Claude

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Claude is a family of powerful, multi-modal AI models developed by Anthropic. It functions as a versatile thinking partner and productivity co-pilot designed to assist with complex knowledge work. Core capabilities include in-depth conversation, long-form reasoning, code generation and analysis, document and data interpretation (via uploaded files), web search, and task automation via integrations like Google Workspace. Its signature feature is 'Cowork,' an agentic mode where Claude can autonomously execute multi-step workflows with local files and cloud apps, handling tasks like organizing folders, building spreadsheets, or preparing reports. Claude is distinguished by its range of models (Fable, Opus, Sonnet, Haiku) optimized for different use-case trade-offs between cost, speed, and reasoning depth. It produces 'Artifacts' – interactive, visual outputs like code visualizations, reports, and study aids. Target users are professionals, developers, researchers, and teams needing to off

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Added on

Jul 8, 2026

Monthly Visits

946.8M

ArtifactsCoworkMulti-modelWeb searchCode executionFile analysisIntegrationsMemory

Product information

Everything worth knowing about Claude

The complete picture — from everyday features to the technical detail builders and IT folks dig for.

Core features

What it actually does

Artifacts

Create interactive, visual outputs like code, data visualizations, and reports within the chat interface, allowing for direct manipulation and exploration.

Cowork

Hand off complex, multi-step tasks to Claude within the desktop app, which can autonomously work with local files and connected cloud apps to execute tasks like organizing folders or building spreadsheets.

Memory & Projects

Claude retains context across conversations (Memory) and users can organize chats and documents into unlimited Projects for structured, long-term work.

Web Search & Integrations

Search the web for live information and connect to external tools via Google Drive, Microsoft 365, Slack, and custom MCP connectors.

Technical capabilities

Code Execution Sandbox

A secure environment where Claude can write and execute Python code for advanced data analysis, visualization, and iterative development within the chat.

Model Family Selection

Access to multiple LLM models (Fable 5, Opus 4.8, Sonnet 5, Haiku 4.5) with distinct architectures and performance profiles optimized for different tasks, from long-running agents to low-latency queries.

Must watch videos

The different levels of how Claude thinks

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Tutorial5:27

The different levels of how Claude thinks

Out of everything happening in your brain right now, only a tiny fraction is consciously accessible — thoughts you can describe, hold in mind, and reason with. We found a strikingly similar divide inside our AI model, Claude. Our experiments were inspired by a leading theory in neuroscience: the global workspace theory. It holds that a thought becomes consciously accessible when it enters a shared "workspace" that's broadcast across the brain. We found a set of representations in Claude’s neural activity that play a similar role. Read more about the research here: https://www.anthropic.com/research/global-workspace 0:00 The mind as an ocean 0:47 Meet the J-space 1:52 Silent math 2:22 Don't think about the bridge 3:12 Claude's automatic processing 3:42 Catching hidden thoughts 4:34 The question of consciousness

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Tutorial1:53

Introducing Claude Fable 5

Claude Fable 5 is our most capable model yet, now generally available. It’s a Mythos-class model with safeguards that let us share it broadly without compromising on safety. It can stay with complex tasks and hard problems for days, handling ambitious work across coding, research, analysis, finance, law, and beyond. Learn more: https://www.anthropic.com/news/claude-fable-5-mythos-5

Translating Claude’s thoughts into language

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Tutorial3:16

Translating Claude’s thoughts into language

AI models like Claude talk in words but think in numbers. These numbers, called activations, encode Claude’s thoughts, but not in a language we can read. We are introducing Natural Language Autoencoders, or NLAs, which translate AI models’ activations into readable text. NLAs have already helped us improve how we test our models for safety and better understand why they do what they do. Read more about this research on our blog: https://www.anthropic.com/research/natural-language-autoencoders

Who uses it

Real use cases, no hype

Complex Code Development

Generate, review, and debug multi-file projects with deep understanding of architecture.

Multi-step Task Automation

Delegate complex workflows via Cowork using local files and cloud integrations.

Deep Research & Analysis

Analyze documents and data with citations, creating interactive visual reports.

Creative Writing & Refinement

Brainstorm, develop unique voices, and produce polished content across formats.

Enterprise Security & Compliance

Leverage HIPAA-ready, audit-logged, and SSO-enabled features for regulated work.

Educational Tutoring

Explain complex topics simply and prepare for exams with interactive artifacts.

Data Analysis & Visualization

Analyze complex datasets, run Python code, and create visual artifacts.

What's great

Industry-leading reasoning for complex tasks
Best-in-class multi-file code generation and review
Powerful integration with desktop and cloud apps

Technical strengths

Advanced multi-step task delegation via Cowork feature
Proprietary long-context architecture excels in long-form analysis
Comprehensive enterprise-grade security and compliance features

Where it falls short

High cost for advanced models like Opus and Fable
Usage-based quotas can be restrictive on Pro plan
Limited features available on the free tier

Technical limitations

Model context windows can be less efficient than specialized competitors
Proprietary features may create vendor lock-in
Complex pricing structure across tiers and API tokens

For technical folks

The deep-dive specs

Core Architecture

Transformer-based Large Language Models (LLMs)

Model Family

Fable 5, Opus 4.8, Sonnet 5, Haiku 4.5 (distinct architectures for speed vs. capability)

Context Window

Extended thinking for complex, multi-step tasks

Code Execution

Sandboxed Python environment with file I/O capabilities

Data Residency

US-only inference option available

FAQ

Includes technical Q&A

Opus and the newer Fable are the most powerful for deep reasoning and long projects. Sonnet is balanced for daily tasks and coding. Haiku is the fastest for quick queries and basic tasks.