Two illuminated computing modules represent alternative Sonnet 5.5 and Opus 5.5 routes for workload evaluation.

Comparison

Claude Sonnet 5.5 vs Opus 5.5: Which Model Fits Your Tasks?

Jacey

September 26, 2026

Updated on September 29, 2026

10 min read

Start your evaluation with Sonnet 5.5 for well-scoped daily work; test Opus 5.5 where complex, open-ended tasks need sustained judgment. Both models are released. Sonnet 5.5 has lower standard input/output token prices, but the model that delivers an accepted result at the right cost and latency should own that task class.

For EvoLink users, the decision is which model to select through the unified gateway and when to escalate a task. Check Sonnet 5.5 and Opus 5.5 for current route details and prices. This is a selection framework based on official documentation and explicit test methods, not an EvoLink benchmark or a guarantee that either model wins your workload.

Claude Sonnet 5.5 vs Opus 5.5: confirmed differences

Anthropic positions Sonnet 5.5 as a complement to Opus for everyday work. Its release report also says Opus remains stronger on complex, open-ended tasks. That is provider evidence; the selection policy below is a starting hypothesis to validate on your own application.

Decision input	Claude Sonnet 5.5	Claude Opus 5.5
Official release	September 28, 2026	September 22, 2026
API identifier	`claude-sonnet-5-5`	`claude-opus-5-5`
Context / maximum output	1M / 128K tokens	1M / 128K tokens
Standard Anthropic input / output price	$2 / $10 per million tokens	$4 / $20 per million tokens
Standard Anthropic cache-read price	$0.20 per million tokens	$0.20 per million tokens
Initial evaluation role	Scoped coding and everyday tool-based work	Complex work requiring sustained judgment
Original testing in this article	None	None

Prices are Anthropic standard rates, checked September 29, 2026, not an EvoLink quote. Use the existing Sonnet 5.5 pricing and Opus 5.5 pricing sections for gateway rates. Sonnet input and output are half the official Opus rates, but cache reads cost the same: a cache-heavy workflow does not automatically halve its bill.

Choose the first candidate by task, then measure

For a coding workflow, distinguish an isolated bug with a clear regression test from an ambiguous change spanning multiple systems. Sonnet is a reasonable first candidate for the former. Opus deserves evaluation for the latter, especially when repeated repair consumes more time than the initial generation. Neither choice should bypass the repository tests.

The same logic applies to document workflows. If your existing model routinely misses required clauses, loses citations, or produces outputs that need manual restructuring, test those exact cases. Do not replace the requirement with a general impression that one model writes better.

Workload situation	First candidate to evaluate	Evidence that would justify promotion
Scoped bug fix or well-defined implementation	Sonnet 5.5	Accepted patches, regression checks, elapsed time, and total billed cost
Ambiguous architecture or cross-system change	Opus 5.5	Requirements resolved with fewer repair cycles and no critical regressions
Repeated extraction or document formatting	Sonnet 5.5	Required fields and source facts preserved within budget
Long analysis with conflicting requirements	Opus 5.5	Reasoning and citations survive review with less manual repair
High-volume classification already meets targets	Keep the baseline; sample Sonnet 5.5	Equal or better accuracy within latency and cost limits
Multiple agents repeat or undo work	Measure the full workflow before choosing tiers	Fewer handoff failures and lower cost per accepted outcome

These are evaluation recommendations, not measured rankings. Include ordinary traffic and failure cases; a test set containing only easy tasks cannot tell you whether the more expensive model earns its place on hard ones.

Effort and compatibility can change the choice

Treat the candidate as a model plus an effort setting, prompt, tools, and route. Do not compare Sonnet at a low setting with Opus at a high setting and attribute every cost difference to the model. Run an effort sweep where supported, keeping the task and acceptance criteria fixed. A higher setting can improve a difficult outcome while wasting tokens on an easy one.

Check the Sonnet 5.5 migration guide before reusing a client. Forced tool choice is unsupported on the upstream model, and thinking history cannot be copied blindly between models. Sonnet supports between_tools at high effort or below to turn off up-front thinking, but tool progress may still appear in thinking blocks. Verify the controls and conversion behavior of the actual gateway route.

Keep a working model if the new configuration fails a requirement or the gain is too small to justify a migration. The Sonnet 5 upgrade guide explains how to preserve and replay an existing deployment. Selecting a new default should not erase the configuration you know how to restore.

Compare cost per successful task

Glowing data packets pass through a review core, with an amber retry loop illustrating cost per successful task.

A token price cannot tell you how many attempts a workflow needs. Compare the cost of delivering an accepted result:

Cost per successful task = total billed cost for the task set / accepted tasks

Include all attempts in the numerator: successful calls, failed attempts that incurred charges, retries, and model calls made during repair. Use the route's actual billing dimensions so input, output, and cache charges are counted once. If no tasks pass, report zero successes and the money spent; do not present a finite cost per success.

