Claude Opus 4.6 vs Llama 4 Scout

Overview (our 12-test suite, 1–5 scale unless noted): Claude Opus 4.6 wins 8 benchmarks; Llama 4 Scout wins 1; 3 are ties. Detailed walk-through (scores are our testing):

• Strategic analysis: Opus 5 vs Scout 2 — Opus ranks tied for 1st (tied with 25 others out of 54) on nuanced tradeoff reasoning; Scout ranks 44 of 54. This matters for financial modeling and multi-constraint decisions.
• Creative problem solving: Opus 5 vs Scout 3 — Opus tied for 1st (with 7 others), so expect more non-obvious feasible ideas from Opus.
• Agentic planning: Opus 5 vs Scout 2 — Opus tied for 1st (with 14 others); better at goal decomposition and recovery for agents.
• Tool calling: Opus 5 vs Scout 4 — Opus tied for 1st (with 16 others); expect more accurate function selection and sequencing in complex workflows.
• Faithfulness: Opus 5 vs Scout 4 — Opus tied for 1st (with 32 others); better at sticking to source material and avoiding hallucination.
• Safety calibration: Opus 5 vs Scout 2 — Opus tied for 1st (with 4 others); Opus is more likely to refuse harmful prompts and permit legitimate ones in our tests.
• Persona consistency & multilingual: Opus 5 vs Scout 3/4 — Opus ranks tied for 1st in persona_consistency and multilingual; better at consistent voices and non-English parity.
• Long context: Opus 5 vs Scout 5 — tie; both rank tied for 1st for retrieval accuracy at 30K+ tokens in our suite.
• Structured output & constrained rewriting: both tie (4 and 3 respectively) — similar performance on JSON schema compliance and hard-limit rewriting tasks.
• Classification: Opus 3 vs Scout 4 — Llama 4 Scout wins this single benchmark and is tied for 1st in our classification ranking (tied with 29 others), so it can be a cheaper, effective choice for routing and categorization workloads. External benchmarks: 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. Llama 4 Scout has no external SWE-bench or AIME scores in the payload. Overall interpretation: Opus dominates agentic, safety, and reasoning dimensions in our tests (and leads on external SWE-bench), while Scout is narrowly better at classification and massively cheaper.

Costs from the payload: Claude Opus 4.6 = $5 input / $25 output per 1K tokens; Llama 4 Scout = $0.08 input / $0.30 output per 1K tokens. Per 1M tokens (1,000 mtok) with equal input and output volumes, Opus = $5,000 (input) + $25,000 (output) = $30,000; Scout = $80 (input) + $300 (output) = $380. At 10M tokens: Opus ≈ $300,000 vs Scout ≈ $3,800. At 100M tokens: Opus ≈ $3,000,000 vs Scout ≈ $38,000. The priceRatio in the payload is ~83.3x. Who should care: startups, high-volume API apps, and inference-heavy products (user-facing chat, batch classification, telemetry processing) will see massive budget differences; research/enterprise teams that need Opus’s top agentic and safety behavior may accept the premium, while cost-sensitive production classifiers or simple chatbots will prefer Llama 4 Scout.

Choose Claude Opus 4.6 if you build agentic systems, multi-step automation, professional coding assistants, or require top safety calibration and faithfulness — our testing shows Opus wins 8/12 benchmarks (tool calling, strategic analysis, agentic planning, faithfulness, safety) and scores 78.7% on SWE-bench Verified (Epoch AI). Choose Llama 4 Scout if unit cost is the binding constraint and your primary need is high-throughput classification or budget chat: it wins classification in our suite and costs $0.08/$0.30 per 1K tokens versus Opus’s $5/$25.