Claude AI: Complete Guide to Features, Models, Pricing and How It Works
GuidesSunday, 02 August 2026 at 23:00
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Claude is an artificial intelligence assistant developed by Anthropic. You can use it to ask questions, write and revise text, analyze files, search the web, create documents, work with connected services, build software and hand off multi-step tasks. The same name also refers to the family of AI models that powers these experiences.
That double meaning explains much of the confusion around Claude. Claude can mean the assistant at Claude.ai, an underlying model such as Claude Sonnet or Opus, the Claude Code coding agent, or a model reached through the Claude API. Those products are connected, but they are not interchangeable and they do not all have the same prices, limits or data rules.
This guide maps the whole system. If you only want to start chatting, see our practical guide to using Claude step by step. If you are comparing subscriptions, go directly to our Claude pricing guide.
Claude at a glance
| Question | Short answer |
| Who makes Claude? | Anthropic, a US artificial intelligence company founded in 2021 |
| What is Claude? | A family of AI models and the assistant, coding and workplace products built around them |
| Is Claude free? | Yes, a limited Free plan is available |
| What is the first paid plan? | Claude Pro, at $20 monthly or $200 with annual billing in the United States before tax |
| Can Claude search the web? | Yes, supported models can use current web search and cite sources |
| Can Claude read files? | Yes, it can work with common documents, spreadsheets, images and other supported formats |
| Can Claude create files? | Yes, it can create and edit documents, spreadsheets, presentations, PDFs and other outputs in supported experiences |
| Can Claude write code? | Yes; Claude Code is Anthropic’s dedicated agentic coding product |
| Is there an API? | Yes, developers can access Claude through Anthropic and supported cloud platforms |
| Is Claude the same as Anthropic? | No. Anthropic is the company; Claude is its model and product family |
What is Claude?
Claude is a generative AI system that processes instructions and other input, identifies patterns learned during training and generates a response. In normal use, that response may be text, code, analysis, a structured file or a sequence of tool actions.
The basic chat experience resembles other general AI assistants: enter a request, receive an answer and continue the conversation. The more important change is what now sits around that chat. Claude can use web search, uploaded files, project knowledge, connected services and tools. It can place substantial outputs in Artifacts, create downloadable files, work inside office applications and complete longer tasks through products such as Claude Cowork and Claude Code.
Anthropic describes Claude as an AI for “problem solvers.” The positioning is useful because it moves the product away from the idea of a question-and-answer bot. Claude is most valuable when it receives a goal, enough context to understand that goal and a clear definition of a useful result.
Who is Anthropic?
Anthropic is an AI research and product company led by co-founders Dario Amodei and Daniela Amodei. It was formed in 2021 by a group that included former OpenAI researchers and released Claude commercially in 2023.
The company is a Public Benefit Corporation rather than a nonprofit. It develops and sells commercial AI products while stating a public-benefit purpose around the responsible development of advanced AI. Its governance includes an elected board and a Long-Term Benefit Trust with a role in board selection.
Anthropic is not a subsidiary of Amazon, Google or Microsoft. Those companies are important investors, compute suppliers and distribution partners, but a strategic investment is not the same as owning or controlling the entire company. Our separate guide to Anthropic covers the founders, funding, cloud relationships, business model, governance and proposed stock-market listing.
How does Claude work?
Claude is built on large language models. These models break input into units called tokens, process relationships across those tokens and generate the next part of an answer. Current Claude models can accept text and images, work across multiple languages and use tools when the product or developer has made those tools available.
Calling this “autocomplete” is technically suggestive but practically incomplete. A modern frontier model does not merely finish a sentence. It can transform information, compare sources, plan a sequence of steps, write and run code, call external tools and revise work after receiving results. It can still make errors because generating a plausible answer is not the same thing as retrieving a guaranteed fact.
Training, the constitution and alignment
Anthropic is known for Constitutional AI. In its original research, a model used written principles to critique and revise responses, followed by a reinforcement-learning stage using AI-generated feedback. Anthropic has since continued developing Claude’s constitution and other alignment methods.
This does not mean Claude follows a short public rulebook mechanically or that every answer is objectively “safe.” The constitution is one part of a larger training and deployment system that includes model training, fine-tuning, policies, classifiers, testing and product controls. It can reduce some unwanted behavior while also producing false refusals or overly cautious answers.
The practical implication is that Claude has been deliberately trained for steerability: it should respond to instructions about purpose, tone, format and constraints. Clear context still matters. Our existing Claude prompting guide explains how to provide that context without relying on magic phrases.
