Claude Sonnet 4.6 vs GPT-5 Mini

Summary of our 12-test comparison (scores from our testing; external benchmarks attributed): Wins and ties are from our test suite. Claude Sonnet 4.6 wins: creative_problem_solving (5 vs 4), tool_calling (5 vs 3), safety_calibration (5 vs 3), and agentic_planning (5 vs 4). GPT-5 Mini wins: structured_output (5 vs 4) and constrained_rewriting (4 vs 3). They tie on strategic_analysis (both 5), faithfulness (both 5), classification (both 4), long_context (both 5), persona_consistency (both 5), and multilingual (both 5). Details and practical meaning: - Tool calling: Sonnet 5 vs GPT-5 Mini 3. Sonnet is tied for 1st (tied with 16 other models of 54) while GPT-5 Mini ranks 47/54 — in practice Sonnet is meaningfully better at function selection, argument accuracy, and sequencing. - Safety calibration: Sonnet 5 (tied for 1st of 55) vs GPT-5 Mini 3 (rank 10 of 55) — Sonnet is more reliable at refusing harmful requests while permitting legitimate ones in our tests. - Agentic planning: Sonnet 5 (tied for 1st) vs GPT-5 Mini 4 (rank 16) — Sonnet performs better at goal decomposition and failure recovery. - Structured output: GPT-5 Mini 5 (tied for 1st) vs Sonnet 4 (rank 26) — GPT-5 Mini is stronger at strict JSON/schema compliance and format adherence. - Constrained rewriting: GPT-5 Mini 4 (rank 6) vs Sonnet 3 (rank 31) — GPT-5 Mini handles tight character/byte budgets more reliably. - Creative problem solving: Sonnet 5 (tied for 1st) vs GPT-5 Mini 4 (rank 9) — Sonnet generates more non-obvious, feasible ideas in our tests. External benchmarks (Epoch AI): on SWE-bench Verified, Sonnet scores 75.2% (rank 4 of 12) vs GPT-5 Mini 64.7% (rank 8 of 12). On MATH Level 5 (Epoch AI), GPT-5 Mini scores 97.8% (rank 2 of 14) — Sonnet did not report a math_level_5 score in our payload. On AIME 2025 (Epoch AI), Sonnet 85.8% (rank 10 of 23) vs GPT-5 Mini 86.7% (rank 9 of 23). What this means for tasks: choose Sonnet for agentic systems, multi-step tool orchestration, and safety-sensitive production agents; choose GPT-5 Mini for strict schema outputs, tight-rewrite constraints, and high-volume or math-heavy workloads where cost matters.

Pricing (per mTok from the payload): Claude Sonnet 4.6 — input $3, output $15. GPT-5 Mini — input $0.25, output $2. Using a conservative 50/50 split of input/output tokens: Sonnet costs $9.00 per 1k tokens → $9,000 per 1M tokens; GPT-5 Mini costs $1.125 per 1k → $1,125 per 1M tokens. At 10M tokens/month: Sonnet ≈ $90,000 vs GPT-5 Mini ≈ $11,250. At 100M tokens/month: Sonnet ≈ $900,000 vs GPT-5 Mini ≈ $112,500. The payload’s priceRatio is 7.5x; Sonnet’s higher output price ($15 vs $2) drives most of the gap. Who should care: startups or apps with large conversational volumes, high-throughput APIs, or low-margin products will feel the difference immediately; teams that require best-in-class tool-calling, safety, or agentic features may accept Sonnet’s premium.

Choose Claude Sonnet 4.6 if you need best-in-class tool-calling, safety calibration, agentic planning, or creative problem solving in production (Sonnet scores 5 on tool_calling, safety_calibration, agentic_planning and is tied for top ranks). Choose GPT-5 Mini if you need the lowest cost at scale, top structured-output compliance, constrained rewriting, or superior MATH Level 5 performance (GPT-5 Mini scores 5 on structured_output, 4 on constrained_rewriting and 97.8% on MATH Level 5 according to Epoch AI). If you expect >10M tokens/month and cost is a key constraint, prefer GPT-5 Mini; if each request must reliably pick functions, follow safety policies, and coordinate multi-step plans, prefer Sonnet despite the 7.5x price gap.