> ## Documentation Index > Fetch the complete documentation index at: https://docs.tess.im/llms.txt > Use this file to discover all available pages before exploring further. # Claude Sonnet 5.5 > Learn about Claude Sonnet 5.5, the Anthropic model that combines speed and intelligence for everyday work: documents, spreadsheets, presentations, customer support and code. Claude Sonnet 5.5 is the second model in Anthropic's Claude 5.5 family. It was built for **well-scoped everyday work**: polished documents, spreadsheets and presentations, customer support, analysis and code fixes. What stands out is the mix of speed and quality. According to Anthropic, Sonnet 5.5 generates output **more than 30% faster** than Sonnet 5, needs fewer steps to finish the same task and, on several professional-work evaluations, comes very close to Claude Opus 5.5. | **Provider model** `claude-sonnet-5-5` | **Context** 1M tokens | **Max output** 128K tokens | **Provider** Anthropic | | :- | :- | :- | :- | | **Input** Text + image | **Output** Text | **Thinking** Adaptive | **Knowledge cutoff** June 2026 | ## When to use Sonnet 5.5 and when to use Opus 5.5 The two models complement each other. Anthropic itself positions Sonnet 5.5 as the faster option for well-defined tasks, and Opus 5.5 as the choice for complex, open-ended work that requires sustained judgment. | | Claude Sonnet 5.5 | Claude Opus 5.5 | | - | - | - | | Best for | Well-scoped everyday tasks, fast iteration and high volume | Complex, open-ended and long-running work | | Speed | Fast | Moderate | | Context / max output | 1M / 128K | 1M / 128K | | Thinking | Adaptive | Adaptive, always on | | Reliable knowledge cutoff | June 2026 | June 2026 | > [!TIP] > > A combination that works well: Opus 5.5 sets the structure of a large piece of work, and Sonnet 5.5 carries out the steps quickly. ## What changes from Claude Sonnet 5 ### Faster and more efficient Sonnet 5.5 is Anthropic's fastest Sonnet model to date. It also completes the same task in fewer steps: in tests cited by Anthropic, it batched tool calls together and needed fewer iterations to reach the result. In practice, work moves faster and costs up to 30% less per task than on Sonnet 5. Atlassian reports that Rovo agents run up to 30% faster with Sonnet 5.5 than with Sonnet 5. And on several benchmarks, Sonnet 5.5 at low or medium effort already beats Sonnet 5's best score for about a tenth of the cost per task. ### More polished documents, spreadsheets and presentations The model has a sharper eye for design. It follows slide templates and delivers materials that need little editing. In an internal Anthropic test, Sonnet 5.5 received a public company's quarterly earnings materials, the call transcripts and a slide template. The task was to build a 10-slide operating review, and two experts judged the first draft ready to send as is. ### Clearer writing Like Opus 5.5, Sonnet 5.5 writes more directly than the previous generation. Early testers described it as a better collaboration partner than Sonnet 5. ### More care with source data Early adopters report that the model rechecks data in source documents and catches errors Sonnet 5 missed. In customer support, Zendesk tested the model on hundreds of real reply and escalation cases: it made fewer wrong decisions and processed tickets 20% faster. A partner serving financial services and healthcare companies reported that, compared with Sonnet 5, the model was more accurate and 2.4x faster on this kind of sensitive work. ## What the benchmarks show In the results published by Anthropic, the jump over Sonnet 5 is large in almost every area. On professional work and computer use, Sonnet 5.5 comes very close to Opus 5.5. | Benchmark | Sonnet 5 | Sonnet 5.5 | Opus 5.5 | What it measures | | - | -: | -: | -: | - | | GDPval-AA v2.1 | 1,449 | **1,844** | 1,846 | Real work across 44 occupations | | AA-Briefcase v1.1 | 1,359 | **1,811** | 1,822 | Long-horizon knowledge work | | OSWorld 2.1 | 57.0% | **80.1%** | 81.8% | Computer use | | Chartography (no tools) | 15.6% | **61.6%** | 64.4% | Chart reading | | Humanity's Last Exam (with tools) | 54.9% | **64.5%** | 67.7% | Multidisciplinary reasoning | | Terminal-Bench 4.0 | 10.3% | **70.6%** | 66.4% (XHigh) | Professional tasks in a terminal | | CursorBench 4.0 | 34.1% | **55.5%** | 57.8% | Ambiguous, multi-file coding | | FrontierCode 1.1 | 42.4% | **52.1%** (XHigh) | 54.4% | Code changes of mergeable quality | In Artificial Analysis's independent evaluation, Sonnet 5.5 scored **56 on the Intelligence Index**, ranking 3rd among 216 models in the same price range. The median for that range is 26. > [!NOTE] > > The benchmarks in the table were published by Anthropic, and some were run by Artificial Analysis on a pre-release version. Results depend on the harness, the tools and the effort used in each measurement. Validate in your own workflow before changing a production setup. ### Where it doesn't lead * Anthropic states that on complex, open-ended work requiring sustained judgment, **Opus 5.5 remains clearly stronger**, even when benchmark scores are close. * On FrontierCode, Sonnet 