Thinking and tool use
Hard tasks often benefit from additional reasoning before the final answer. Anthropic’s current leading models use adaptive thinking, which lets the system vary the amount of internal work according to the task and configured effort. Older Claude models may use a manually configured extended-thinking mode instead.
Thinking is not the same as access to current facts. A model can reason carefully from an incorrect premise or outdated knowledge. Web search, attached evidence, databases and other tools provide information the model would not otherwise have. The strongest workflows combine reasoning with sources and then verify the output.
Claude is a product family, not one chatbot
The easiest way to understand Claude in 2026 is as a set of connected surfaces.
Claude Chat
Claude Chat is the standard conversational experience on the web, desktop and mobile. It is used for writing, questions, analysis, brainstorming, files, web search and other general tasks. Free and paid plans differ in model access, usage and advanced features.
Projects
Projects group related conversations, source material and instructions. You can upload a knowledge base and add project-level directions that apply across work in that project. When a paid project becomes too large to fit into the active context at once, Claude can use retrieval-augmented generation to find relevant passages rather than loading everything on every turn.
Projects are useful for a book, client, research question, product or recurring editorial process. They are not a substitute for access control or records management. Put only appropriate material into a consumer project and use a managed organizational plan when company policy requires it.
Artifacts
Artifacts place substantial, reusable output in a separate workspace beside the conversation. They can include documents, code, visualizations and interactive tools. This makes iterative work easier than repeatedly searching through a long chat.
An Artifact can be edited, shared or published depending on the product and account. It is still AI-generated output and should be checked before public or operational use. Code in an Artifact can contain mistakes; a polished interface does not guarantee correct logic.
Web search and Research
Web search lets Claude retrieve current information and show links or citations. Research performs a more extensive investigation across the web and, when enabled, connected internal sources.
Use ordinary search for a current fact or small comparison. Use Research when the answer depends on multiple sources, competing claims or a documented trail. In both cases, open the sources behind important claims. Citation markers make verification possible; they do not perform the verification for you.
File analysis and file creation
Claude can analyze common documents and images. It can also create and edit formats such as Word documents, Excel spreadsheets, PowerPoint presentations and PDFs in supported experiences. That makes it useful for turning raw source material into an organized deliverable.
The quality of a generated file depends on the source data, instructions and complexity. Verify formulas, totals, citations, document changes and slide claims. Anthropic itself advises human review for final client, legal, financial and audit-critical work in its Microsoft 365 guidance.
Memory and chat search
Claude can search previous conversations and maintain memory across chats when those features are available and enabled. Search retrieves relevant earlier discussions. Memory is designed to preserve useful context such as preferences or continuing work.
For a task that should not use or create memory, Claude offers Incognito chats. These do not appear in normal history or feed memory and are not used for model training, although Anthropic says they are generally retained for 30 days for safety unless a longer organizational retention setting applies.
Connectors, desktop extensions and MCP
Connectors let Claude work with external systems instead of relying only on copied text. Depending on the plan and product, those may include Google Workspace, Slack, Microsoft 365 and other services.
The Model Context Protocol, or MCP, is an open standard initiated by Anthropic for connecting AI applications to tools and data. A connector can give Claude valuable context or permission to perform actions, which also expands the security boundary. Review the provider, requested permissions, data handling and available actions before enabling it.
Claude Cowork
Claude Cowork is the agentic product for non-coding knowledge work. A user describes an outcome and grants access to selected files and tools; Claude can then perform a multi-step task and return a document, spreadsheet, presentation or other result for review.
Cowork differs from ordinary chat because it is intended to act across a task rather than only explain what a person could do. It differs from Claude Code because Cowork focuses on broader knowledge work while Claude Code focuses on software engineering.
See Claude for Work for practical workflows, team deployment and governance.
Claude Code
Claude Code is Anthropic’s agentic coding environment. It can inspect a repository, edit multiple files, run commands and tests, work with Git and connect to development tools. It is available in the terminal, supported IDEs, the Claude desktop app and the browser.
That is materially different from pasting a code snippet into a chatbot. Claude Code can operate inside the development environment and carry a task from investigation through implementation and verification. The added agency is also why permissions, sandboxing, diffs, tests and human review matter.
Claude Design, Science and Security
Anthropic has also developed more specialized applications:
- Claude Design creates and iterates on prototypes, wireframes, decks, marketing material and documents. Our existing guide shows how to build a presentation with Claude Design.
- Claude Science is a scientific workbench that can use existing scripts, tools and compute while preserving a trail of how an analysis was produced.
