Tag: Claude API

  • How Many Words Is a Million Claude Tokens? (2026)

    How Many Words Is a Million Claude Tokens? (2026)

    Last verified: June 13, 2026

    A million Claude tokens equals roughly 750,000 words on Claude Sonnet 4.6 — but only about 555,000 words on Claude Opus 4.7, Claude Opus 4.8, and Claude Fable 5. The gap comes from a new tokenizer that Anthropic introduced with Opus 4.7: it emits up to 35% more tokens from the same text. The only reliable way to measure your actual token count is the /v1/messages/count_tokens endpoint.

    Token-to-word conversion by model (1 million tokens)

    Small token cubes assembling into short phrase cards on a desk
    Token-to-word conversion framing.

    Anthropic publishes word equivalents directly in the context-window tooltips on the official models overview page. The figures below come from those tooltips.

    Lineup currency (Sept 2026): Current API list (Sept 2026, verified): Sonnet 5 $2/$10, Opus 5.5 $4/$20, Haiku 4.5 $1/$5, Fable 5.1 $10/$50. Legacy (still listed on Anthropic’s card): Opus 4.8 $5/$25, Sonnet 4.6 $3/$15. Rows below that still name Opus 4.8 / Sonnet 4.6 / Fable 5 are legacy-or-prior availability figures — confirm live Anthropic limits before quoting TPM/RPM/context.

    Model Tokenizer Context window ~Words per 1M tokens ~Pages per 1M tokens*
    Claude Fable 5 (claude-fable-5) New (Opus 4.7) 1M tokens ~555,000 ~2,200
    Claude Opus 4.8 (claude-opus-4-8) New (Opus 4.7) 1M tokens ~555,000 ~2,200
    Claude Opus 4.7 (claude-opus-4-7) New (Opus 4.7) 1M tokens ~555,000 ~2,200
    Claude Sonnet 4.6 (claude-sonnet-4-6) Older 1M tokens ~750,000 ~3,000
    Claude Haiku 4.5 (claude-haiku-4-5) Older 200k tokens ~150,000 (200K context) ~600 (200K context)
    Claude Opus 4.6 (claude-opus-4-6) Older 1M tokens ~750,000 ~3,000

    * Pages estimated at ~250 words per double-spaced page. These are approximations for typical English prose; actual counts vary by content type.

    What the new tokenizer changed — and why it matters

    Diagram comparing a long context window bar with a shorter output limit bar
    What the new tokenizer changed — and why it matters.

    Anthropic introduced a new tokenizer with Claude Opus 4.7. The official migration guide states that the new tokenizer “may use roughly 1x to 1.35x as many tokens when processing text compared to previous models (up to ~35% more, varying by content).” The most commonly cited figure across Anthropic’s documentation is roughly 30% more tokens for the same text.

    The practical effect: a document that costs 1,000,000 tokens on Opus 4.6 or Sonnet 4.6 costs approximately 1,300,000 tokens on Opus 4.7, Opus 4.8, or Fable 5. Budgets built for the old tokenizer need to be re-baselined against the new one.

    Lineup currency (Sept 2026): Current API list (Sept 2026, verified): Sonnet 5 $2/$10, Opus 5.5 $4/$20, Haiku 4.5 $1/$5, Fable 5.1 $10/$50. Legacy (still listed on Anthropic’s card): Opus 4.8 $5/$25, Sonnet 4.6 $3/$15. Rows below that still name Opus 4.8 / Sonnet 4.6 / Fable 5 are legacy-or-prior availability figures — confirm live Anthropic limits before quoting TPM/RPM/context.

    Tokenizer Models Approximate token increase vs. older tokenizer
    New (introduced Opus 4.7) Opus 4.7, Opus 4.8, Fable 5, Mythos 5 ~30% typical; up to ~35% depending on content
    Older Opus 4.6, Sonnet 4.6, Haiku 4.5, Opus 4.5, Sonnet 4.5 Baseline

    The token counting page also notes the comparison directly: “Claude Fable 5 and Claude Mythos 5 use the tokenizer introduced with Claude Opus 4.7, which produces roughly 30% more tokens than models before Claude Opus 4.7 for the same text.”

    Use count_tokens — not tiktoken or ratio math

    Desk with laptop, checklist notebook, and billing card ready before creating an Anthropic API key
    Use count_tokens — not tiktoken or ratio math.

    Anthropic’s migration guide explicitly flags the risk: “Any code path that estimates tokens client-side or assumes a fixed token-to-character ratio should be re-tested against Claude Opus 4.7.” OpenAI’s tiktoken library is trained on a different vocabulary and produces different counts. It will not give accurate results for any Claude model.

