Claude Opus 4.7 vs Claude Sonnet 4.6

Walkthrough (in our testing):

• Ties (both models matched top scores): creative problem solving (5/5 — tied for 1st), tool calling (5/5 — tied for 1st), faithfulness (5/5 — tied for 1st), strategic analysis (5/5 — tied for 1st), long-context retrieval (5/5 — tied for 1st), persona consistency (5/5 — tied for 1st), and agentic planning (5/5 — tied for 1st). Practically, both models are equally strong for complex planning, multi-step tool-driven flows, creative ideation, and very long-context retrieval.
• Sonnet 4.6 wins classification (4 vs Opus 3), safety calibration (5 vs Opus 3), and multilingual (5 vs Opus 4). Rankings reinforce this: Sonnet is tied for 1st on classification and safety (rank 1 of 54/56 respectively), while Opus sits lower (Opus classification rank 31 of 54; Opus safety rank 10 of 56). For real tasks this means Sonnet will refuse harmful prompts more reliably, route and label inputs more accurately, and produce higher-quality non‑English output in our tests.
• Opus 4.7 wins constrained rewriting (4 vs Sonnet 3). Opus ranks 6 of 55 on constrained rewriting (higher than Sonnet's rank 32 of 55), so if you must compress or strictly reformat content to tight character/byte limits, Opus shows measurable advantage.
• Structured output is a tie (both 4/5; rank 26 of 55), so JSON/schema compliance is comparable. Long-context and tool-calling parity means both handle very large contexts and function selection/argument sequencing at the top of our pool.
• External benchmarks (supplementary): Sonnet 4.6 scores 75.2% on SWE-bench Verified and ranks 4 of 12 on that external coding benchmark (Epoch AI). Sonnet also scores 85.8% on AIME 2025 (rank 10 of 23) per Epoch AI; Opus has no SWE-bench/AIME scores in our payload. Use external results as complementary evidence that Sonnet performs strongly on code and competition math tasks.

List prices: Claude Opus 4.7 charges $5 per million input tokens and $25 per million output tokens; Claude Sonnet 4.6 charges $3 per million input and $15 per million output. Using a 50/50 input/output token split as a simple real-world example, cost per 1M total tokens is $15 for Opus and $9 for Sonnet — a $6 savings. At 10M total tokens (50/50) Opus ≈ $150 vs Sonnet ≈ $90 (save $60). At 100M total tokens Opus ≈ $1,500 vs Sonnet ≈ $900 (save $600). If your usage is output-heavy (e.g., long generations), the gap widens because Opus charges $25/M for outputs vs Sonnet's $15/M. High-volume API customers, chat platforms, or services that generate many long responses should prioritize Sonnet for cost efficiency; individual researchers or low-volume prototyping will see smaller absolute savings but the same percentage advantage (Opus is roughly 1.67× the per-token price of Sonnet by raw rate).

Choose Claude Sonnet 4.6 if: you need a safer, more accurate classifier and better multilingual quality in production; you want lower per-token cost at scale (Sonnet charges $3 input/$15 output); you care about third-party coding/math performance (75.2% on SWE-bench Verified, Epoch AI). Choose Claude Opus 4.7 if: your priority is constrained rewriting (tight character-compression or exact reformatting) — Opus scores higher there (4 vs 3) and ranks 6 of 55 on that test. For everything else — tool calling, long-context reasoning, creative problem solving, persona consistency and strategic analysis — both models perform at the top of our tested set and are interchangeable decisions based on price and the single constrained-rewriting advantage.