- Claude Security is a defensive security product that scans code, validates potential vulnerabilities and proposes patches for review.
These products should not be treated as universal features in every Claude account. Availability can depend on the plan, platform, region, administrator and product stage.
What can Claude do well?
Claude’s usefulness varies by task, but several categories are especially natural.
Writing and editing
Claude can turn notes into a draft, reorganize an argument, preserve a requested voice, compare versions and perform a critical edit. It works best when it receives the audience, purpose, constraints, factual source material and expected format.
A useful editorial process is staged:
- Ask Claude to identify the intended reader and missing information.
- Agree on the structure.
- Draft one complete version.
- Check claims against sources.
- Run a separate edit for clarity, repetition and unsupported language.
- Let a human accept or reject changes.
This produces more control than asking for “the perfect article” in one sentence.
Long documents and source synthesis
Large context windows and project knowledge make Claude attractive for comparing policies, reports, transcripts or research. It can identify agreements, contradictions and missing evidence across several inputs.
Context capacity is not accuracy. A model can overlook a detail in a large source set or blend claims from different documents. Ask for page, section or source references and check decisive passages yourself.
Research
Claude can search current sources, produce a structured overview and explain uncertainty. It is useful for creating a map of a topic, finding primary documents and identifying questions that require further reporting.
It should not become an invisible source. If Claude found a regulatory filing, research paper or company announcement, cite the original document in published work. The model’s summary is an intermediate layer.
Data and documents
Claude can inspect tables, write analysis code, calculate derived values and produce charts or files. It can also help explain what a spreadsheet is doing.
For high-stakes analysis, reproduce calculations independently. AI is particularly capable of creating an answer that looks structurally correct while containing a quiet assumption, wrong reference or incomplete filter.
Coding
Claude models are widely used for programming, and Claude Code gives them repository-level tools. Good tasks include codebase orientation, tests, bug fixes, refactors, migrations, documentation and pull-request preparation.
Use version control and start with a scoped task. A smaller change with an explicit acceptance test is easier to review than a vague instruction to “improve the codebase.”
Repetitive knowledge work
Cowork, Skills, Projects and connectors can turn a repeated process into a reusable workflow: prepare meeting briefs, transform research into a deck, classify a document collection or generate a weekly report.
Automation does not remove accountability. Define the inputs, permissions, quality checks, escalation points and owner before scheduling an unattended workflow.
What are the current Claude models?
Anthropic’s current model family includes Fable, Opus, Sonnet and Haiku. Mythos is a restricted model for approved defensive cybersecurity partners rather than a normal public choice.
| Model | Positioning | Best fit |
| Claude Fable 5 | Highest-capability widely released model for long-running agents | The hardest extended tasks where quality matters more than unit cost |
| Claude Opus 5 | Advanced professional and agentic model | Complex coding, analysis and enterprise work |
| Claude Sonnet 5 | Strong balance of intelligence, speed and cost | Most production applications and everyday advanced work |
| Claude Haiku 4.5 | Fastest and least expensive current model | Classification, extraction, routing and high-volume simpler tasks |
| Claude Mythos 5 | Invitation-only cyber model | Approved defensive cybersecurity work through Project Glasswing |
The names describe model tiers, not subscriptions. Paying for Claude Pro does not mean every request uses Opus, and using the Claude API does not require a Claude Pro subscription. The product chooses or exposes models according to plan and interface.
Context limits also differ between the API and consumer plans. Anthropic documents one-million-token context windows for current Fable 5, Opus 5 and Sonnet 5 API models, but its individual subscription comparison shows a 200,000-token context window. Do not use an API specification to promise the same capacity in a chat plan.
Our complete Claude model comparison explains model IDs, context, speed, cost and selection without turning this cornerstone into a second model page.
How much does Claude cost?
Claude has separate subscription and API pricing.
Individual plans
- Free costs $0 and provides limited use.
- Pro costs $20 per month, or $200 paid annually in the United States before tax.
- Max starts at $100 per month for a higher allowance; a $200 tier provides a larger allowance.
Team and Enterprise
Team supports managed organizational use with standard and premium seats. Enterprise adds more advanced administration, permissions, retention and compliance capabilities. Anthropic’s current self-serve Enterprise structure combines a seat fee with usage billed according to model and task.
API
The API is metered mainly by input and output tokens. Current base rates range from $1 per million input tokens and $5 per million output tokens for Haiku 4.5 to $10 and $50 respectively for Fable 5. Features such as prompt caching, batch processing, fast inference, web search and code execution have their own rates or modifiers.
