Anthropic

Claude 4.7 Opus

Opus 4.7 is the next generation of Anthropic's Opus family, built for long-running, asynchronous agents. Building on the coding and agentic strengths of Opus 4.6, it delivers stronger performance on...

Apr 16, 2026 1M context 128,000 tokens output

Text Image File Tools Structured Output Reasoning

Overview ↓ About ↓ Capabilities ↓ Pricing ↓ Price Comparison ↓ Providers ↓ Parameters ↓ Compare ↓ Tools ↓ Resources ↓ Community ↓

Model Overview

High-signal model metadata in a structured two-column overview table.

Provider

The entity that provides this model.

Anthropic

Model ID

The routed model identifier exposed by upstream providers.

anthropic/claude-opus-4.7

Input Context Window

The number of tokens supported by the input context window.

1M tokens

Maximum Output Tokens

The number of tokens that can be generated by the model in a single request.

128,000 tokens tokens

Open Source

Whether the model's code is available for public use.

Release Date

When the model was first released.

Apr 16, 2026 1 month ago

Knowledge Cut-off Date

When the model's knowledge was last updated.

Unknown

API Providers

The providers that offer this model. This is not an exhaustive list.

Google, Amazon Bedrock, Anthropic

Modalities

Types of data this model can process.

Text Image File

What is Claude 4.7 Opus

A fuller summary of positioning, capabilities, and source-specific details for Claude 4.7 Opus.

Capabilities

What Claude 4.7 Opus supports

Reasoning Controls

OpenRouter lists GPT-5.5 with reasoning support and explicit reasoning-related request parameters.

JSON

Structured Outputs

Structured output settings are exposed through OpenRouter for schema-driven or format-controlled responses.

Tool Calling

Tool invocation and tool selection are supported in the routed OpenRouter interface for this model.

Multimodal I/O

This model accepts text input, image input, file input and returns text output.

CTX

Large Context Window

OpenRouter currently lists a context window of 1M with up to 128,000 tokens maximum output tokens.

Pricing for Claude 4.7 Opus

Primary API pricing shown in the same “quick compare” spirit as the reference page.

Input tokens $5.00 Per million tokens

Output tokens $25.00 Per million tokens

Price Comparison

Additional usage-cost dimensions synced into the project for this model.

Web search $10000.00

Cache read $0.50

Cache write $6.25

maxTemperature 1

maxResponseSize 128,000 tokens

API Access & Providers

Places where this model is available, based on the synced detail-page metadata.

Google Amazon Bedrock Anthropic

Provider Endpoints

Endpoint-level provider data currently available for this model.

Google

Max output: 128,000 Supported params: 8 Implicit caching: No

Amazon Bedrock

Max output: 128,000 Supported params: 9 Implicit caching: No

Amazon Bedrock

Max output: 128,000 1d uptime: 100.0% Supported params: 9 Implicit caching: No

Anthropic

Max output: 128,000 1d uptime: 99.9% Supported params: 9 Implicit caching: No

Google

Max output: 128,000 1d uptime: 100.0% Supported params: 8 Implicit caching: No

Anthropic

Max output: 128,000 1d uptime: 99.6% Supported params: 9 Implicit caching: No

Configuration & Parameters

The configurable options currently documented for this model.

Reasoning

Select

When enabled, the model will explain its thought process step-by-step before providing a final answer. This can help users understand how the model arrived at its conclusions, but may result in longer responses. Opus 4.7 uses adaptive thinking mode. The model dynamically decides when and how much to think.

Default: false

Disabled Enabled

Effort

Select

Controls how much the model thinks vs. how quickly it responds. Higher effort produces better quality but uses more tokens and is slower. Recommended: High or Extra High for coding and agentic work; Medium for general use; Low for short, latency-sensitive tasks. Only applies when Reasoning is enabled.

Default: medium

Low Medium High Extra High Max

Supported Request Parameters

Parameters currently listed by OpenRouter or the local catalog for this model.

Reasoning Effort

Resources & Documentation

Official model cards, release notes, docs, and other references synced from the source page.

