safety_calibration reduces risky outputs. Devstral’s 5/5 structured_output and constrained_rewriting make it better for strict JSON/schema compliance and hard-limit compression tasks. Beyond our internal tests, Claude Sonnet 4.6 scores 75.2% on SWE-bench Verified (Epoch AI) and 85.8% on AIME 2025 (Epoch AI), placing it 4th of 12 and 10th of 23 respectively on those external measures; Devstral has no external scores in the payload.
Pricing Analysis
Pricing per million tokens (assuming a 50/50 input/output split): Claude Sonnet 4.6 costs $9.00 per 1M tokens (0.5*$3 + 0.5*$15). Devstral 2 2512 costs $1.20 per 1M tokens (0.5*$0.4 + 0.5*$2). At scale that reads: 1M tokens/month = $9 vs $1.2; 10M = $90 vs $12; 100M = $900 vs $120. The output-rate ratio (15/2) and priceRatio=7.5 in the payload show Sonnet is roughly 7.5× more expensive on output token billing. Teams with heavy inference volumes or tight budgets should prefer Devstral 2 2512; teams that need the higher benchmarked quality, safety, and agentic capabilities should budget for Sonnet 4.6.
Real-World Cost Comparison
Bottom Line
Choose Claude Sonnet 4.6 if you need the highest reliability on agentic workflows, safe refusal behavior, strong faithfulness, tool calling, and nuanced strategic reasoning (e.g., multi-step agents, production assistants, safety-sensitive automation) and can absorb higher token costs. Choose Devstral 2 2512 if you need low-cost, high-throughput inference with best-in-class structured-output and constrained-rewriting behavior (e.g., strict JSON/schema generation, compression-limited transformations) or are optimizing for token budget at scale.
How We Test
We test every model against our 12-benchmark suite covering tool calling, agentic planning, creative problem solving, safety calibration, and more. Each test is scored 1–5 by an LLM judge. Read our full methodology.