Prices and inclusions change. See the full Claude pricing comparison for current plan tables, API rates and a practical method for choosing.
Is Claude free?
Yes. Claude’s Free plan is enough to test normal conversation, writing, web search, files and selected advanced features within limits. A free account is the right starting point because it reveals whether Claude fits the user’s real tasks.
Upgrade when the free allowance repeatedly interrupts valuable work or when a needed feature requires a paid plan. Do not upgrade solely because a plan promises “more” use; estimate how often the tool saves time or improves output.
The Claude API is not included as unlimited use with a consumer subscription. API usage is a separate metered service. Claude Code can be accessed through eligible subscriptions or through consumption-based developer access, but the billing route affects limits and cost.
How to start using Claude
The shortest path is:
- Go to https://claude.ai.
- Create an account or sign in.
- Start with a low-risk, real task.
- Explain the audience, purpose and desired output.
- Attach source material if the answer should be grounded in specific information.
- Ask Claude to identify uncertainty and missing context.
- Review the result rather than publishing or executing it automatically.
A stronger first prompt is:
I need to turn the attached report into a two-page decision memo for a non-technical leadership team. First identify the three decisions the report supports and any missing evidence. Then draft the memo with an executive summary, options, risks and a recommendation. Cite the page or section behind every numerical claim.
That prompt supplies a goal, reader, process, format and evidence rule. It gives Claude much more to work with than “summarize this.”
Our complete beginner’s guide to Claude covers files, Projects, web search, Research, Artifacts, memory, Incognito mode, connectors and common problems.
Claude versus ChatGPT
Claude and ChatGPT are now broad AI work environments rather than simple chatbots. Both can write, reason, research, analyze files, remember context, connect to external systems and support agentic coding.
Claude is a particularly strong choice for focused writing, long-document work, Artifacts and teams that want Claude Code or Cowork in the same ecosystem. ChatGPT has a broader consumer and creator surface around images, voice, custom GPTs, plugins, Codex and ChatGPT Work.
The better product is the one that matches the workflow, data boundary, integrations and level of review. A temporary benchmark lead should not decide a long-term organizational purchase.
See our dedicated Claude versus ChatGPT comparison for a task-by-task decision. The broader best ChatGPT alternatives guide remains the right page when the choice also includes Gemini, Copilot, Perplexity, Grok, DeepSeek or Mistral.
Is Claude safe?
Claude is designed with security and safety controls, but “safe” is not a yes-or-no property.
There are at least five separate questions:
- Will Anthropic use the content for model training?
- How long will data be retained?
- Which people, connectors and external services can access it?
- Can the model produce an incorrect or harmful output?
- Can an agent take an unintended action?
For Free, Pro and Max accounts, Anthropic says chats and coding sessions may be used to improve Claude when the user chooses to allow it. For commercial products such as Claude for Work and the Anthropic API, inputs and outputs are not used for model training by default. Retention rules, product exceptions and safety investigations still apply.
Claude can hallucinate. Connected tools can expose more data. Documents and web pages can contain prompt-injection instructions. An agent with permission to edit files or operate software can do more damage than a read-only chatbot.
Use the smallest necessary permissions, separate consumer and company use, verify important claims, review actions and never treat an AI answer as automatic professional approval. Our guide Is Claude safe? explains consumer, business and API data rules in detail.
Claude for business
Claude can be purchased for individual work, teams, enterprises and API deployments. A successful organizational rollout is less about giving every employee a chatbot and more about selecting repeatable, measurable workflows.
Good first use cases have:
- a clear input and output;
- enough volume to justify standardization;
- a human reviewer;
- non-catastrophic failure modes;
- a measurable baseline;
- and data that the chosen plan is allowed to process.
Examples include drafting meeting briefs, comparing approved contracts, preparing first-pass research, converting source documents into presentations, answering questions over an internal knowledge base and accelerating software maintenance.
Organizations should decide which data classes are allowed, who owns the workflow, which connectors are approved, how output is checked and when the process must stop for human review. See Claude for Work for the implementation framework.
Claude for developers
Developers can use Claude at three levels:
- Ask programming questions or analyze a file in Claude Chat.
- Use Claude Code inside a repository.
- Build a product or agent through the Claude API.
The API gives the application direct control over models, messages, tools, structured outputs and cost. Claude Code supplies an opinionated agentic development environment. They can be used together, but they solve different problems.
Claude models are also distributed through supported cloud platforms. The provider choice affects identity, billing, regional architecture and available features. Compare the exact service rather than assuming every “Claude on cloud” deployment behaves like Anthropic’s first-party API.