Announcement Blog Post

→

About Claude

→

Anthropic Prompt Engineering Resources

→

Official Website

→

Acceptable Use Policy

→

Anthropic Trust Center

→

OpenRouter Model Page OpenRouter

→

Compare Claude 4.7 Opus with related models

Jump straight into the most relevant side-by-side comparison pages for this model.

Claude 4.7 Opus vs Claude 4 Sonnet

Compare Claude 4.7 Opus and Claude 4 Sonnet across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for long-context workloads versus reasoning-heavy tasks.

Claude 4.7 Opus vs Claude 4 Opus

Compare Claude 4.7 Opus and Claude 4 Opus across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for long-context workloads versus reasoning-heavy tasks.

Claude 4.8 Opus vs Claude 4.7 Opus

Compare Claude 4.8 Opus and Claude 4.7 Opus across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for reasoning-heavy tasks versus long-context workloads.

Claude 4.7 Opus vs Claude 4.6 Sonnet

Compare Claude 4.7 Opus and Claude 4.6 Sonnet across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for long-context workloads versus long-context workloads.

Claude 4.7 Opus vs Claude 4.6 Opus

Compare Claude 4.7 Opus and Claude 4.6 Opus across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for long-context workloads versus long-context workloads.

Claude 4.7 Opus vs Claude 4.5 Sonnet

Compare Claude 4.7 Opus and Claude 4.5 Sonnet across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for long-context workloads versus reasoning-heavy tasks.

AI tools related to Claude 4.7 Opus

These tools are strongly connected to Claude 4.7 Opus through direct product references, provider mentions, or explicit model mappings.

AI Chatbot

LongShot AI

LongShot AI is an AI-powered content creation platform built to help users plan, generate, and optimize articles for search engines like Google, ChatGPT, Perplexity, and Gemini. It provides features such as real-time content generation, fact-checking, semantic SEO, and custom AI tools to produce high-quality, SEO-optimized content. LongShot AI balances creativity with optimization to help users create content that engages audiences and improves search rankings.

Free 0 visits 30 saves

AI Chatbot

Claudeai.ai

Claudeai.ai is a platform powered by Anthropic's Claude 2 language model. It provides global access to Claude 2's features, including support for processing various text files, a 100K token context limit, and the ability to interact with up to 5 files at once. While not affiliated with Anthropic, Claudeai.ai uses the Claude 2 API to offer a user experience similar to the official website, accessible without regional restrictions.

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AI Writing Assistants

Sudowrite

Sudowrite is an AI writing assistant tailored for fiction authors, novelists, and screenwriters. It helps users overcome writer's block, brainstorm concepts, generate prose, expand scenes, refine sentences, and receive feedback on drafts. By utilizing various large language models, it supports the entire writing process—from initial outlining to final editing—to make writing more efficient, enjoyable, and collaborative.

Free 1 visits 17 saves

AI Agent

Engine

Engine is a suite of LLM-powered no-code tools that enables the creation of hosted API endpoints, HTML pages, and images using natural language. Additionally, it functions as an AI software engineer for teams, integrating with platforms like Jira, Trello, and Linear to convert tickets into pull requests, helping to automate development tasks and clear backlogs.

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Community discussion

What people think about Claude 4.7 Opus

Claude 4.7 Opus discussions are most active in r/QualityAssurance. The strongest match in this snapshot has 49 upvotes and 28 comments.

r/QualityAssurance 49 upvotes 28 comments May 11, 2026

With AI evolution (Claude 4.7 opus) E2E Automation career opportunities exists ?

I’m currently working as an SDET in a product-based company, mainly focused on end-to-end automation testing. Recently, I came across discussions saying many companies no longer prefer QA engineers who only have E2E automation experience, and it honestly made me anxious about my long-term career prospects.

A lot of my work involves:

* E2E automation frameworks
* API testing
* CI/CD deployments in test env
* Test infrastructure and automation pipelines

For experienced engineers/managers here:

* How do you see the future of SDET/QA roles evolving?
* Is deep E2E automation experience still valuable long term?
* What skills should someone in QA automation start building now to stay relevant in the next 5–10 years?
* Would you recommend transitioning toward backend development, infrastructure/platform engineering, or something else?

Thanks in advance (used gpt to format/modify it)

Open Reddit thread

View more discussions →

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