Claude Sonnet 5.5 vs Opus 5.5: Which Should You Use?

The main difference between Sonnet 5.5 and Opus 5.5

Claude Sonnet 5.5 and Claude Opus 5.5 belong to the same 5.5 generation, but Anthropic gives them different jobs.

Anthropic describes Sonnet 5.5 as the faster, lower-cost complement to Opus 5.5. Its launch material specifically highlights well-scoped everyday tasks, fixing bugs, fast iteration, document creation, slides, spreadsheets and design-oriented work.

Opus 5.5 is positioned for a different class of workload: complex work that requires careful judgment, long-running agentic coding, difficult research and knowledge work where the model has to decide what matters rather than simply execute a well-defined instruction.

This distinction is more useful than simply asking which model has the higher benchmark score. Sonnet 5.5 is close enough to Opus 5.5 on several evaluations that paying more for Opus on every task may not make sense. At the same time, Anthropic says its own testing and external testing still find Opus clearly stronger when the work is complex, open-ended and requires sustained judgment.

Official sources: Introducing Claude Sonnet 5.5 and Introducing Claude Opus 5.5 .

Sonnet 5.5 vs Opus 5.5 specifications and pricing

The token prices make the headline difference easy to understand: for ordinary uncached input and output, Opus 5.5 is priced at roughly twice Sonnet 5.5.

But per-token price is not the same as cost per completed task. Effort settings change how long the model works, how many tool calls it makes and how many reasoning tokens it consumes. A lower-priced model running at a very high effort can sometimes approach the total task cost of a more expensive model running efficiently at a lower effort.

How close is Sonnet 5.5 to Opus 5.5 on benchmarks?

Surprisingly close in several categories.

The GDPval result is especially striking: Sonnet 5.5 scored 1844 while Opus 5.5 scored 1846, essentially adjacent in Anthropic's published table.

CursorBench is similarly close at 55.5% versus 57.8%, and OSWorld is 80.1% versus 81.8%.

Terminal-Bench is a useful reminder not to reduce model selection to a single hierarchy. Sonnet 5.5's published 70.6% score is higher than the 66.4% Opus figure in that table.

Anthropic makes the same broader point in its launch material: benchmark margins increasingly fail to capture some of the practical differences it sees between models during difficult real-world work.

Benchmark source: Anthropic Sonnet 5.5 performance table .

Which model makes more sense for coding?

It depends more on the shape of the coding task than on whether the task contains code.

Sonnet 5.5 for everyday development

Sonnet 5.5 is an appealing choice for work such as fixing a bug, implementing a specified feature, creating a component, reviewing a normal pull request, modifying a known part of a codebase or iterating rapidly on an application.

Anthropic says the model batches tool calls more efficiently than Sonnet 5 in its testing, and early testers reported fewer steps and faster iteration. Sonnet's lower token price also matters when an IDE, coding agent or CI workflow is invoking the model thousands of times.

Opus 5.5 for sprawling engineering work

Opus becomes more attractive when the problem is not merely “write this code” but “understand this system, decide what should change and carry the work through.”

Anthropic highlights Opus 5.5 for large codebase migrations, audits and long-running jobs. Its launch material describes early-access examples involving hundreds of thousands of lines of code and multi-hour or overnight autonomous work.

A practical engineering strategy is therefore to use Opus where the architecture or diagnosis itself is difficult, then use Sonnet for more of the implementation once the plan has become concrete.

Sonnet 5.5 vs Opus 5.5 for agents and tool use

Agentic workloads magnify cost differences because a single user request can produce many model turns, tool calls, cached context reads and intermediate reasoning steps.

Sonnet 5.5 has a natural advantage when the workflow is repeated frequently and the decisions at each step are relatively bounded. Examples include support triage, recurring document processing, standardized coding work, routine research extraction and internal business automations.

Opus 5.5 is better aligned with agents that may have to operate for a long time, recover from unexpected conditions, reconcile conflicting evidence or make architectural decisions while working.

Anthropic's broader platform guidance follows a similar principle: evaluate cost per successful task rather than assuming the model with the lowest price per token will always produce the lowest operating cost.

What about research, analysis and knowledge work?

Sonnet 5.5 made one of its biggest gains in this area. Anthropic reports a GDPval-AA score of 1844, just two points below Opus 5.5's 1846 in the published launch table.

It also scores 1811 on AA-Briefcase compared with 1822 for Opus 5.5, while remaining substantially cheaper per token.

That makes Sonnet attractive for high-volume professional work where the instructions are already well defined: summarizing research, reviewing documents, extracting data, creating routine reports, producing first drafts and preparing recurring business analysis.

Opus is more compelling when the research question itself is uncertain, sources conflict, the model has to challenge assumptions, or a plausible-looking but unsupported conclusion would be particularly costly.

Anthropic's Opus launch material repeatedly emphasizes this deeper investigative behavior. Its own internal research tests and early-access feedback focus on checking evidence beyond the first plausible answer, finding hidden problems and sustaining reasoning over long investigations.

Which should you use for writing, slides and documents?

Sonnet 5.5 is much more competitive here than the old assumption that “Opus is for quality and Sonnet is for speed” would suggest.

