Pick Claude Sonnet 4.6 over Opus 4.7, when is that the right call?

Anthropic's Claude model family has a clear tier structure in 2026. **Sonnet 4.6** is the mid-tier model. It is cheaper, lower latency, and good enough for most production workloads. **Opus 4.7** is the top tier. It is more expensive per token, has higher time-to-first-token, and wins on the hardest reasoning tasks. The right way to pick between them is to evaluate both on your own task. Write a test set that looks like real production traffic. Measure quality, latency, and cost for both. If Opus does not produce a quality lift that justifies the price and latency, ship Sonnet. Option B captures this empirical framing. Cost and latency matter, and Sonnet is the right pick when your evaluation does not show Opus pulling ahead on the work you actually do. The other options fail simple sanity checks. Option A says cost is marginal, which is false. Option C reverses the tier ordering. Option D invents an output-window limit that does not exist. The actual decision rule is empirical: pick the smaller, cheaper model unless your evaluation proves you need the bigger one.

**The decision is empirical, not theoretical.** Sonnet 4.6 is the cheaper, faster mid-tier; Opus 4.7 is the frontier tier with multi-x price and noticeably higher time-to-first-token. The right move is to evaluate both on YOUR workload and pick the cheaper model unless the eval shows Opus buying meaningful quality lift. Option B is the only one that names this framing. The mistake in the other options is treating the choice as a property of the models in isolation rather than a property of the model crossed with your task. Option A claims cost is marginal. In production, Opus typically runs at several times Sonnet's per-token price, and that premium compounds across millions of calls. It also adds noticeable TTFT, which matters for interactive UX. Option C inverts the tier structure. Sonnet is the smaller, faster, cheaper model. Opus is the larger, slower, more expensive model. There is no regime where Opus is the latency-friendly option. Option D invents an output-window ceiling. Both models share comparable output limits in the 2026 release line; the difference is reasoning depth, cost, and latency, not output length. The practical rule is: ship Sonnet by default, run evals on your hardest task slices, and route only those slices to Opus where the lift justifies the premium. Most production fleets end up with a mixed-tier router rather than a single model.