TL;DR: Claude is Anthropic's family of large language models. The weights are closed - you reach Claude through Anthropic's API, through major cloud platforms, or inside Anthropic's own apps and coding tools. The family's reputation rests on long-context work, careful instruction following, and strong performance as the engine behind coding agents.
What it is and how you use it
Claude is made by Anthropic, an AI company founded in 2021 by former OpenAI researchers with an explicit focus on AI safety research. Rather than a single model, Claude is a family released in tiers: larger tiers maximize capability, smaller tiers trade some of it away for lower latency and cost. Each generation refreshes those tiers, so the durable way to think about Claude is as a capability ladder, not a list of version numbers.
The family is best known for a few things. It handles a large context window well, which suits reading long documents and whole codebases. It follows detailed instructions and system prompts closely, which matters when a model runs unattended inside a pipeline. And it is a common engine for AI coding agents and other agentic products, where reliable tool use over many steps counts for more than one-shot cleverness. Anthropic also trains the family with a technique it calls Constitutional AI, steering behavior with written principles.
Access is entirely hosted: Claude's weights are closed, so there is nothing to download and no local install. Developers call the first-party API directly or reach the same models through cloud platforms such as Amazon Bedrock and Google Cloud's Vertex AI, which matters for teams whose billing, compliance, and networking already live in one cloud. Non-developers meet the family through the Claude apps and through Claude Code in the terminal. If you need weights you can run yourself, look at an open family such as Llama instead.
In practice, teams reach for Claude when the work involves long documents, sustained multi-step agent runs, or code - and when they are comfortable with a hosted, per-token API rather than infrastructure they operate. It competes head-to-head with GPT and Gemini at the frontier tier, so the deciding factors are usually fit on your specific tasks, existing cloud commitments, and price, not any absolute ranking.
Where it sits in the AI stack
Claude occupies the model layer: your application composes a prompt, sends it over an API, and Anthropic or a cloud partner runs the inference. You never operate the model itself:
Key tools and implementations
-
Anthropic API
The first-party HTTP API - the most direct path, and the first place new capabilities land.
-
Cloud platforms
The same models offered through Amazon Bedrock and Google Cloud Vertex AI, billed and governed inside your existing cloud account.
-
Official SDKs
Client libraries for Python, TypeScript, and other languages that wrap the API with streaming and tool-use helpers.
-
Claude apps and Claude Code
Anthropic's own chat apps and terminal coding agent - the no-integration way to put the family to work.
Related entries
- GPT OpenAI's family of closed-weight language models, served through its API, Azure, and the ChatGPT products.
- Gemini Google's multimodal model family, accessed through the Gemini API, Vertex AI, and Google's own products.
- Choosing a model A framework for weighing capability, latency, cost, privacy, and openness when picking a model for a task.
- AI coding agent Software that plans and executes multi-step coding tasks - reading files, editing code, and running tests with minimal supervision.