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Text · Released Sep 2026

Anthropic Claude Sonnet 5.5

Anthropic's Sonnet-class model for everyday coding and agentic work, a direct upgrade to Sonnet 5 with vision, tool use and a 1M-token context window.

Claude Sonnet 5.5 is a cloud text model built by Anthropic. It is multimodal: alongside a text prompt it accepts images, then replies with generated text. Its context window handles up to 1M input tokens and up to 128K output tokens, and it supports adjustable reasoning effort for harder problems. Generation can be tuned with system instructions. It runs through Runware, OpenRouter, and Anthropic using your own API key, from $2.00 per million input tokens.

Modality
Text
Model ID
anthropic/claude-sonnet-5.5
Specs
Released
Sep 2026
Pricing
$2.00 / 1M in · $10.00 / 1M out
Inputs
Text, Images
Context window
1M in · 128K out
Reasoning
Adjustable effort
Controls
System prompt
Samples

Examples

Generated with Claude Sonnet 5.5 via Runware. The same three prompts run against every text model in the catalog, shown verbatim, so the only thing that changes between two models’ answers is the model.

Short answer52 / 50 words

Explain what an API is to someone who has never written code. Do not use a restaurant or waiter analogy. Plain prose only — no headings, bullet points, or markdown formatting. Maximum 50 words.

An API is a set of agreed rules that lets one piece of software ask another for something. Think of a wall outlet: you don't need to know how electricity is generated, you just plug in following the standard shape. Similarly, apps send requests in a set format and receive predictable answers.

Medium answer161 / 150 words

A two-person startup is deciding whether to build their own user authentication or use a hosted provider. Give them a clear recommendation, then the single strongest argument against your own recommendation. Plain prose only — no headings, bullet points, or markdown formatting. Maximum 150 words.

Use a hosted provider such as Auth0, Clerk, or Supabase Auth. Authentication is a solved problem with an unforgiving failure mode: a subtle mistake in password hashing, session handling, token expiry, or account recovery can expose every user you have. A two-person team has no spare capacity to build, audit, and maintain password resets, social logins, multi-factor authentication, and rate limiting, and none of that differentiates your product. Hosted providers give you all of it in days, with security teams watching for new attack patterns. Your limited engineering time belongs on what customers actually pay for. The strongest argument against this is lock-in and cost at scale. Your user identities, and the login flows built around them, become dependent on a vendor whose pricing, policies, or existence can change. Per-user fees can balloon as you grow, and migrating password hashes and sessions later is painful. Choosing a provider with data export and standard protocols reduces, but does not eliminate, that risk.

Long answer208 / 190–220 words

Write a briefing for a non-technical executive explaining why their company's spending on AI is hard to predict, and what they can do about it. Cover at least three distinct causes. Plain prose only — no headings, bullet points, or markdown formatting. Write exactly 205 words.

AI spending is hard to forecast because most of it is metered, not fixed. Unlike traditional software licenses, where you pay a known amount per seat, AI services typically charge based on usage, measured in units of text processed. When employees find a tool useful, usage climbs quickly, and so does the bill, often without anyone deciding to spend more. A second cause is that costs depend on how the tools are used. A short question and a request to analyze a hundred-page contract can differ in price by a hundredfold, yet both look like one interaction to a manager. Newer systems that work autonomously compound this, because they may take dozens of steps, each billed separately. Third, prices and products keep changing. Vendors release new models, retire old ones, and revise pricing frequently, so a budget built in January may be obsolete by summer. Hidden costs, such as data preparation, security reviews, and specialist staff, also surface late. You can regain control. Have finance and technology leaders set spending caps and alerts for every team. Require that each project report cost per outcome, such as cost per resolved customer inquiry. Negotiate committed-volume discounts only after observing usage. Budget in ranges and review them quarterly rather than annually.

About the creator

Anthropic

Anthropic builds the Claude family of large language models, focused on safety, helpfulness, and honesty.

www.anthropic.com ↗
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