Claude Sonnet vs Opus: Which Model Tier Should You Actually Use?
Anthropic ships Claude in tiers — historically Haiku (fast and cheap), Sonnet (the balanced workhorse), and Opus (maximum capability). Specific version numbers change several times a year; the shape of the decision doesn't. This guide is about that shape, so it stays useful after the next release — always check anthropic.com for current models and prices.
The one-sentence answer: Sonnet is the right default; Opus is the right escalation. The interesting question is knowing which of your tasks are escalation-worthy.
What the tiers actually trade
| Dimension | Sonnet | Opus |
|---|---|---|
| Cost per token | Meaningfully cheaper — viable for high-volume work | Premium pricing |
| Speed | Faster responses, better for interactive loops | Slower, especially with extended thinking |
| Everyday tasks (drafts, summaries, standard code) | Effectively equivalent — you won't tell the difference | Equivalent, at a premium |
| Hard reasoning, ambiguity, novel problems | Good | The gap appears here — fewer subtle mistakes |
| Long agentic sessions (many-step tasks) | Strong | More reliable over long horizons; recovers better from errors |
| High-stakes single answers (architecture, tricky bugs, hard analysis) | Good | Worth the premium when one mistake costs more than the tokens |
The honest truth about the gap
On the majority of everyday work — routine code, summaries, emails, standard analysis — blind-testing Sonnet against Opus produces a shrug. Each new Sonnet generation absorbs most of what made the previous Opus special. If your workload is 90% everyday tasks, defaulting to Opus is buying a truck to commute.
The gap is real, though, and it lives in three places:
- Depth under ambiguity. Vague requirements, conflicting constraints, problems with no template — Opus-tier models make fewer subtle reasoning errors and notice more of what you didn't say.
- Long-horizon reliability. In agentic work (Claude Code sessions that run for an hour, multi-step pipelines), small per-step error rates compound. A model that's 3% better per decision is dramatically better at step forty.
- The last 10% of hard output. Complex refactors, nuanced strategy memos, subtle bug diagnosis — where Sonnet gives a good answer and Opus gives the answer a senior specialist would.
The cost math people get wrong
Token prices anchor the decision, but tokens are rarely the real cost. The real costs are your time reviewing output and the price of a wrong answer. One workable heuristic:
- If a mistake costs minutes (a reworded email, a regenerated summary) → Sonnet, always.
- If a mistake costs hours (a misleading analysis, a subtle bug that ships) → Opus is cheap insurance.
- If the task runs thousands of times (pipelines, classification, bulk generation) → Sonnet or even Haiku, with Opus reserved for the failure-escalation path.
Practical setups
In Claude Code
Model switching is a command away — the effective pattern is Opus-tier for planning, architecture, and gnarly debugging; Sonnet for the implementation grind once the plan is solid. Subscribers on higher tiers get Opus access within their plan limits, which makes the escalation nearly frictionless.
In the API
Route by task type, not by loyalty: Sonnet as default, Opus behind a flag for the requests your own evals show it earning. A 20-case eval on your real workload answers this question better than any comparison page — including this one.
In the chat apps
Pick per conversation: Opus when you're thinking hard about something once (a strategy, a contract, a design), Sonnet for the daily churn. If you never notice a difference in your work, believe your experience and keep the cheaper default.
Model choice is the smaller half. A well-prompted Sonnet beats a lazily prompted Opus on almost anything — see the ten techniques that matter more than the tier, or install them pre-packaged via the ClaudeThings kits.