Consider this illustrative arithmetic, not measured model performance:

Hypothetical route	Total billed cost over 100 tasks	Accepted tasks	Cost per accepted task
Current route	$12	80	$0.15
Candidate route	$15	100	$0.15

The candidate spends more in total and reaches the same cost per accepted outcome. Whether that is preferable still depends on your latency requirement, the seriousness of failures, and the budget available. If reviewer time matters, record it separately; API cost alone does not capture the entire operating expense.

Neither hypothetical row represents Sonnet 5.5 or Opus 5.5. Their real task costs require measured usage and outcomes. Record cache writes and reads separately, and include billed thinking output even when its text is not displayed. A token-price comparison alone misses those costs.

Test the workflow before splitting it across models

For an agent system, splitting planning and execution between models creates another boundary to test. A lower-priced worker may require more instructions, review, and retries from the planner. Use a bounded policy rather than an unlimited escalation loop:

Task outcome	Suggested application policy	Budget or correctness control
Sonnet result passes the task checks	Return the accepted result	Do not add an Opus review without a reason
Result fails a recoverable quality check	Escalate once to an evaluated Opus configuration	Carry the task and failure summary; validate history compatibility
Request fails because of authentication or an invalid parameter	Correct the request or surface the error	Changing the model is not a fix for invalid credentials
An external action may already have happened	Reconcile state before any retry	Use idempotency and prevent duplicate effects
Budget or deadline is exhausted	Stop and use the application's failure path	Record the failure instead of hiding it behind more attempts

Start with the complete current workflow as a baseline. Test a candidate against the same task set, tool environment, and success rubric. Only then change one stage at a time. Record which stage caused a failure and whether a downstream model recovered it. This helps distinguish a model improvement from a change to the workflow around it.

For latency-sensitive applications, capture both time to first useful response and time to accepted completion. A short first response does not settle how quickly the user receives a usable result. For asynchronous workloads, deadline completion and total spend may matter more than the first token.

A practical evaluation through EvoLink

Use the unified gateway as the integration entry point while treating each model's behavior as a separate contract.

Freeze the baseline. Save your current model, prompts, supported settings, tool definitions, retry policy, and a representative task set.
Define success before running candidates. Use tests or a review rubric that reflects the product outcome. Include difficult cases and ordinary traffic.
Run both candidates on the same workload. Verify access and supported settings for each route. Log the model, effort, prompt version, and tool environment.
Compare complete outcomes. Track accepted tasks, failures, latency, total billed usage, and reviewer repair. Separate cold-cache and warm-cache runs when relevant.
Promote only where the evidence supports it. Start with a limited task class and preserve rollback. A model can be useful for one job without replacing the entire application baseline.

Recheck the task set when the product changes. A routing policy that worked for short bug fixes may fail on larger repositories or a new tool environment. Restore the previous configuration if quality, latency, or spending breaks the requirements you chose before evaluation.

Automatic fallback is a separate application or gateway capability to verify. Do not assume this evaluation plan configures it for you. A fallback also needs to meet the task's requirements, and retrying a tool-driven workflow must not duplicate external actions.

Review Sonnet 5.5 for everyday tasks Compare the Opus 5.5 route

Sonnet 5.5 release date and confirmed facts: check the evidence behind the release status.
Opus 5.5 vs Opus 5: evaluate an available Opus upgrade.
Sonnet 5 coding-agent routing: build a workload-specific baseline.

FAQ

Is Sonnet 5.5 better than Opus 5.5?

There is no universal winner. Anthropic reports strong Sonnet results while retaining Opus for more complex, open-ended work. Match model and effort to the task, and measure accepted outcomes rather than declaring a winner from a single benchmark.

Do I still need to wait for Sonnet 5.5 to launch?

No. Anthropic released Sonnet 5.5 on September 28, 2026. Check the actual gateway route and account access before testing; official release and platform-specific access are separate facts.

Is Sonnet 5.5 half the cost of Opus 5.5?

Its official standard input/output token rates are half, but cache reads have the same rate. Different token use, retries, effort, and acceptance rates mean your total task bill need not be half.

Is the $4 / $20 price an EvoLink price?

No. It is Anthropic's standard Opus 5.5 input/output price per million tokens. Use EvoLink's existing model-page pricing for the gateway quote and your bill for actual consumption.

Should every sub-agent use Opus 5.5?

This guide does not establish that policy. Measure the full workflow first, then change individual stages to understand quality, handoff failures, and total cost.

Can I route a failed Sonnet task to Opus?

You can design and test that policy in your application. Confirm route access, history compatibility, a retry budget, and idempotency for external actions. A shared API key does not by itself configure automatic fallback.

What would justify switching later?

The candidate should meet compatibility and quality requirements, fit your latency and cost limits, and have a tested rollback path. Set those requirements before seeing its results.

Sources

Updated September 29, 2026. Official facts and prices are attributed to Anthropic. Routing rules, the test method, and hypothetical arithmetic are editorial guidance, not results from an EvoLink model benchmark.

All Posts

#Claude Sonnet 5.5 #Claude Opus 5.5 #model selection #cost per task