AI Model Comparison
Claude Opus vs Sonnet
Anthropic's two main tiers, one practical question: which work actually needs Opus, and when is Sonnet the better engineering decision?
What to know before choosing Opus or Sonnet
Claude ships in tiers, and the decision usually comes down to two of them. Opus is the frontier tier, priced for the work that justifies it, and Sonnet is the volume tier, tuned to cover most production work at a much lower price. The interesting question is not which is better, because Opus is, but where the gap actually shows up in your work, and whether it is worth the multiple.
The current generation brought the tiers closer than they have ever been: Claude Sonnet 5 closes much of the gap to Opus on agentic coding, while Claude Opus 5 pushes the ceiling with Anthropic's strongest coding and knowledge-work results to date. Both lines are compared below with live official pricing, current generation and previous.
Where the app tiers fit in
If you use Claude through the app rather than the API, the subscription tier decides how much of each model you get. Prices checked August 2026; Anthropic's own page carries the current numbers.
Claude
AnthropicOpus and Sonnet are not rivals, they are sizes
Anthropic ships Claude in tiers, like engine sizes in one car line: Opus is the largest and most capable, Sonnet the balanced middle, Haiku the small fast one. Inside the Claude app the tier is largely picked for you; over the API you choose it yourself and pay per million tokens accordingly (a token is a short chunk of text, roughly three quarters of a word).
The board below compares the two main tiers so you can settle the Sonnet vs Opus question for your own work: which tasks truly need Opus, and where Sonnet does the same job for a fraction of the price.
The lineups, side by side
Live specs and per-million-token prices, straight from the providers. Where several providers serve a model, the lowest price is shown.
The Opus line
AnthropicAnthropic's frontier tier, built for complex agentic coding, deep research and enterprise knowledge work. Opus 5 carries a 1M token context window, up to 128K output tokens, and adaptive thinking that spends reasoning depth where the task is hard.
The Sonnet line
AnthropicThe volume tier, tuned for production traffic. Sonnet 5 is the strongest agent-focused Sonnet yet, with near-Opus coding, a 1M token context window, and its biggest gains on terminal-based agent benchmarks.
What Opus buys you
Opus earns its price where the marginal quality compounds: agents that run unattended for hours, multi-file refactors where one wrong assumption cascades, research and legal-grade knowledge work where a reviewer would catch a cheaper model's mistakes anyway, just expensively. Opus 5 launched at the top of Anthropic's coding and knowledge-work evaluations, and its adaptive thinking spends reasoning depth only where a request is actually hard, which softens the cost story on mixed workloads.
The previous generation is still a serious option: Opus 4.8 refined its tool calling to complete agent tasks in fewer steps.
Why Sonnet is usually the right default
Anthropic's own history argues for Sonnet as the starting point. When Sonnet 4.6 shipped, early-access developers often preferred it to the then-current Opus for real work, and Sonnet 5 repeats the pattern, delivering near-Opus agentic coding with its biggest jump on terminal-based agent benchmarks, exactly the lane most coding agents live in. At production volume the price gap between the tiers compounds into real money, and a task Sonnet completes correctly is not improved by Opus completing it correctly for several times the cost.
The honest default: start on Sonnet, measure, and promote to Opus only the task types where the difference is visible in your own results.
The pattern that beats either: route by task
Teams running Claude at scale rarely choose one tier, they compose them. A common shape: Opus plans and reviews, Sonnet executes the bulk of the steps, and Haiku 4.5 handles the high-volume simple calls, classification, extraction and triage, where it delivers previous-generation Sonnet coding quality at roughly a third of the cost and more than twice the speed. Add an escalation rule, retry the failures one tier up, and the blended cost lands far below all-Opus at nearly all-Opus quality.
On an LLM gateway this pattern is configuration rather than code: every Claude tier sits behind the same OpenAI-compatible endpoint on Opper, so routing rules and fallbacks are a config change, and each call is traced so you can see which tier actually earned its tokens.
Compare the models head-to-head
Full side-by-side specs, pricing, privacy and benchmarks for the pairings people actually weigh.
Or build your own on the interactive compare page, up to four models at a time.
Common questions
Is Claude Opus worth it over Sonnet?
For some work, clearly yes: unattended agents, the hardest refactors, research where errors are expensive. For most interactive coding and production traffic, Sonnet 5's near-Opus quality at a fraction of the price wins the engineering argument. The reliable way to decide is to run both on a sample of your real tasks and check whether the delta shows up at all.
How big is the price difference?
The tiers are priced multiples apart, not percentages, and exact figures move with providers, so check the live cards above or the head-to-head page for current numbers. Remember that thinking tokens bill as output on both tiers, so reasoning-heavy work amplifies the gap.
Do Opus and Sonnet have the same context window?
In the current generation, yes: Opus 5 and Sonnet 5 both work across 1 million token context windows, so context size is no longer a reason to pick one over the other. The difference is reasoning depth and reliability on the hardest tasks, not how much they can read.
What about Haiku?
Claude Haiku 4.5 is the third tier, and it matters to this choice more than people assume: it was the first Haiku with extended thinking and it matches previous-generation Sonnet coding quality, which makes it the natural landing spot for the large share of calls that never needed Sonnet in the first place.