Anthropic specifically highlights polished documents, slides, spreadsheets and design as Sonnet 5.5 strengths. In an internal example described in its launch announcement, Sonnet received a company's earnings materials and a slide template and produced a ten-slide operating review that two experts judged ready to send on the first draft.

That makes Sonnet a sensible starting model for proposals, internal reports, decks, support content, routine marketing copy and document-heavy office workflows.

Opus still has a role when the writing depends on difficult reasoning rather than merely prose quality: executive recommendations, complex financial interpretation, strategy documents, legal-style issue analysis, deep synthesis or situations where the model must decide which evidence deserves the most weight.

Which one feels faster?

Sonnet is deliberately the faster tier.

Anthropic calls Sonnet 5.5 its fastest Sonnet model at launch and says it generates output more than 30% faster than Sonnet 5. It is designed for fast iteration, where waiting time becomes noticeable because the user is repeatedly asking for small or medium changes.

Opus 5.5 has moderate comparative latency in Anthropic's platform documentation. It is also more than 30% faster than the previous Opus 5, but its role is still capability-first rather than being the latency-focused model in the pair.

There is also an optional Opus 5.5 Fast mode on supported Claude Code and Claude Platform surfaces. Anthropic says it can run up to 2.5 times faster, but the price rises to $8 per million input tokens and $40 per million output tokens.

That Fast mode can be useful when Opus-level behavior is required but interaction latency is especially valuable. It should not be confused with the normal $4/$20 Opus 5.5 pricing.

Opus specifications: Claude Opus 5.5 model overview .

API cost: what does the 2× price difference mean in practice?

Suppose a request uses one million normal input tokens and produces 100,000 output tokens.

At identical token usage, the normal uncached calculation is straightforward: Opus costs roughly twice as much.

Real agent workloads are less simple. If Opus solves a difficult task in fewer attempts, makes fewer wrong turns or eliminates a human escalation, its cost per successful outcome can be competitive even with the higher token price.

The reverse is also true. If Sonnet handles the workload reliably at medium or low effort, paying Opus prices for every request creates expense without necessarily creating useful additional quality.

Prompt caching changes the equation

Both models currently charge the same $0.20 per million tokens for cache reads. That matters for long-running agents whose repeated context is mostly read from cache.

Cache writes differ: Sonnet's five-minute cache write price is $2.50 per million tokens while Opus is $5.

Effort settings can change the comparison

Claude's effort parameter controls how much work the model does before and during the answer, including thinking, tool calls and self-checking.

Higher effort generally gives the model more room to solve difficult problems, but it also raises token use and latency.

Anthropic says Sonnet 5.5 complements Opus best at lower effort settings. At high settings Sonnet can become much more capable, but the cost-per-task difference can narrow because it works for longer.

Opus 5.5 is unusual because its Claude Platform default effort is medium, not high. Anthropic recommends starting there and running your own effort sweep instead of assuming the same effort label produces the same economics across models.

Anthropic effort documentation: Controlling Claude effort .

What if you are choosing inside the Claude app rather than the API?

The same conceptual distinction still helps.

If you are working interactively and want quick back-and-forth on coding, drafts, spreadsheets, slides, ordinary analysis or repeated revisions, Sonnet 5.5 is designed to make that iteration feel fast.

Switch to Opus when the work starts becoming less specified: you are asking Claude to investigate, make strategic tradeoffs, understand a large system, reconcile conflicting evidence or work autonomously for a long period.

The Claude apps also expose effort differently from raw API defaults. Anthropic says Sonnet 5.5 uses Medium effort by default in Claude Code and its apps, while the Claude Platform defaults Sonnet to High. Opus 5.5's documented Claude Platform default is Medium.

A practical way to choose between Sonnet 5.5 and Opus 5.5

Instead of asking which model is generally better, ask what kind of failure you are trying to avoid.

1. Is the task clearly specified? If the inputs, output and success criteria are obvious, start by testing Sonnet.
2. Will this run at high volume? If the workflow executes hundreds or thousands of times, Sonnet's lower price becomes increasingly important.
3. Does the model need to decide what the problem actually is? Ambiguous diagnosis, architecture and research are stronger reasons to test Opus.
4. Will the task run unattended for a long period? Long-horizon autonomous work is one of the areas Anthropic specifically highlights for Opus 5.5.
5. How expensive is a wrong answer? Where a subtle reasoning failure creates large downstream cost, evaluate whether Opus materially improves your own success rate.
6. Compare cost per successful task. Do not stop at the token price. Measure total tokens, retries, latency, tool calls and human correction.

Which model fits common tasks?

Frequently asked questions

The practical difference is execution versus judgment

Sonnet 5.5 has moved close enough to Opus 5.5 on several benchmarks that “always choose Opus for serious work” is no longer a useful rule.

For well-defined work, Sonnet offers a compelling combination of capability, speed and price. That includes a large amount of everyday coding, office work, document production, support, automation and repeated API traffic.

Opus earns its place when the difficulty is not merely producing the output but deciding what the correct approach should be. Large code migrations, messy investigations, high-autonomy agents and complex professional analysis are the kinds of tasks Anthropic continues to associate with Opus 5.5.

For developers, the most reliable answer is to evaluate both models on a representative set of your own tasks. Measure successful completions, total token use, latency, retries and human corrections. That tells you considerably more than comparing model names or a single benchmark score.