    The correct approach is the /v1/messages/count_tokens endpoint, passing the specific model you intend to use:

    curl https://api.anthropic.com/v1/messages/count_tokens \
      --header "x-api-key: $ANTHROPIC_API_KEY" \
      --header "content-type: application/json" \
      --header "anthropic-version: 2023-06-01" \
      --data '{
        "model": "claude-opus-4-8",
        "messages": [{"role": "user", "content": "Your text here"}]
      }'

    The endpoint returns a model-specific count. If you are migrating a workload from Sonnet 4.6 to Opus 4.8, count the same prompt with both model IDs and compare the two input_tokens values. The token counting endpoint is free to use (rate limits apply by usage tier). Anthropic notes that the returned count is an estimate; the actual count at inference time may differ by a small amount.

    Quick reference: common document sizes

    Lineup currency (Sept 2026): Current API list (Sept 2026, verified): Sonnet 5 $2/$10, Opus 5.5 $4/$20, Haiku 4.5 $1/$5, Fable 5.1 $10/$50. Legacy (still listed on Anthropic’s card): Opus 4.8 $5/$25, Sonnet 4.6 $3/$15. Rows below that still name Opus 4.8 / Sonnet 4.6 / Fable 5 are legacy-or-prior availability figures — confirm live Anthropic limits before quoting TPM/RPM/context.

    Document type Approx. words Tokens (older tokenizer) Tokens (new tokenizer)
    Novel (~400 pages) ~100,000 ~133,000 ~173,000
    Long research paper ~20,000 ~27,000 ~35,000
    Full context, Sonnet 4.6 (1M tokens) ~750,000 1,000,000 N/A (different model)
    Full context, Opus 4.8 (1M tokens) ~555,000 N/A (different model) 1,000,000

    These word estimates assume typical English prose. Code, structured data, and non-Latin scripts tokenize differently from natural language prose. Highly repetitive text and dense symbol-heavy content (like JSON or code) can fall well outside the ~0.75 words-per-token ratio.

    Does the new tokenizer change what fits in the context window?

    Yes, in one direction. The context window is still 1M tokens, but that window holds fewer words on the new tokenizer (~555k words) than on the old one (~750k words). A document that previously fit comfortably may now require trimming or chunking when moving to Opus 4.7, Opus 4.8, or Fable 5.

    Does Sonnet 4.6 use the new tokenizer?

    No. Claude Sonnet 4.6 uses the older tokenizer. Anthropic’s model overview page lists Sonnet 4.6’s 1M-token context window as equivalent to ~750k words, the same ratio as Opus 4.6 — confirming it has not adopted the Opus 4.7 tokenizer. Only Opus 4.7, Opus 4.8, Fable 5, and Mythos 5 use the new tokenizer.

    Can I use tiktoken or another open-source tokenizer for Claude?

    No. tiktoken is built for OpenAI models and uses a different vocabulary. It will not produce accurate token counts for any Claude model, and its error will be larger on the new Opus 4.7 tokenizer than on older Claude models. Use /v1/messages/count_tokens with the specific Claude model ID you plan to deploy.

    Does the new tokenizer affect pricing?

    Yes. Billing reflects token counts under the model’s tokenizer. If you migrate a workload from Opus 4.6 to Opus 4.8 and the new tokenizer produces 30% more tokens, your input token costs increase by roughly 30% before accounting for any per-token price difference between the models. Re-baseline cost estimates using the count_tokens endpoint rather than scaling from old measurements.

    How many pages is the full 1M-token context window?

    On models with the older tokenizer (Sonnet 4.6, Opus 4.6), 1 million tokens is approximately 3,000 double-spaced pages of typical English prose. On models with the new tokenizer (Opus 4.8, Fable 5), the same 1 million tokens holds approximately 2,200 pages. These are prose estimates — a 1M-token window filled with source code or dense structured data will span a very different page count.

    Related on Tygart Media: Message Batches API · Claude pricing · Anthropic API quickstart.

  • Claude Cowork vs Code vs Agent SDK vs Managed Agents (2026)

    Claude Cowork vs Code vs Agent SDK vs Managed Agents (2026)

    Last verified: June 13, 2026

    Anthropic ships four distinct ways to put Claude to work as an agent, and they are easy to confuse. The short version: Claude Cowork and Claude Code are interactive products billed through your Claude subscription — Cowork for knowledge work in the desktop app, Code for software work in your terminal, IDE, desktop, or browser. The Claude Agent SDK and Managed Agents are programmatic surfaces for developers, billed through the API: the Agent SDK is a Python/TypeScript library that runs the agent loop inside your own process, while Managed Agents is a REST API where Anthropic runs the loop and hosts the sandbox. The tables below give the verified, side-by-side breakdown.

    The decision matrix

    Three cards: coding depth, latency first, agent reliability
    Cowork vs Code vs Agent SDK vs Managed Agents matrix.

    Each row is one surface. Read across for who it serves, whether you drive it turn-by-turn or hand it a goal, where the work executes, and how it is paid for.

