Claude

Anthropic

MODEL DIRECTORY

MODEL DIRECTORY

Claude

Claude

Anthropic’s Claude family spans frontier reasoning, coding, vision, and faster production models. The practical choice is a specific pinned model ID on the Claude API or a supported cloud platform.

CURRENT MODEL SNAPSHOT

Provider: Anthropic
Current anchor: Claude Fable 5, Opus 4.8, Sonnet 5, and Haiku 4.5
Lifecycle: Current
Weights: Closed
Reviewed: 20 July 2026

Claude models in context

Claude is Anthropic’s family of hosted language and multimodal models. For enterprise teams, the family name is only the start of the decision: the selected model tier, pinned model ID, provider surface, tool implementation, and lifecycle all affect behaviour. Anthropic documents direct access and availability through major cloud platforms, which gives architects multiple procurement and deployment routes.

Anthropic’s model overview currently lists four primary anchors:

  • Claude Fable 5 is the newest frontier option in the published family overview.

  • Claude Opus 4.8 targets the most demanding reasoning and agentic work.

  • Claude Sonnet 5 is the broad production tier for capability, speed, and cost balance.

  • Claude Haiku 4.5 provides a faster, lighter option for high-volume tasks.

Evaluate Sonnet as the general baseline, Opus or Fable for tasks that demonstrably need more capability, and Haiku for constrained high-volume steps. Pin the model ID used in testing and monitor its availability on the chosen platform.

Where Claude is distinctive

Claude is particularly relevant to teams designing long-running agents, coding workflows, document analysis, and careful instruction-following. Anthropic’s direct and cloud-platform availability can also fit organizations that want procurement through an existing hyperscaler, although model features and release timing may vary by surface.

Strengths to test

  • Complex analysis and synthesis where the model must preserve instructions across a long task.

  • Coding and software-engineering workflows that combine repository context, planning, edits, and review.

  • Document and vision tasks where a workflow needs structured reasoning over mixed business material.

  • Tiered production routing between stronger frontier models and the faster Haiku option.

Trade-offs and failure modes

  • A Claude family name does not identify the fixed model snapshot used in an evaluation.

  • Feature availability and release timing can differ between Anthropic, AWS, Google Cloud, and Microsoft surfaces.

  • Long-context capacity does not guarantee retrieval of every relevant fact or resistance to conflicting instructions.

  • Agentic coding needs repository permissions, test gates, and change review beyond the model’s generated patch.

Use complete tasks rather than isolated prompts: provide the actual tools, documents, codebase boundaries, and approval steps. Score task completion, groundedness, edit quality, tool recovery, latency, and cost. Repeat tests on the exact model ID and provider surface intended for production.

Deployment and enterprise decision notes

Anthropic documents access through the Claude API and supported platforms including AWS, Amazon Bedrock, Google Cloud, and Microsoft Foundry. Choose the route based on feature parity, procurement, identity, networking, region, and data controls—not brand familiarity alone.

Best fit

A strong candidate for enterprise agents, coding, document analysis, and workflows that benefit from careful instruction-following and a choice between frontier and faster tiers. It is also relevant when the organization prefers access through an existing cloud platform.

Not the best fit

Do not select Claude solely from a generic benchmark or chatbot impression. It may be unsuitable when required regions, tools, throughput, model access, or contractual controls are unavailable on the chosen surface, or when a self-hosted model is mandatory.

Data and governance

Store the pinned model ID, provider surface, region, retention and training settings, tool permissions, prompt version, and evaluation results. Revalidate after model changes, and treat computer-use, code execution, browsing, and external connectors as separate security boundaries.

Official sources

Beam AI support status

Under evaluation. This page is a model-selection reference, not confirmation of a Beam integration, benchmark result, data-residency promise, or production recommendation. Validate the exact provider surface and model version in the intended workflow before release.

Use case 1

Long-running enterprise agent

Coordinate a bounded sequence of research, reasoning, and system actions while maintaining the task goal and escalation rules. Evaluate recovery after failed tools, prompt injection, long-horizon drift, and the operational value of stronger Claude tiers.

Use case 2

Software engineering workflow

Use repository context to plan, implement, test, and review a change within explicit file and permission boundaries. Require automated checks and human review; compare Sonnet, Opus, and Fable on successful merged outcomes rather than code aesthetics.

