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Anthropic model°

Claude Sonnet 5

Claude Sonnet 5 is Anthropic's most capable Sonnet-class model, built for coding, agentic work and professional tasks, with adaptive thinking that lets you select how much reasoning effort a request gets.

AnthropicVerified 24/09/2026Released 30/06/2026

01 / decision

Decision snapshot

Each figure sits next to the middle of the field, so it can be read as dear or cheap, wide or narrow, rather than floating on its own. Compared against the 151 models we track, not against an absolute standard.

Capability

Not measured

No published benchmark scores yet

Input / 1M tokens

$2.00

field median $0.43

Output / 1M tokens

$10.00

field median $1.75

Context

1,000K

field median 524K

02 / overview

What Claude Sonnet 5 is, and when to reach for it

Four questions, answered separately, because somebody arrives at one of them rather than at the top of the page.

What it is

The job it was built for, and the job it is not for.

Claude Sonnet 5 is a general-purpose reasoning model from Anthropic aimed at the work most teams actually ship: writing and reviewing code, running agents, and handling professional documents and analysis. Its distinguishing feature is selectable reasoning effort, so the same model can be run cheaply on routine calls and pushed harder on the ones that matter. It is not a specialist image generator or a voice model, it reads images and files but produces text.

When it arrived, and when to use it

Where it sits in its line, and when a sibling is the better pick.

Claude Sonnet 5 first appeared on 30 June 2026 as the top of Anthropic's Sonnet line, the tier that sits between the small fast models and the largest ones. It is the right pick when you want frontier-level coding and agent behaviour without committing every call to the heaviest model available, because you can dial the reasoning effort down. It is the wrong pick for very high-volume, trivially simple classification or extraction work, where a smaller Claude will do the same job for less.

How you reach it

The API, the apps it powers, and what its limits let you do.

Claude Sonnet 5 is reached through the Anthropic API and the Claude apps, and it takes text, images and files in a single request. The million-token context window means you can put a full codebase, a long contract set or a stack of reports in front of it rather than chunking and retrieving, and the large output ceiling means it can write a long document or a substantial patch in one pass. Reasoning effort is chosen per call, from low through to max.

Why it matters

What changes because this exists, or why it does not.

The combination of a very large context window and a per-call effort dial removes two familiar pieces of plumbing: the retrieval layer built only because the context was too small, and the routing layer built to send hard prompts to a bigger model. A team can now run one model across an agent's whole task list and vary the spend by step. For long-running agents and code review over whole repositories, that is a simpler system than most teams currently operate.

Follows Claude Sonnet 4.5, and is the newest in its line. See the whole line.

03 / evidence

How much of this is verified

Split by category, so a strong number never hides a thin evidence base. Verified means we read it on the benchmark's own published results; a provider's claim about its own model is shown and labelled rather than dropped.

No published benchmark scores for this model yet.

We publish a score only where we can link the result to where it was published. Until a benchmark result for this model exists in a source we read, this section stays empty rather than being filled with a provider's marketing figure.

How we decide what counts as evidence

04 / ledger

Benchmark ledger

Every published row, grouped by category, each compared with the best published score on the same benchmark. 'Is 64% good' is a question nobody can answer; '26 points behind the leader' is one anybody can.

Nothing in the ledger yet.

Each row here carries a score, the benchmark it came from, what the leading model scored on the same test, and a link to the published result. Rows appear as results are published and read.

How we decide what counts as evidence

05 / capability

Capability shape

Where this model is strong, and against how many peers. Ranks are against models with evidence in that category, not against everything we track: ranking against models nobody tested would rank who published, not who is better.

No category scores to shape yet.

A category score is the weighted mean of the benchmarks published for it. With no published rows there is nothing to average, and an empty chart drawn at zero would say something false.

How we decide what counts as evidence

06 / cost

What it costs

List API rates as last read from the provider, with the source on every row, plus every change we have recorded since we started tracking it.

Claude Sonnet 5 API pricingSurge45°
ChargePriceUnitRead onSource
Input$2.00per 1M tokens2026-09-24Check
Output$10.00per 1M tokens2026-09-24Check

Claude Sonnet 5 is priced in the mid-range for a frontier-class model, cheaper to run than the largest models on the market while claiming comparable coding and agent performance. The effort setting matters as much as the rate card, since low-effort calls finish with fewer reasoning tokens and cost correspondingly less than max-effort ones on the same input.

What a month costsSurge45°
WorkloadInput / monthOutput / monthCost
A small product team20M tokens5M tokens$90.00
A busy support assistant200M tokens40M tokens$800.00
A document pipeline1000M tokens100M tokens$3,000.00

List API rates, no caching and no batch discount, which both providers offer and which change the answer a great deal. Treat these as the ceiling, not the bill.

07 / specs

Specifications

As listed by the provider's own catalogue and re-read every few hours. Anything absent is absent there too.

SpecificationSurge45°
Context window1,000,000 tokens
Maximum output128,000 tokens
Modalitiestext, image, file
Released30/06/2026
StatusCurrent
Catalogue identifieranthropic/claude-sonnet-5

08 / lineage

Lineage

What this model replaced, what replaced it, and what else its provider has in the field.

Also from Anthropic

09 / line

The line

Every model in this family in release order, so a page from eight months ago says in one glance that two newer ones exist.

Came before

← Claude Sonnet 4.5

Came after

Nothing newer in this line yet.

  1. 01Claude Sonnet 422/05/2025
  2. 02Claude Sonnet 4.529/09/2025
  3. 03Claude Sonnet 530/06/2026

Ordered by release date and worked out from the naming, so a new member slots in as soon as its page exists. A retired model keeps its page and its place in the line.

10 / notes

Our notes

What this model changes for a brand trying to be cited in AI answers, and every change we have logged since it launched.

What it changes for you

A million-token window changes what a model can hold about your category in one sitting, so an answer about your product may now be assembled from a whole set of documents rather than a couple of retrieved snippets. That rewards brands whose positioning, pricing and comparison pages are consistent across the whole site, because inconsistency is now visible within a single context. File and image input also means your PDFs, spec sheets and screenshots are readable source material, not dead weight.

Where buyers meet this model

Buyers meet Claude Sonnet 5 in the Claude consumer and team apps, where it answers questions and works through documents, and through the Anthropic API inside the products their vendors have built on it. Increasingly it also sits behind coding assistants and research tools, so a buyer may be reading its output without seeing Anthropic's name anywhere on the screen.

Change log

Nothing published here yet. Changes appear within hours of a provider announcing them.

11 / questions

Questions

The things people ask about this model, answered from what is on this page rather than from anywhere else.

What is Claude Sonnet 5 best at?
Anthropic positions it for coding, agentic workflows and professional work. The selectable reasoning effort makes it practical to use the same model for both routine and demanding steps in one pipeline.
How does Claude Sonnet 5 differ from other Claude models?
It is the most capable model in Anthropic's Sonnet class, sitting above the smaller, faster Claude models. The adaptive thinking control, with effort levels from low to max, is what lets it cover ground that would otherwise need two different models.
Can Claude Sonnet 5 read images and files?
Yes. It accepts text, images and files as input, so documents, screenshots and diagrams can be passed in directly. Its output is text.
Is Claude Sonnet 5 worth the cost over a smaller model?
It is if your work involves long context, code or multi-step agents, where the larger window and stronger reasoning save you building retrieval and routing layers. For simple high-volume extraction, a smaller Claude is the cheaper answer.
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Is Claude Sonnet 5 recommending you?

Models change what gets cited. We measure whether AI answers name your brand or your competitors across every assistant, and show you what to change.

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