    Surface Who it is for Interactive vs autonomous Where it runs How it is billed
    Claude Cowork Knowledge workers (non-developers) — research, documents, file and spreadsheet work Interactive, supervised — shows you the plan and waits for your approval before acting The Claude desktop app on your own computer (macOS or Windows); not available on web or mobile Claude subscription (Pro, Max, Team, Enterprise) — draws from your plan’s usage allocation
    Claude Code Developers doing interactive coding — build features, fix bugs, automate dev tasks Interactive — you drive it in a session, though it can run agentically across files and tools Your machine (terminal, VS Code, JetBrains, desktop app) or the browser at claude.ai/code Claude subscription or an Anthropic Console (API) account
    Claude Agent SDK Developers building custom agents programmatically (Python or TypeScript) Autonomous — Claude reads files, runs commands, and edits code on its own via the agent loop Your own process and infrastructure API key (pay-as-you-go credits); see the subscription note below for the June 15, 2026 change
    Managed Agents Developers running production or long-running agents without operating their own sandbox/session infrastructure Autonomous — you send events, Claude executes tools and streams back results Anthropic-managed cloud sandbox per session (or a self-hosted sandbox on your own infrastructure) Claude API key + the managed-agents-2026-04-01 beta header (no subscription path)

    Where billing actually differs

    The cleanest way to split these four is by the wallet they draw from. The two interactive products are funded by a subscription; the two programmatic surfaces are funded by the API. This is the single distinction that trips people up most often, so it is worth stating plainly in its own table.

    Surface Billing model Notes
    Claude Cowork Subscription Included on Pro, Max, Team, and Enterprise. Multi-step tasks consume more of your usage allocation than chatting.
    Claude Code Subscription or API Most surfaces require a Claude subscription or a Console account; the terminal CLI and VS Code also support third-party providers.
    Claude Agent SDK API (pay-as-you-go) Authenticated with an ANTHROPIC_API_KEY; also supports Bedrock, Claude Platform on AWS, Vertex AI, and Azure. Anthropic does not permit claude.ai login for third-party agents built on the SDK.
    Managed Agents API (credits) Requires a Claude API key and the beta header; enabled by default for API accounts.

    One dated nuance is worth pinning down because it changes how subscription users pay for programmatic work. Starting June 15, 2026, Claude Agent SDK and claude -p usage on subscription plans no longer counts toward your Claude plan’s interactive usage limits; instead, eligible subscribers receive a separate monthly Agent SDK credit (per-user, not pooled), while subscription usage limits stay reserved for interactive use of Claude Code, Cowork, and Claude. If you use the Agent SDK with an API key from the Claude Platform, nothing changes — pay-as-you-go billing continues and you do not receive an Agent SDK monthly credit.

    SDK vs Managed Agents: the programmatic split

    Side-by-side cards defining what Claude Code is and is not
    SDK vs Managed Agents — the programmatic split.

    Both programmatic surfaces let Claude run tools autonomously, but they differ in where the loop and the work live. Anthropic’s own comparison frames it this way: the Agent SDK “is a library that runs the agent loop inside your own process,” while Managed Agents “is a hosted REST API: Anthropic runs the agent and the sandbox, and your application sends events and streams back results.” Pick by who you want operating the infrastructure.

    Dimension Agent SDK Managed Agents
    Runs in Your process, your infrastructure Anthropic-managed infrastructure
    Interface Python or TypeScript library REST API
    Agent works on Files on your infrastructure A managed sandbox per session
    Session state JSONL on your filesystem Anthropic-hosted event log
    Best for Local prototyping; agents that work directly on your filesystem and services Production agents without operating sandbox/session infrastructure; long-running, asynchronous sessions

    A common path, per Anthropic’s docs, is to prototype with the Agent SDK locally, then move to Managed Agents for production.

    Quick chooser

    Three cards for fast volume, daily workhorse, and deep flagship Claude seats
    Quick chooser for the right surface.

    If you are not writing code and want Claude to finish a task on your computer, use Cowork. If you are a developer working interactively on a codebase, use Claude Code. If you are building your own agent and want it to run in your own process, use the Agent SDK. If you want Anthropic to run the agent and host the sandbox for long-running or production work, use Managed Agents.

    Is Claude Cowork the same as Claude Code?

    No. Both appear in the Claude desktop app, but Cowork is aimed at knowledge work (research, documents, spreadsheets, file management) for non-developers, while Claude Code is an agentic coding tool. Cowork runs only in the desktop app (macOS or Windows); Claude Code also runs in the terminal, VS Code, JetBrains, and the browser.

    Does a Claude subscription cover the Agent SDK or Managed Agents?

    Cowork and Claude Code are included with Claude subscriptions (Pro, Max, Team, Enterprise). The Agent SDK and Managed Agents are API surfaces authenticated with a Claude API key. As of June 15, 2026, subscription users do get a separate monthly Agent SDK credit for SDK and claude -p usage, but Managed Agents has no subscription path — it requires an API key and a beta header.

    Where does the work actually execute for each surface?