Use case 3

Complex policy and contract analysis

Compare long documents, identify obligations and conflicts, and produce a structured reviewer brief with traceable source passages. Test missing-context behaviour, contradictory clauses, citation accuracy, and abstention on legal or regulatory conclusions.

Use case 4

High-volume service triage

Use Haiku or another validated tier to classify requests, summarize history, and propose the next step while routing sensitive or ambiguous cases to a stronger model or person. Track false routing and escalation quality.

Related LLMs

Curated alternatives to compare before selecting a model family.

ChatGPT

ChatGPT is OpenAI’s conversational product; enterprise automations use the underlying GPT models and APIs. This guide separates the product from the model family and explains how to evaluate the current GPT-5.6 lineup.

ChatGPT

Combine sections from a range of categories to easily assemble pages that meet the needs of your growing business.

DeepSeek

DeepSeek’s current V4 family provides Pro and Flash API models with thinking and non-thinking modes, a documented one-million-token context window, and compatible API interfaces.

DeepSeek

Combine sections from a range of categories to easily assemble pages that meet the needs of your growing business.

Perplexity

Perplexity’s Sonar API family combines language models with web search and citations. The core enterprise decision is whether provider-managed retrieval and source handling fit the workflow.

Perplexity

Combine sections from a range of categories to easily assemble pages that meet the needs of your growing business.

Gemini

Google’s Gemini family covers production and preview models for multimodal, reasoning, audio, media, and tool-oriented workloads. Model stage and endpoint stability are central to an enterprise selection.

Gemini

Combine sections from a range of categories to easily assemble pages that meet the needs of your growing business.

Llama

Meta’s Llama 4 family provides open-weight, natively multimodal models. Scout emphasizes very long context and efficient deployment; Maverick targets stronger general multimodal capability.

Llama

Combine sections from a range of categories to easily assemble pages that meet the needs of your growing business.

PaLM

PaLM is Google’s superseded language-model family. Existing implementations should identify the old endpoint, select a current Gemini replacement, and run a full migration regression.

PaLM

Combine sections from a range of categories to easily assemble pages that meet the needs of your growing business.

Start Today

Build AI agents with the right model

See how Beam can orchestrate governed AI workflows across the model family that fits your requirements.

Start Today

Build AI agents with the right model

See how Beam can orchestrate governed AI workflows across the model family that fits your requirements.

Start Today

Build AI agents with the right model

See how Beam can orchestrate governed AI workflows across the model family that fits your requirements.

FAQs

Frequently Asked Questions

Model selection, deployment, governance, and Beam support questions answered.

What is the current Claude model lineup?

Anthropic’s current overview lists Claude Fable 5, Opus 4.8, Sonnet 5, and Haiku 4.5, with different capability, latency, and availability profiles. Model names and lifecycle labels can change quickly, so record the exact model ID or release used in testing and confirm it against the linked provider documentation before production.

How can an enterprise access or deploy Claude?

Claude is available through Anthropic’s platform and documented cloud routes including AWS, Amazon Bedrock, Google Cloud, and Microsoft Foundry. Availability, regional controls, service terms, and feature parity can vary by route. Evaluate the exact provider surface that will carry production traffic, rather than assuming every hosted or self-managed option behaves identically.

What workloads are a strong fit for Claude?

Claude is a strong candidate for agentic work, coding, complex document analysis, vision, and workflows that depend on sustained instruction-following. Treat that as a shortlist hypothesis, not a universal ranking. Use representative prompts, tools, documents, languages, and failure cases to compare quality, latency, reliability, and total operating cost.

What should security and governance teams review for Claude?

Record a pinned model ID and review provider-surface differences, regions, retention, tool permissions, prompt-injection exposure, and model lifecycle. Document the data path, retention settings, model version, region, subprocessors or hosting stack, human-review points, and incident fallback before the workflow is approved.

Does this page confirm Beam support for Claude?

No. Beam support is marked Under evaluation because no approved integration or production-support evidence is attached to this CMS record. The page can guide discovery and evaluation, but the implementation owner must verify access, controls, tool behaviour, and operational fit before making a customer commitment.