Claude Sonnet 4.6 vs GPT-5 Nano

Summary of our 12-test internal comparison (scores are our 1-5 internal ratings unless noted):

• Strategic analysis: Claude Sonnet 4.6 5 vs GPT-5 Nano 4 — Sonnet ranks 1st (tied) of 54, so expect better nuance in tradeoff reasoning and numeric tradeoffs.
• Creative problem solving: Sonnet 5 vs GPT-5 Nano 3 — Sonnet ranks tied 1st of 54, meaning more non-obvious feasible ideas in brainstorming and ideation tasks.
• Tool calling: Sonnet 5 vs GPT-5 Nano 4 — Sonnet tied for 1st of 54, so better function selection, argument accuracy and sequencing in agentic workflows.
• Faithfulness: Sonnet 5 vs GPT-5 Nano 4 — Sonnet tied for 1st of 55, so it sticks to source material and hallucinates less in our tests.
• Classification: Sonnet 4 vs GPT-5 Nano 3 — Sonnet tied for 1st of 53, giving more reliable routing/categorization.
• Safety calibration: Sonnet 5 vs GPT-5 Nano 4 — Sonnet tied for 1st of 55, better at refusing harmful requests while permitting legitimate ones in our testing.
• Persona consistency: Sonnet 5 vs GPT-5 Nano 4 — Sonnet tied for 1st of 53, stronger at maintaining role and resisting injection.
• Agentic planning: Sonnet 5 vs GPT-5 Nano 4 — Sonnet tied for 1st of 54, better at decomposition and failure recovery.
• Structured output: Sonnet 4 vs GPT-5 Nano 5 — GPT-5 Nano wins here and is tied for 1st of 54; expect more reliable JSON/schema compliance from GPT-5 Nano in our tests.
• Constrained rewriting: tie 3 vs 3 — both score 3, rank 31 of 53.
• Long context: tie 5 vs 5 — both excel at long-context retrieval (tied for 1st of 55).
• Multilingual: tie 5 vs 5 — both tied for 1st of 55 for non-English parity. External benchmarks (Epoch AI) as supplementary context: Sonnet 4.6 scores 75.2% on SWE-bench Verified (Epoch AI), ranking 4 of 12; Sonnet scores 85.8% on AIME 2025 (Epoch AI), rank 10 of 23. GPT-5 Nano scores 95.2% on MATH Level 5 (Epoch AI), rank 7 of 14, and 81.1% on AIME 2025 (Epoch AI), rank 14 of 23. These external results reinforce Sonnet’s strengths in safety, planning and multi-step tasks while GPT-5 Nano shows a strong math result on MATH Level 5.

Per-token rates from the payload: Claude Sonnet 4.6 charges $3 per mTok input and $15 per mTok output; GPT-5 Nano charges $0.05 per mTok input and $0.40 per mTok output (priceRatio = 37.5). Costs by volume (mTok = 1,000 tokens):

• 1M tokens (1,000 mTok): Claude input-only $3,000; output-only $15,000; 50/50 split $9,000. GPT-5 Nano input-only $50; output-only $400; 50/50 split $225.
• 10M tokens (10,000 mTok): Claude input $30,000; output $150,000; 50/50 $90,000. GPT-5 Nano input $500; output $4,000; 50/50 $2,250.
• 100M tokens (100,000 mTok): Claude input $300,000; output $1,500,000; 50/50 $900,000. GPT-5 Nano input $5,000; output $40,000; 50/50 $22,500. Who should care: teams running millions+ tokens per month (consumer chat apps, large-scale ingestion, search augmentation, or API-driven products) must account for Claude’s orders-of-magnitude higher cost; small projects, prototypes, or latency-sensitive tools will usually find GPT-5 Nano dramatically more economical.

Choose Claude Sonnet 4.6 if you need the highest-quality agentic workflows, strategic reasoning, faithful outputs, safety calibration, and strong multilingual/long-context performance — use cases like complex codebase navigation, end-to-end project management, or safety-sensitive assistants. Choose GPT-5 Nano if you need reliable structured outputs, ultra-low cost and low-latency developer tooling at scale (prototyping, high-volume API products, or apps where every dollar per million tokens matters). If budget is tight at millions of tokens/month, GPT-5 Nano is the pragmatic choice; if task-critical correctness and agentic behavior justify cost, Sonnet is the choice.