    Cowork runs on your own computer in the desktop app. Claude Code runs on your machine (or in the browser). The Agent SDK runs in your own process and infrastructure. Managed Agents executes in an Anthropic-managed cloud sandbox per session, or a self-hosted sandbox you control.

    Is the Agent SDK built on Claude Code?

    Yes. Per Anthropic, the Agent SDK “gives you the same tools, agent loop, and context management that power Claude Code, programmable in Python and TypeScript.” Anthropic also describes it as “Claude Code as a library.”

    Is Managed Agents generally available?

    No. As of June 13, 2026, Claude Managed Agents is in beta. Every Managed Agents endpoint requires the managed-agents-2026-04-01 beta header (the SDK sets it automatically), and access is enabled by default for API accounts.

    Related on Tygart Media: what Claude Cowork is · Claude Code getting started · Agent SDK migration.


    >Part of the complete guide: Claude Code

  • Claude Enterprise Compliance: SOC 2, HIPAA & Security

    Claude Enterprise Compliance: SOC 2, HIPAA & Security

    Last verified: June 13, 2026

    Anthropic publishes a defined compliance posture for Claude: it holds SOC 2 Type I and Type II, ISO 27001:2022, and ISO/IEC 42001:2023 credentials; it will sign a Business Associate Agreement (BAA) covering HIPAA-ready services such as the first-party API and Enterprise plans; by default it does not train models on data sent under its commercial terms; and it offers a zero-data-retention (ZDR) arrangement on the Messages and Token Counting APIs. The hard part for buyers is the per-surface boundary — what the BAA covers, which features are blocked under ZDR or HIPAA, how long data is kept, and where it can be processed. Every figure below is drawn from Anthropic’s own trust, privacy, and developer documentation, with sources at the bottom. Eligibility, feature lists, and durations change; treat your signed contract and the live Trust Center as the controlling sources.

    Certifications and attestations

    Five security domains: identity, data, code governance, audit, agents
    Certifications and attestations overview.

    Anthropic’s help center lists the following compliance credentials for its commercial products (Claude for Work and the Anthropic API). It directs customers to the Trust Portal at trust.anthropic.com to request copies of the underlying reports and certificates.

    CredentialStatus as described by AnthropicScope
    SOC 2 Type I & Type IIListed as heldCommercial products (Claude for Work, Anthropic API)
    ISO 27001:2022CertifiedInformation Security Management
    ISO/IEC 42001:2023Certified (issued by Schellman Compliance, LLC, accredited by the ANSI National Accreditation Board)AI Management Systems
    HIPAA“HIPAA-ready configuration (BAA available)”See BAA section

    Anthropic describes itself as “one of the first frontier AI labs” to achieve ISO/IEC 42001:2023 certification, in an announcement dated January 13, 2025. The help-center certifications list does not mention ISO 27017, ISO 27018, FedRAMP, or CSA STAR; those are left out here rather than asserted. GDPR and CCPA are handled through Anthropic’s privacy program and customer agreements rather than as line-item “certifications” (see GDPR section).

    HIPAA and the BAA: covered by product surface

    Five-step path: account, API keys, billing, usage, workspaces
    HIPAA and the BAA by product surface.

    Anthropic states it “provides a Business Associate Agreement (BAA) covering our HIPAA-ready services, such as use of our first-party API or Enterprise plans.” HIPAA readiness is enforced at the organization level: Anthropic provisions a dedicated HIPAA-enabled organization that automatically blocks non-eligible features. To process protected health information (PHI) on the API, an administrator must sign the BAA and contact sales to enable it; for Enterprise, an admin activates HIPAA compliance in the Claude Enterprise admin settings under “Data & Privacy” and signs the BAA there.

    SurfaceBAA / HIPAA-ready coverage
    First-party Claude API (Messages API)Covered as an Eligible Service (admin signs BAA, then contact sales)
    Claude EnterpriseCovered once an admin activates HIPAA compliance and signs the BAA
    Workbench and ConsoleNot covered
    Claude Free, Pro, Max, TeamNot covered
    CoworkNot covered
    Claude CodeNot covered under HIPAA readiness
    Amazon Bedrock / Vertex AINot covered (cloud provider is the data processor; see those platforms)
    Claude Platform on AWS / Microsoft FoundryHIPAA readiness not available
    Beta features (e.g., Claude in Office, Claude Design)Generally not covered unless explicitly listed as eligible

    Within the API, only a subset of features is HIPAA-eligible. Anthropic enforces this in code: a HIPAA-enabled organization that sends a non-eligible feature gets a 400 invalid_request_error naming the blocked feature. Anthropic states your signed BAA is the official source of truth for what is covered.

