Claude Sonnet 4.6 vs Llama 4 Scout

Our 12-test suite shows Claude Sonnet 4.6 winning 8 categories, Llama 4 Scout winning none, and 4 ties (structured_output, constrained_rewriting, classification, long_context). Detailed results (Sonnet vs Scout in our tests):

• Tool calling: Sonnet 5 vs Scout 4 — Sonnet ranks "tied for 1st with 16 others out of 54" while Scout ranks 18 of 54. This means Sonnet is more reliable at function selection, argument accuracy and sequencing for agents.
• Agentic planning: Sonnet 5 vs Scout 2 — Sonnet is tied for 1st (among 54) while Scout is rank 53 of 54. Expect Sonnet to decompose goals and recover from failures far better in workflows and planners.
• Safety calibration: Sonnet 5 vs Scout 2 — Sonnet is tied for 1st of 55; Scout is rank 12. Sonnet more consistently refuses harmful requests and permits legitimate ones.
• Faithfulness: Sonnet 5 vs Scout 4 — Sonnet tied for 1st (of 55) vs Scout rank 34; Sonnet sticks to source material more tightly, reducing hallucination risk in factual tasks.
• Persona consistency: Sonnet 5 vs Scout 3 — Sonnet tied for 1st of 53; Scout rank 45. Sonnet better maintains character and resists prompt injection.
• Strategic analysis: Sonnet 5 vs Scout 2 — Sonnet tied for 1st; Scout rank 44. Sonnet is superior at nuanced tradeoff reasoning with real numbers.
• Creative problem solving: Sonnet 5 vs Scout 3 — Sonnet tied for 1st of 54; Scout rank 30. Sonnet generates more non-obvious feasible ideas.
• Multilingual: Sonnet 5 vs Scout 4 — Sonnet tied for 1st of 55; Scout rank 36. Sonnet delivers higher equivalent quality in non-English languages. Ties: structured_output (both 4), constrained_rewriting (both 3), classification (both 4; both tied for 1st for classification), and long_context (both 5; tied for 1st with many models). External benchmarks: Claude Sonnet 4.6 scores 75.2% on SWE-bench Verified (Epoch AI) — rank 4 of 12 — and 85.8% on AIME 2025 (Epoch AI) — rank 10 of 23. Llama 4 Scout has no SWE-bench or AIME external scores in the payload. In practice: Sonnet’s 5/5 ratings and top ranks mean it’s the safer, more capable option for agentic, safety-critical, multilingual, and faithfulness-sensitive applications. Scout’s 4s and ties show solid baseline capability at a much lower cost, but it lags on planning, safety, and persona.

Costs combine input+output per mTok: Claude Sonnet 4.6 is $3 + $15 = $18 per mTok; Llama 4 Scout is $0.08 + $0.30 = $0.38 per mTok. Translating to real volumes (1 mTok = 1,000 tokens): 1M tokens/month (1,000 mTok) costs Sonnet $18,000 vs Scout $380; 10M tokens costs Sonnet $180,000 vs Scout $3,800; 100M tokens costs Sonnet $1,800,000 vs Scout $38,000. Teams doing heavy inference (chatbots with high throughput, large-scale indexing, or low-margin apps) will find the Scout savings material. Teams needing best-in-class agentic planning, safety calibration, multilingual output, or faithfulness should budget for Sonnet despite the steep premium.

Choose Claude Sonnet 4.6 if you need best-in-class agentic planning, safe behavior, strong faithfulness, and multilingual parity — e.g., production agents, multi-step tool chains, regulated-domain assistants, or complex codebase automation. Choose Llama 4 Scout if budget and scale dominate your decision — e.g., high-volume classification, cost-sensitive chatbots, or apps where fine-grained planning and top safety calibration are not required.