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Anthropic model°

Claude Opus 4.5

Claude Opus 4.5 is Anthropic's frontier reasoning model, built for complex software engineering, agentic workflows and long-horizon computer use, with text, image and file input.

AnthropicVerified 24/09/2026Released 24/11/2025

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 126 models we track, not against an absolute standard.

Capability

Not measured

No published benchmark scores yet

Input / 1M tokens

$5.00

field median $0.30

Output / 1M tokens

$25.00

field median $1.25

Context

200K

field median 524K

02 / overview

What Claude Opus 4.5 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 Opus 4.5 is the top tier of Anthropic's Claude line, aimed at work that takes many steps rather than one answer: writing and reviewing real codebases, driving agents, and operating a computer over an extended task. It reads text, images and files, so it can take a screenshot, a spec document and a repository extract in the same request. It is not the model you reach for when you want the cheapest possible classification or bulk summarisation pass.

When it arrived, and when to use it

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

Claude Opus 4.5 first appeared on 24 November 2025 as the Opus branch of the Claude family, the branch Anthropic reserves for its hardest reasoning work. Pick it when a task is genuinely long-horizon and the cost of a wrong intermediate step is high, such as an agent editing production code. For high-volume, shallow, latency-sensitive work, a smaller Claude model is the more sensible choice.

How you reach it

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

Claude Opus 4.5 is reached through the Anthropic API and powers the Claude apps and Claude Code. Its context window holds a substantial working set, an extended codebase, a long agent trace or a stack of reference documents, and its output ceiling is large enough to return whole files rather than fragments. Because it accepts images and files alongside text, a single call can combine a design mock, a PDF specification and the code being changed.

Why it matters

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

Claude Opus 4.5 makes agentic work that runs for hours rather than seconds more practical to attempt, because the model can hold the whole task in view and emit long, complete artefacts without being stitched back together. Teams that previously chunked a refactor across many calls and reconciled the results can hand over more of the job in one go. The change is one of degree, not of kind, but for engineering agents the degree matters.

Follows Claude Opus 4.1. Superseded by Claude Opus 5. 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 Opus 4.5 API pricingSurge45°
ChargePriceUnitRead onSource
Input$5.00per 1M tokens2026-09-24Check
Output$25.00per 1M tokens2026-09-24Check

Claude Opus 4.5 sits at the premium end of the market, priced as a frontier model rather than a workhorse, with output charged at several times the rate of input as is normal for the category. It is meaningfully more expensive to run than the smaller Claude models, so the usual pattern is to route only the hard reasoning and agentic steps to it and handle the rest further down the range.

What a month costsSurge45°
WorkloadInput / monthOutput / monthCost
A small product team20M tokens5M tokens$225.00
A busy support assistant200M tokens40M tokens$2,000.00
A document pipeline1000M tokens100M tokens$7,500.00

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 window200,000 tokens
Maximum output64,000 tokens
Modalitiesfile, image, text
Released24/11/2025
StatusCurrent
Catalogue identifieranthropic/claude-opus-4.5

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 Opus 4.1

Came after

Claude Opus 5 →
  1. 01Claude Opus 4.105/08/2025
  2. 02Claude Opus 4.524/11/2025
  3. 03Claude Opus 524/07/2026
  4. 04Claude Opus 5.522/09/2026

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

When an Opus-tier model handles a buyer's question, it will follow more sources, read documents and screenshots, and reconcile what it finds before answering, so thin or contradictory content is more likely to be caught out than rewarded. Documentation, pricing pages and comparison material need to survive being read properly, not just skimmed. For a SaaS brand, that means writing pages that hold up as evidence across a long chain of reasoning, not as a single quotable line.

Where buyers meet this model

Buyers meet Claude Opus 4.5 inside the Claude consumer and team apps, where it is the model chosen for the hardest prompts, and in Claude Code when a developer is working through a repository. Others meet it indirectly, through the Anthropic API, inside products their vendors have built on it. Anywhere a Claude surface answers a research or comparison question, this is the tier doing the reasoning.

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 Opus 4.5 best at?
Complex software engineering, agentic workflows and long-horizon computer use, the tasks that run over many steps rather than resolving in a single response.
Can Claude Opus 4.5 read images and documents?
Yes. It accepts text, images and files, so a single request can combine a screenshot, a document and the code or content being worked on.
When should you use a smaller Claude model instead?
For high-volume, shallow or latency-sensitive work such as classification or routine summarisation, where the reasoning depth of Opus is not needed and the cost difference is significant.
Where do people encounter Claude Opus 4.5?
In the Claude apps, in Claude Code, and through the Anthropic API inside third-party products built on it.
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Is Claude Opus 4.5 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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