    API featureHIPAA-eligible
    Messages API (/v1/messages)Yes
    Token countingYes
    Web searchYes (dynamic filtering not eligible)
    Prompt caching, structured outputs, extended/adaptive thinking, citations, 1M context, PDF (inline), data residency, effort, fast mode, bash & text-editor tools, memory toolYes
    Web fetch, computer use, advisor tool, context management (compaction / editing), tool search, cache diagnosticsNo
    Code execution, programmatic tool callingNo
    Batch API, Files API, Agent Skills, MCP connector, Claude Managed Agents, MCP tunnelsNo

    PHI must appear only in message content, attached files, or related file names/metadata — never in JSON schema definitions (property names, enum/const values, or pattern regexes), because compiled schemas are cached separately and do not receive the same PHI protections. Anthropic notes workspace names, user contact details, billing data, and support tickets are not expected to contain PHI under the BAA.

    Data retention (commercial default)

    Under Anthropic’s commercial data retention policy, conversation content is not retained by default for the API, and API inputs and outputs are automatically deleted on the backend within 30 days of receipt or generation. For interface products such as Claude for Work, data persists until you delete it, after which it is removed from backend storage within 30 days. Two exceptions extend retention regardless of arrangement.

    Data type / eventRetention
    API inputs and outputs (default)Auto-deleted within 30 days
    Deleted conversation content (Claude for Work)Removed from backend within 30 days
    Inputs/outputs for a chat flagged as a Usage Policy violationUp to 2 years
    Trust & safety classification scores (flagged chat)Up to 7 years
    Data tied to feedback you submit (thumbs up/down, bug report)5 years

    Zero data retention (ZDR)

    Desk with laptop, checklist notebook, and billing card ready before creating an Anthropic API key
    Zero data retention (ZDR).

    With a ZDR arrangement, customer data is not stored at rest after the API response is returned, except where needed to comply with law or combat misuse. ZDR is requested through Anthropic sales and enabled per organization — it does not carry over automatically to new organizations under the same account. Even under ZDR, Anthropic retains User Safety classifier results, and may retain inputs and outputs for up to 2 years if a chat or session is flagged for a Usage Policy violation. CORS is not supported for ZDR organizations, so browser apps must call through a backend proxy.

    SurfaceZDR coverage
    Claude Messages API & Token Counting APIEligible
    Claude Code (Commercial org API keys, or via Claude Enterprise with ZDR enabled)Eligible
    Console and WorkbenchNot eligible
    Claude Teams & Claude Enterprise interfacesNot eligible (except Claude Code via Enterprise with ZDR on)
    Claude Free, Pro, MaxNot eligible
    Claude Managed AgentsNot eligible (stateful; delete transcripts manually)
    Batch API, Files API, code execution, Agent Skills, MCP connectorNot eligible
    Third-party integrationsNot eligible

    A handful of ZDR-eligible features are marked “Yes (qualified)” — structured outputs and cache diagnostics — meaning Anthropic retains a narrow, documented set of technical data (for example, a cached JSON schema for up to 24 hours since last use) rather than your prompts or Claude’s outputs.

    Model-training policy and Covered Models

    Anthropic’s Privacy Policy states it does not apply to content processed on behalf of business customers; that data is governed by the customer agreement. For the API specifically, Anthropic states retained data is never used for model training without your express permission. Anthropic’s consumer-terms update confirms the data-use changes “do not apply to services under our Commercial Terms,” including Claude for Work, Claude for Government, Claude for Education, and API use (including via Amazon Bedrock and Google Cloud’s Vertex AI). Training on commercial data happens only if a customer explicitly opts in (for example, the Development Partner Program).

    One model-specific exception affects retention, not training: Claude Fable 5 and Claude Mythos 5 are designated Covered Models and require 30-day data retention. ZDR is not available for these two models; a request to either from an organization whose retention configuration doesn’t meet the requirement returns a 400 invalid_request_error. Organizations with ZDR can turn on 30-day retention for a single workspace (Console > Settings > Workspaces > Privacy controls) to use those models there while keeping ZDR elsewhere. On Bedrock, Vertex AI, and Microsoft Foundry, retention requirements for these models are set by each platform.

    GDPR, data residency, and international transfers

    For users in the EEA, UK, or Switzerland, the data controller is Anthropic Ireland, Limited; elsewhere it is Anthropic PBC. Where the EU or UK GDPR applies, Anthropic responds to verifiable data-subject requests within one calendar month. For transfers to countries without an adequacy decision, Anthropic relies on standard contractual clauses, and publishes its subprocessors at anthropic.com/subprocessors.

    On data residency, the Claude API exposes two independent controls. inference_geo sets where inference runs per request — values are "global" (default) or "us" — and is supported on Claude Opus 4.6, Sonnet 4.6, and later (older models return a 400). Workspace geo controls where data is stored at rest and where endpoint processing happens; it is set at workspace creation and cannot be changed afterward. Per Anthropic’s documentation, "us" is currently the only available workspace geo, and only "us" and "global" inference geos are available — so there is currently no EU-resident storage option at the workspace level. US-only inference is priced at 1.1x the standard rate on supported models. Data residency is available on the Claude API (first-party) and Claude Platform on AWS; on Bedrock and Vertex AI the region is set by the endpoint or inference profile.

