Claude Sonnet 4.6 vs R1 0528

Summary of head-to-head results in our 12-test suite (internal 1–5 scores plus external Epoch AI math/coding benchmarks):

• Claude Sonnet 4.6 wins (in our testing): • strategic_analysis 5 vs 4 — Sonnet tied for 1st of 54 models (tied with 25 others). This matters for tasks requiring nuanced tradeoffs and numeric reasoning. • creative_problem_solving 5 vs 4 — Sonnet tied for 1st of 54 (tied with 7 others). Expect stronger non-obvious, feasible idea generation. • safety_calibration 5 vs 4 — Sonnet tied for 1st of 55 (tied with 4 others). Better at refusing harmful requests while permitting legitimate ones.
• R1 0528 wins: • constrained_rewriting 4 vs 3 — R1 ranks 6 of 53 (shared), Sonnet ranks 31 of 53. R1 is measurably better at compression and strict character-limit rewriting.
• Ties (no decisive winner): structured_output 4–4 (both rank 26/54), tool_calling 5–5 (both tied for 1st), faithfulness 5–5 (both tied for 1st), classification 4–4 (both tied for 1st), long_context 5–5 (both tied for 1st), persona_consistency 5–5 (both tied for 1st), agentic_planning 5–5 (both tied for 1st), multilingual 5–5 (both tied for 1st). For those tasks you can choose based on cost, context window, or other product constraints.
• External benchmarks (Epoch AI): Sonnet scores 75.2% on SWE-bench Verified (Epoch AI) and ranks 4 of 12, and 85.8% on AIME 2025 (Epoch AI) rank 10 of 23 — supporting strong coding and advanced math/problem-solving in some measures. R1 posts 96.6% on MATH Level 5 (Epoch AI) rank 5 of 14, but 66.4% on AIME 2025 rank 16 of 23, indicating a strong showing on competition math tests but weaker AIME performance. Practical meaning: Sonnet is the safer, more creative and strategically capable model in our tests; R1 is the cost-efficient option with a clear edge on constrained rewriting and high-level math benchmarks.

Pricing fields in the payload: Claude Sonnet 4.6 charges input $3 per mTok and output $15 per mTok; R1 0528 charges input $0.50 per mTok and output $2.15 per mTok. Interpreting mTok as 1,000-token units, per 1M tokens (1,000 mTok) that equals: Sonnet — input $3,000 + output $15,000 = $18,000 per 1M tokens; R1 — input $500 + output $2,150 = $2,650 per 1M tokens. At scale: 10M tokens → Sonnet $180,000 vs R1 $26,500; 100M → Sonnet $1,800,000 vs R1 $265,000. The output-cost ratio is ~6.98× (15 / 2.15) and overall combined cost is ~6.79× higher for Sonnet at equal I/O. Who should care: startups or high-volume API consumers will see material savings with R1; teams that need Sonnet’s top safety/creative/strategic output must budget accordingly.

Choose Claude Sonnet 4.6 if: you need top-tier safety calibration, creative ideation, strategic tradeoff reasoning, very long context (1,000,000 window) or you’ll rely on tool calling/agent workflows and can afford higher cost. Choose R1 0528 if: you must minimize API spend at scale, you need stronger constrained rewriting or MATH Level 5 performance (96.6% on MATH Level 5, Epoch AI), or you can tolerate R1’s quirks (empty responses on structured_output, reasoning tokens consume output budget). If budget is the primary constraint, R1’s ~6.8–7× lower per-token costs make it the clear operational choice.