5.5 scored lower at Max (46.2%) than at XHigh (52.1%), because at Max it tended to make changes beyond the requested scope. * On Artificial Analysis, running at maximum effort, the model produced far more text than the median for its range. For simple tasks, lower effort levels tend to be more efficient. ## Where it adds the most value ### A presentation that has to go out today The numbers are spread across reports, spreadsheets and meeting transcripts, and the presentation has to follow the company template. Sonnet 5.5 gathers the material, respects the template and delivers a first draft that needs little editing. **Expected result:** a presentation in the company's visual standard, with checked numbers, ready for final review. ### A support queue that keeps growing Similar tickets and emails arrive all day, and some need to be escalated. The model answers the routine ones quickly and separates the cases that need a person. **Expected result:** consistent replies for recurring cases and escalations with the context already organized. ### A financial analysis that needs to be checked Questions, extractions and forecasts depend on data spread across many documents. Sonnet 5.5 goes back to the sources to check the numbers before using them. **Expected result:** an analysis where every number traces back to its source and discrepancies are flagged. ## How to apply it in Tess **1. Pick well-scoped work** Prefer recurring, well-defined tasks: documents, spreadsheets, presentations, support replies and analyses. For open-ended, high-risk work, prefer Opus 5.5. **2. Provide the material and the expected format** Send the files, the template and examples of the result. Say who the material is for and how it will be used. **3. Set tools and approvals** Enable only the tools you need. Require confirmation before sending, publishing or changing data. **4. Iterate quickly** The model's speed favors short cycles: ask for a draft, adjust it and ask for the next version. For simple tasks, a lower effort level is usually enough and makes the reply even faster. **5. Ask for a check before delivery** Tell the agent to verify numbers, sources and requirements before finishing. ## Three playbooks to get started ### 1. Results presentation from a template **Input:** period reports, spreadsheets, meeting transcripts and a slide template.\ **Tools:** file reading, data analysis and presentation generation. ```text theme={null} Build a 10-slide operating review from these materials, following the attached template. Use only numbers that appear in the sources and state where each one came from. Highlight results, deviations and next steps. Before finishing, check that every number matches the sources. ``` **Done when:** the presentation follows the template, the numbers match the sources and the material can be reviewed without rework. ### 2. Support triage and replies **Input:** incoming tickets or emails, support policies and examples of good replies.\ **Tools:** knowledge base and integration with the support tool. ```text theme={null} For each ticket, identify the topic and urgency. Reply to recurring cases following the policies and the tone of the examples. When a case requires an exception, a refund or a decision outside the policy, do not reply: escalate it with a summary of the problem, the history and what the customer asked for. ``` **Done when:** routine cases have replies within the policy and escalations arrive with enough context for a decision. ### 3. Financial report with source checks **Input:** spreadsheets, statements, reports and the business question.\ **Tools:** data analysis and spreadsheet and document generation. ```text theme={null} Gather the numbers needed to answer the question and check each one against the original source. Build a spreadsheet with the calculations and an executive summary with the conclusion. Flag discrepancies between sources instead of picking a value. Do not invent missing data; list what is needed to close the analysis. ``` **Done when:** every number has an identified source, discrepancies are explicit and the spreadsheet and summary tell the same story. ## Limitations and best practices * For complex, open-ended, high-impact work, Opus 5.5 remains the safer choice. * Anthropic offers Sonnet 5.5 with a zero data retention option, like Opus 5.5 and Sonnet 5. * A 1M-token context does not replace selecting information. Send only relevant content. * Higher-risk cybersecurity tasks visibly fall back to Sonnet 5. Bug fixes and routine development are not affected. * Some microbiology and virology requests may be flagged in error by the biology safeguards. * Review numbers, citations and files before publishing or sending. * Keep human approval for financial, legal, clinical or high-impact decisions. See also: [Models and Costs](/en/models-and-cost) · [Claude Opus 5.5](/en/claude-opus-5-5) · [Claude Sonnet 5.5 — Anthropic](https://www.anthropic.com/claude-sonnet-5-5) · [Claude Sonnet 5.5 — Anthropic documentation](https://platform.claude.com/docs/en/models/sonnet-5-5/overview). This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.