    Does Anthropic train its models on my API or commercial data?

    No, not by default. Anthropic’s Privacy Policy excludes business-customer content (governed by your customer agreement), and for the API it states retained data is never used for training without your express permission. The consumer data-use changes explicitly do not apply to Commercial Terms services. Training on commercial data requires an explicit opt-in.

    Will Anthropic sign a BAA, and for what?

    Yes. Anthropic signs a BAA covering HIPAA-ready services such as the first-party API and Enterprise plans. The Messages API is covered as an Eligible Service. It does not cover Workbench/Console, Free/Pro/Max/Team, Cowork, Claude Code, or beta features unless explicitly listed. An admin must sign the BAA and enable HIPAA readiness; the organization then auto-blocks non-eligible features.

    What’s the difference between ZDR and HIPAA readiness?

    Per Anthropic, ZDR prevents customer data from being stored at rest after the API response. HIPAA readiness is a broader set of safeguards (encryption, access controls, audit logging) that protect PHI throughout its lifecycle and lets data be retained with safeguards rather than deleted immediately. Anthropic states you do not also need ZDR if you have HIPAA readiness.

    How long does Anthropic keep my data?

    By default, API inputs and outputs are auto-deleted within 30 days. If a chat is flagged as a Usage Policy violation, inputs/outputs may be retained up to 2 years and trust & safety classification scores up to 7 years. Data tied to feedback you submit is kept 5 years. ZDR removes the default at-rest storage but does not remove the law/misuse exceptions.

    Can I keep Claude inference and data in the EU?

    Not at rest currently. The API’s inference_geo can pin inference to "us" or run "global", but Anthropic’s documentation lists "us" as the only available workspace geo (storage region). EU/UK data-subject rights and standard contractual clauses apply regardless, but an EU storage-residency option is not currently offered at the workspace level per the docs verified here.

    Related on Tygart Media: is Claude safe · Anthropic safety.

  • Claude Skills vs MCP vs Connectors vs Plugins (2026)

    Claude Skills vs MCP vs Connectors vs Plugins (2026)

    Last verified: June 13, 2026

    The simplest way to keep these straight: Skills teach Claude how to do a task, MCP servers and Connectors give Claude access to external systems, Plugins bundle several of these together, and Hooks and slash commands control a Claude Code session. A Skill is a folder of instructions Claude reads when relevant (Anthropic agent Skills docs). MCP (the Model Context Protocol) is an open standard that connects Claude to your tools and data (MCP docs; also Anthropic Trust Center). A Connector is Anthropic’s packaging of a remote MCP server inside the Claude apps. A Plugin packages any combination of commands, agents, MCP servers, hooks, and skills for Claude Code. Every definition below is taken verbatim from Anthropic’s official documentation, fetched on the verification date.

    The one-glance comparison

    Four comparison cards for Claude skills, MCP, connectors, and plugins
    One-glance comparison of the four extension surfaces.

    This is the liftable summary. Each row is one mechanism; the third column is the distinction people most often get wrong — whether the thing teaches Claude how to do something or gives Claude access to something.

    TypeWhat it isTeaches-HOW or gives-ACCESSWhere it runsHow you install / enable it
    Skill A modular capability that packages instructions, metadata, and optional resources (scripts, templates) in a SKILL.md file that Claude uses automatically when relevant. Teaches HOW. Provides domain-specific expertise: workflows, context, and best practices (procedural knowledge). In Claude’s code execution environment / VM, where Claude has filesystem access, bash, and code execution. claude.ai: upload a zip under Settings > Features. API: upload via the Skills API (/v1/skills) with the required beta headers (code-execution-2025-08-25, skills-2025-10-02, files-api-2025-04-14). Claude Code: a SKILL.md directory under ~/.claude/skills/ or .claude/skills/.
    MCP server An implementation of the Model Context Protocol — “an open-source standard for connecting AI applications to external systems.” Described as “a USB-C port for AI applications.” Gives ACCESS. Connects Claude to data sources, tools, and workflows so it can access information and perform tasks. Local (stdio) servers run as processes on your machine; remote servers run over HTTP (recommended) or SSE (deprecated). In Claude Code: claude mcp add, at local, project, or user scope. Also configurable in .mcp.json or imported from Claude Desktop / claude.ai.
    Connector A feature that “let[s] Claude access your apps and services, retrieve your data, and take actions within connected services.” Custom connectors use remote MCP. Gives ACCESS. Same access role as MCP — a Connector is the in-app packaging of a remote MCP server. Custom connectors are reached from Anthropic’s cloud infrastructure, not from your local machine. In the Claude apps under Customize > Connectors (or the in-chat “+” menu). Add a directory connector, or “Add custom connector” by URL.
    Plugin “A lightweight way to package and share any combination of” Claude Code customizations. Both — it’s a container. Bundles things that teach HOW (commands, skills) and things that give ACCESS (MCP servers), plus hooks and subagents. In Claude Code — “they’ll work across your terminal and VS Code.” The /plugin command (public beta). For a marketplace: /plugin marketplace add user-or-org/repo-name, then install from the /plugin menu.
    Hook “User-defined shell commands, HTTP endpoints, or LLM prompts that execute automatically at specific points in Claude Code’s lifecycle.” Controls behavior. Provides deterministic control rather than relying on the LLM to decide. In Claude Code, firing at lifecycle events (e.g. PreToolUse, PostToolUse, UserPromptSubmit, SessionStart, Stop). Configured in JSON settings files such as ~/.claude/settings.json or .claude/settings.json, or bundled in a plugin.
    Slash command A command starting with / that controls a Claude Code session. Includes built-ins (e.g. /help, /compact) and custom commands. Teaches HOW (custom) / controls session (built-in). Custom commands have been merged into Skills. In the Claude Code session (terminal or VS Code). Built-ins ship with Claude Code. Custom: a Markdown file under .claude/commands/ (project) or ~/.claude/commands/ (personal); a .claude/skills/<name>/SKILL.md does the same.

