Claude Opus 5.5 is an AI model from Anthropic, released on September 22, 2026. It accepts text and images and produces text. You can use it to review documents, work with code, or read charts and screenshots. Its API model ID is claude-opus-5-5.

Try it on work you can check: a report with known figures, an email based on an approved brief, or a bug with clear steps to reproduce it.

Anthropic's specifications for Opus 5.5, Opus 5, and Fable 5.1 list the following:

A token is a unit of text the model processes. The context window limits how much material it can work with in a request.

These figures describe API use. Claude's chat plans have their own prices and usage limits. Check your account before choosing a model for a large task.

Opus 5.5's standard input and output rates are 20% lower than Opus 5's and 60% lower than Fable 5.1's. The final cost of a task depends on how many tokens it uses, its effort setting, and any tools or caching involved.

Anthropic reports that Opus 5.5 generates output tokens more than 30% faster than Opus 5. It also reports gains in code review, document and spreadsheet work, and reading charts or screenshots.

We haven't run a live head-to-head comparison for this guide. The exercise below lets you check the models on a small task before testing your own work.

Opus 5.5 defaults to medium effort in the API. Opus 5 and Fable 5.1 default to high. Effort controls how much thinking the model applies to a response. Higher settings can increase time and token use. The labels also differ in how much thinking they produce across models.

Start at the recommended default. Raise effort when you can identify a problem in the answer and check whether the next attempt fixes it.

Start with Opus 5.5 for a campaign brief, a document comparison, or a substantial coding task. Give it the source material and explain what a finished result must include. This follows Anthropic's guidance for complex work.

Try Fable when Opus at higher effort still misses a condition, overlooks a conflict between documents, or fails to resolve a bug. Anthropic recommends this approach for demanding reasoning and long tasks.

Compare the specific result you need. Note whether Fable catches the error and how much correction the answer needs.

Keep a few examples from your current Opus 5 setup and run them through Opus 5.5. Check formatting, facts, and any tool calls your app depends on before switching. Anthropic still offers Opus 5 and recommends considering an upgrade.

Open a new chat. Click the model name beside the send button and choose Opus 5.5, when your account offers it. Check More models for other choices. The same menu lets you change effort. Your organization's settings may limit the options.

Check Fable's usage terms before running the comparison. Pro and standard Team seats use pay-as-you-go credits for Fable. Max plans and certain premium seats include an allowance with limits.

You can complete the exercise below without coding. Use the models your account already offers.

Upload a chart and the table behind it. Use files your team permits you to share.

Compare this chart with its source table.

Check the values, dates, units, labels, and written conclusions.
For each mismatch, name the table row and chart label involved.
Flag any text or values you cannot read clearly.

Check whether the written conclusions follow from the data. Flag any
claim that one metric caused another when the data only shows that
they changed together.

End with the three most important fixes.

Check the listed errors against the original files. Record missed errors and false alarms.

Use a separate branch or test project for this comparison.

Investigate this bug using the supplied steps to reproduce it.

Make the smallest change that fixes the problem. Add a test that fails
before the fix and passes afterward. Preserve behavior outside the
reported bug. Ask before adding a dependency.

Run the relevant tests when you have access to the required tools.
Report the files changed, the tests you ran, their results, and any
remaining risks. State clearly when you could not run a check.

Run the tests yourself before accepting the change. Compare how much review and correction each result needs.

For a request with 20,000 uncached input tokens and 5,000 billed output tokens, the standard API charges would be:

This example holds token counts equal. Actual use varies by task and model. Tool fees, caching, and batch discounts can also change the total.

Thinking can add to billed output even when you only see a short reply. Opus 5.5 keeps thinking enabled in the API; the effort setting controls its depth.

For work in Claude's chat app, also note how quickly each model uses your plan allowance and how much time you spend editing.