# Claude (AI model family)

A family of large language models developed by Anthropic, first released in March 2023, built around a Constitutional AI training approach and known for long-context handling, safety-oriented positioning, and strong coding performance.

Claude is the family of [large language models](https://www.wikiprompt.org/wiki/large-language-model) developed by [anthropic](https://www.wikiprompt.org/wiki/anthropic), first released to the public in March 2023. The model is named after [claude-shannon](https://www.wikiprompt.org/wiki/claude-shannon), the mathematician and founder of information theory, reflecting Anthropic's positioning of its work within a longer intellectual tradition of formal reasoning about information and communication. In 2026 the family gained a new top tier, [Claude Fable 5 and Mythos 5](https://www.wikiprompt.org/wiki/claude-fable-5), generally available with dual-use safeguards as Fable and offered unmitigated only to vetted organizations as Mythos; version 5.1 followed on September 1, 2026.

## Development and training approach

Anthropic was founded in 2021 by a group of former [openai](https://www.wikiprompt.org/wiki/openai) researchers, including [dario-amodei](https://www.wikiprompt.org/wiki/dario-amodei) and Daniela Amodei, who left partly over disagreements about the pace and safety posture of frontier model development. Claude's training combines large-scale pretraining on text data with [reinforcement learning from human feedback](https://www.wikiprompt.org/wiki/rlhf) and, distinctively, [Constitutional AI](https://www.wikiprompt.org/wiki/constitutional-ai), a technique in which the model is trained to critique and revise its own outputs according to a written set of principles, reducing reliance on large volumes of human-labeled feedback for harm reduction. Anthropic has described this approach as part of a broader effort to make model behavior more interpretable and controllable, connected to the company's published [responsible scaling policies](https://www.wikiprompt.org/wiki/anthropic-principles).

## Model line and releases

Claude has been released across several generations, typically organized into tiers balancing capability and cost (commonly named Haiku, Sonnet, and Opus). Successive versions expanded the model's [context-window](https://www.wikiprompt.org/wiki/context-window) substantially, reaching context lengths in the hundreds of thousands of tokens, well beyond the limits of early [ChatGPT](https://www.wikiprompt.org/wiki/chatgpt)-era models, which supported extended document analysis, large codebases, and long conversation histories. Later Claude models added tool use and agentic capabilities, including the ability to control a computer interface directly, and reasoning-oriented modes that allocate additional inference-time computation to harder problems, part of a broader industry shift toward [reasoning models](https://www.wikiprompt.org/wiki/reasoning-model). Anthropic also released [claude-code](https://www.wikiprompt.org/wiki/claude-code), a terminal-based agentic coding tool built on the Claude models, reflecting the family's particular strength and market reputation in software development tasks.

## Distribution and business model

Claude is offered both directly through Anthropic's consumer and API products and through cloud partners, most notably Amazon Web Services (via Bedrock) and Google Cloud (via Vertex AI), both of which are also investors in Anthropic. This multi-cloud distribution strategy distinguished Anthropic's commercial approach from OpenAI's closer, exclusive-feeling partnership with Microsoft.

## Reception and positioning

Claude has generally been positioned by reviewers and enterprise customers as strong on coding, careful long-document reasoning, and cautious, calibrated responses, competing directly with OpenAI's GPT series and Google's [gemini](https://www.wikiprompt.org/wiki/gemini). Independent evaluations and community leaderboards have repeatedly ranked various Claude versions among the top-performing models on coding-specific measures. Anthropic has framed the Claude line within a broader "race to the top" thesis, arguing that building capable models safely at a frontier lab is preferable to ceding frontier development entirely to less safety-focused actors, a stance connected to the company's stated concerns about [AI safety](https://www.wikiprompt.org/wiki/ai-safety) and [alignment](https://www.wikiprompt.org/wiki/alignment). Critics have questioned how much daylight actually separates safety-branded labs from competitors on release pace and product design, an ongoing debate across the generative AI industry as of 2025.

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Source: https://www.wikiprompt.org/wiki/claude
License: CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/)
Last updated: 2026-09-03T19:17:14.097443+00:00