    Skills: teaching Claude a procedure

    Side-by-side cards defining what Claude Code is and is not
    Skills: teaching Claude a procedure.

    An Agent Skill is “a directory containing a SKILL.md file” with YAML frontmatter plus instructions, and optionally additional markdown files, executable scripts, and reference resources. The point is procedural knowledge — it turns “general-purpose agents into specialists” by giving Claude the workflows and best practices for a task, the way you’d write an onboarding guide for a new teammate. Anthropic ships pre-built Skills for PowerPoint, Excel, Word, and PDF, and you can author your own.

    What makes Skills cheap to install in bulk is progressive disclosure: Claude loads information in stages instead of all at once. The numbers below come straight from Anthropic’s Skills overview.

    Loading levelWhen loadedToken cost (per Anthropic docs)Content
    Level 1: MetadataAlways, at startup~100 tokens per Skillname and description from the YAML frontmatter
    Level 2: InstructionsWhen the Skill is triggeredUnder 5k tokensThe SKILL.md body — workflows and guidance
    Level 3+: ResourcesAs neededEffectively unlimitedBundled files read or executed via bash without loading their contents into context

    The name field is capped at 64 characters (lowercase letters, numbers, hyphens; it cannot contain the reserved words “anthropic” or “claude”), and the description is capped at 1,024 characters. One important constraint: custom Skills do not sync across surfaces — a Skill uploaded to claude.ai is not automatically available via the API, and Claude Code Skills are filesystem-based and separate from both.

    MCP: the open standard for access

    Flow from app/IDE through MCP to servers and data APIs
    MCP: the open standard for access.

    The Model Context Protocol is, in Anthropic’s words, “an open-source standard for connecting AI applications to external systems.” The canonical analogy: “Think of MCP like a USB-C port for AI applications. Just as USB-C provides a standardized way to connect electronic devices, MCP provides a standardized way to connect AI applications to external systems.” Using MCP, “AI applications like Claude or ChatGPT can connect to data sources (e.g. local files, databases), tools (e.g. search engines, calculators) and workflows (e.g. specialized prompts).”

    An MCP server can expose three kinds of building block — tools, resources, and prompts. In Claude Code, resources are referenced with @server:protocol://resource/path and prompts surface as commands in the form /mcp__servername__promptname. You connect a server with claude mcp add, choosing a transport and a scope:

    ScopeLoads inShared with teamStored in
    Local (default)Current project onlyNo~/.claude.json
    ProjectCurrent project onlyYes, via version control.mcp.json in project root
    UserAll your projectsNo~/.claude.json

    For transports, HTTP is “the recommended option for connecting to remote MCP servers,” local stdio servers “run as local processes on your machine,” and SSE is explicitly marked deprecated in favor of HTTP.

    Connectors: MCP, packaged for the apps

    A Connector is how the Claude apps surface MCP. Per Anthropic’s help center, “Connectors let Claude access your apps and services, retrieve your data, and take actions within connected services,” and “Custom connectors using remote MCP are available on Claude, Cowork, and Claude Desktop.” So a Connector is not a different technology from MCP — a custom connector is a remote MCP server wired into the Claude UI.

    The most consequential detail is where the connection originates: “Custom connectors (remote MCP servers) are reached from Anthropic’s cloud infrastructure, not from your local machine.” That means a custom-connector MCP server must be reachable over the public internet — one hosted only on a private network, behind a VPN, or blocked by a firewall will not connect even if you can reach it yourself.