Claude’s main limitations
It can confidently be wrong
Fluent language is not evidence. Claude can invent a fact, misread a table, cite the wrong passage or make an invalid calculation. Source-grounded prompts and tools reduce some risk but do not eliminate it.
Limits are workload-dependent
A published subscription price does not buy a fixed number of identical messages. Long inputs, complex models, file analysis and agentic work can consume allowances faster. Shared usage across product surfaces can surprise heavy users.
Product availability changes
Models and features may differ by plan, country, administrator, platform and rollout stage. A beta feature may lack the logging, retention inheritance or support expected elsewhere in an enterprise environment.
Refusals and safeguards can interrupt legitimate tasks
Claude may refuse or redirect a benign request, especially in sensitive or dual-use domains. Fable’s stronger cybersecurity safeguards, for example, can create false positives during legitimate coding and security work.
Agency increases operational risk
When Claude can edit files, run commands, browse, use connectors or act in office software, an error becomes more consequential. Use permissions, sandboxing, version control, backups and approval steps.
Claude is proprietary
Users cannot independently inspect the complete training data or model weights. Organizations that require self-hosted open-weight models should compare a different deployment category rather than assuming a Claude subscription can meet that requirement.
The best way to evaluate Claude
Do not evaluate Claude with trivia or one impressive prompt. Use a small test set based on recurring work.
- Select five to ten representative tasks.
- Define what a good result requires.
- Remove or anonymize sensitive information unless the chosen plan permits it.
- Run the same source material and instructions through the products being compared.
- Score factual accuracy, completeness, time saved, edits required and cost.
- Record failure modes, not only successes.
- Repeat after a meaningful model or product change.
This reveals whether Claude is good for your work. A public benchmark measures a controlled capability; it does not measure integration friction, reviewer time, data governance or whether the output is actually usable.
Frequently asked questions
Is Claude an AI or a chatbot?
Both descriptions are used, but Claude is broader than a chatbot. It is a family of AI models and the product ecosystem built around those models, including chat, coding, workplace and developer tools.
Is Claude owned by Amazon?
No. Amazon is a major investor, primary cloud provider and training partner, but Anthropic remains a separate company. Google, Microsoft, NVIDIA and venture investors also have financial or strategic relationships with Anthropic.
Does Claude have internet access?
Claude can search the web in supported models and product experiences. The underlying model does not independently know every current fact, so enable search or provide sources when recency matters.
Can Claude generate images?
Claude’s core public model documentation describes text and image input with text output. Claude Design and Artifacts can produce visual and interactive work, but Claude is not positioned primarily as a native photorealistic image generator in the way some competing products are.
Can Claude create PowerPoint and Excel files?
Yes, supported Claude experiences can create and edit PowerPoint presentations, Excel spreadsheets, Word documents and PDFs. Verify formulas, facts, formatting and final files before use.
Is Claude good for coding?
Yes. Claude models are strong at programming, and Claude Code can inspect repositories, edit files, run commands and prepare Git changes. Human review, tests and scoped permissions remain necessary.
Does Claude train on my chats?
For consumer Free, Pro and Max accounts, Anthropic says it may use chats and coding sessions if the user enables model improvement. Commercial products such as Claude for Work and the Anthropic API are not used for training by default. Incognito chats are not used for training. Read the current policy for the exact product before entering sensitive data.
What is the best Claude model?
“Best” depends on the task. Fable 5 has the highest broadly available capability; Opus 5 targets demanding professional and agentic work; Sonnet 5 balances capability, speed and price; Haiku 4.5 prioritizes speed and cost. Most applications should not default to the most expensive model without testing.
Is Claude better than ChatGPT?
Claude can be better for focused writing, large source sets, Artifacts and the Claude Code workflow. ChatGPT can be better when its broader image, voice, custom-assistant, plugin and Codex ecosystem matters. Compare complete products on real tasks rather than choosing from a single model benchmark.
Bottom line
Claude has grown from an AI chat interface into a complete work and development ecosystem. Its strongest proposition is the connection between a capable model family and practical surfaces: Chat for collaboration, Projects for context, Artifacts for outputs, Research for sourced investigation, Cowork for delegated knowledge work, Claude Code for software engineering and the API for custom applications.
That breadth also makes precise comparisons more important. A Claude subscription, Claude Code session, API request and enterprise deployment can involve different limits, prices and data rules. Start with the task, select the correct product layer and keep a human responsible for the result.
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byDavid Porter
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