Claude Opus 4.6 vs Codestral 2508
For professional, agentic and safety-critical workflows pick Claude Opus 4.6 — it wins the majority of benchmarks (6 of 12) and ranks top in strategic analysis and safety calibration in our testing. Codestral 2508 is the pragmatic choice when you need best-in-class structured output and a much lower price point.
anthropic
Claude Opus 4.6
Benchmark Scores
External Benchmarks
Pricing
Input
$5.00/MTok
Output
$25.00/MTok
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mistral
Codestral 2508
Benchmark Scores
External Benchmarks
Pricing
Input
$0.300/MTok
Output
$0.900/MTok
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Benchmark Analysis
Head-to-head across our 12-test suite: Claude Opus 4.6 wins six benchmarks in our testing — strategic analysis (5 vs 2), creative problem solving (5 vs 2), safety calibration (5 vs 1), persona consistency (5 vs 3), agentic planning (5 vs 4) and multilingual (5 vs 4). Codestral 2508 wins structured output (5 vs 4). Five tests tie: tool calling (5/5), faithfulness (5/5), long context (5/5), constrained rewriting (3/3) and classification (3/3). Context from rankings: Opus’s strategic analysis score is tied for 1st of 54 models and its SWE-bench Verified score is 78.7% (Epoch AI), while Opus places 4th on AIME 2025 (94.4% per Epoch AI). By contrast, Codestral ranks tied for 1st on structured output (top tier for JSON/schema adherence) while ranking much lower on strategic analysis and creative problem solving (44/54 and 47/54 respectively). Practically, Opus’s 5/5 strategic analysis and safety calibration mean it better handles nuanced tradeoffs and refuses harmful requests in our tests; Codestral’s 5/5 structured output means it is superior for strict schema compliance, fill-in-the-middle and code-correction pipelines.
Pricing Analysis
Claude Opus 4.6 is dramatically more expensive: input $5/mTok and output $25/mTok versus Codestral 2508 at $0.30/mTok input and $0.90/mTok output (priceRatio 27.78 in the payload). Using a 50/50 input-output split as a practical example, Opus costs $15,000 per 1M total tokens, $150,000 per 10M, and $1,500,000 per 100M. Codestral costs $600 per 1M, $6,000 per 10M, and $60,000 per 100M. Startups, high-volume APIs, and cost-sensitive production workloads should care about this gap; teams that need top safety, strategic reasoning and agentic capability may justify Opus’s higher spend for lower-volume, high-value tasks.
Real-World Cost Comparison
Bottom Line
Choose Claude Opus 4.6 if you need high-stakes agentic planning, strategic reasoning, multi‑lingual parity, long-context retrieval, or safety-calibrated outputs and can absorb higher per-token costs. Choose Codestral 2508 if you need best-in-class structured output (JSON/schema), low-latency, high-frequency coding tasks or are operating at high token volumes where cost (about $600 per 1M tokens at 50/50) is decisive.
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.