Sonnet 5.5 migration: test the full task

A Sonnet 5.5 migration should be judged on completed business work: does the integration still behave correctly, does the output meet your acceptance criteria, and what does each accepted task cost after retries and review? A lower token count is useful only alongside those answers.

For a business already using Claude in a repeatable workflow, compare the current and proposed versions in a non-production test before changing the live integration. The worked example below shows how to make that comparison reviewable.

What changed with Sonnet 5.5?

Anthropic launched Sonnet 5.5 on 28 September 2026. Its published base prices are USD $2 per million input tokens, $10 per million output tokens and $0.20 per million cache-read tokens, the same rates as Sonnet 5. Anthropic's claims of faster output and lower task costs describe its own testing, not a guaranteed saving for your business or a per-token price cut. Anthropic's announcement and API pricing. These are API rates, not subscription prices.

Compatibility depends on the integration path. Anthropic documents Messages API changes affecting thinking settings, forced tool selection and content-block handling. Its migration guidance separately says Claude Managed Agents needs only a model-name change. Identify which path you use before estimating the migration work. Anthropic's migration guide.

The following test design is practical guidance, not an independent benchmark or a promise that your existing workflow needs every documented change.

Define an accepted task before measuring cost

Consider an illustrative integration that extracts an order request into a draft business record. The draft goes to a person for approval; the model does not confirm the order, charge a customer or send a message.

Define acceptance before running either version. For example, the record must contain the supplied customer reference, requested items and quantities; missing information must remain unresolved; and the result must fit the application's expected structure. Decide how conflicting instructions should be handled and who judges exceptions.

Count each business request once. Retrying a failed request does not create a new completed task. Keep first-pass acceptance separate from acceptance after correction so an apparently successful result cannot hide extra work.

Run the same work through both versions

Prepare a representative set using synthetic or appropriately approved information. Include an ordinary request, missing details, conflicting quantities, an unsupported item and a destination failure. Establish the expected result or escalation for each case.

Use a test destination that cannot update real customer records or deliver messages. Keep the task set and acceptance criteria consistent. Record model settings, prompts, tool definitions and any changes required for compatibility so you can explain differences in the results.

Ask the integration owner to check the migration guide against the actual implementation. Test response parsing, tool requests, errors and repeat attempts. Check that the intended draft-record action actually occurs. The guide warns that automatic tool selection does not guarantee a tool call. A valid response alone is not proof of completion.

Compare cost per accepted task

Use this scorecard for the same test set. Keep failures and abandoned attempts in the cost totals.

Calculate API and tool cost per accepted task by dividing all relevant test charges by the number of accepted tasks. If none are accepted, report that outcome rather than a cost of zero.

Show review minutes alongside the result. If you convert them into a monetary cost, state the labour-rate assumption and use it consistently. Keep one-off migration and testing effort separate from recurring operating cost. Token charges alone do not describe the whole business case.

Use actual platform billing rules, including relevant cache-write and additional tool charges, and distinguish charges from estimates. A small trial is evidence about those examples, not a forecast that every future task will behave identically.

Choose migrate, hold or fix and retest

Agree the decision conditions before comparing results. Require acceptable output quality and integration behaviour as well as an affordable operating cost. A faster result should not compensate for an unresolved failure that matters to the business.

If the proposal passes, name the release owner, define a limited initial rollout and retain a tested route back to the previous working configuration. Decide what evidence would trigger that rollback. If the result fails, record whether the next step is to fix compatibility, revise the task or retain the current version.

Use the AI ROI guide to place one-off migration work within the wider investment decision. For help testing an AI integration within a website or internal workflow, explore bespoke business system development. Bring the existing workflow, its acceptance criteria and an example of the work it needs to complete.