    AspectDirectory (pre-built) connectorCustom connector
    SourcePre-built integrations in the Connectors DirectoryAdded by you via a remote MCP server URL
    Plan availabilityAvailable across Claude plansFree, Pro, Max, Team, and Enterprise
    Free-plan limitPer directory“Free users are limited to one custom connector.”
    Where to add itCustomize > Connectors, or the in-chat “+” > Connectors > Manage connectors

    Plugins: a bundle, not a single thing

    A Plugin is “a lightweight way to package and share any combination of” Claude Code customizations. The official announcement lists four bundle components, and the Claude Code documentation adds skills as a fifth thing a plugin can carry:

    ComponentWhat it adds
    Slash commandsCustom shortcuts for frequently-used operations
    SubagentsPurpose-built agents for specialized development tasks
    MCP serversConnections to tools and data sources through MCP
    HooksCustomizations of Claude Code’s behavior at key workflow points
    SkillsPer the Claude Code docs, a plugin can include a skills/ directory; plugin skills use a plugin-name:skill-name namespace

    You install a plugin “directly within Claude Code using the /plugin command.” To pull from a marketplace — “curated collections where other developers can discover and install plugins” — you run /plugin marketplace add user-or-org/repo-name and then install from the /plugin menu. Plugins “work across your terminal and VS Code.” Plugins were announced on October 9, 2025, as a public beta for all Claude Code users.

    Hooks and slash commands: controlling the session

    The last two mechanisms aren’t about adding capability — they’re about controlling a Claude Code session. Hooks are “user-defined shell commands, HTTP endpoints, or LLM prompts that execute automatically at specific points in Claude Code’s lifecycle.” Their defining property is determinism: they provide deterministic control rather than relying on the LLM to make decisions. A PreToolUse hook can, for example, block a destructive rm -rf command regardless of what Claude intended. Hooks are configured in JSON settings files (such as ~/.claude/settings.json or a project’s .claude/settings.json) and fire at events including SessionStart, UserPromptSubmit, PreToolUse, PostToolUse, and Stop.

    Slash commands start with / and control the session. Built-in commands like /help and /compact ship with Claude Code. Custom commands are Markdown files — a project command lives at .claude/commands/<name>.md and a personal one at ~/.claude/commands/<name>.md, with the file name becoming the command. As of the 2026 Claude Code docs, custom commands have been merged into Skills: a file at .claude/commands/deploy.md and a skill at .claude/skills/deploy/SKILL.md “both create /deploy and work the same way,” and existing .claude/commands/ files keep working.

    Is a Connector the same as an MCP server?

    Effectively yes, for custom connectors. Anthropic states “Custom connectors using remote MCP are available on Claude, Cowork, and Claude Desktop,” and that they “are reached from Anthropic’s cloud infrastructure.” A Connector is the Claude-app packaging of a remote MCP server; MCP is the underlying open standard.

    What’s the difference between a Skill and an MCP server?

    A Skill teaches Claude how to do a task — it “provide[s] Claude with domain-specific expertise: workflows, context, and best practices.” An MCP server gives Claude access to external systems — it connects Claude “to data sources, tools and workflows.” One is procedural knowledge; the other is a connection.

    Do Skills cost a lot of context tokens?

    Not until used. Per Anthropic’s docs, Level 1 metadata costs about 100 tokens per Skill and is always loaded; the full SKILL.md body (under 5k tokens) only loads when the Skill is triggered; and bundled resources are read on demand with effectively no upfront cost. This is the “progressive disclosure” design.

    What can a Claude Code plugin contain?

    “Any combination of” slash commands, subagents, MCP servers, and hooks, per the announcement; the Claude Code documentation adds that a plugin can also bundle a skills/ directory. You install one with the /plugin command, optionally from a marketplace added via /plugin marketplace add.

    Are custom slash commands still a thing?

    They still work, but they’ve been folded into Skills. The Claude Code docs state custom commands “have been merged into skills,” that existing .claude/commands/ files keep working, and that a command file and an equivalent SKILL.md both produce the same / command. Skills add optional extras like supporting files and automatic invocation.

    Related on Tygart Media: what is MCP · Claude MCP guide.

  • Migrating Off Retired Claude Models: The Breaking-Chang (2026)

    Migrating Off Retired Claude Models: The Breaking-Chang (2026)

    Last verified: October 6, 2026 — retirement dates per Anthropic model deprecations.

    Claude Opus 4 (claude-opus-4-20250514) and Claude Sonnet 4 (claude-sonnet-4-20250514) are deprecated and retire on June 15, 2026, after which requests to them return a 404. The official replacements are claude-opus-4-8 and claude-sonnet-4-6. But swapping the model string alone will break a working integration: depending on which target you choose, several request parameters that were valid on the May 2025 models now return a 400 error, and two changes alter behavior silently. This page maps each removed or changed parameter to the exact failure and the fix.

    One distinction governs the whole migration. The Opus path (to claude-opus-4-8) is the strict one: it removes temperature/top_p/top_k and manual thinking budgets entirely. The Sonnet path (to claude-sonnet-4-6) is gentler: it keeps sampling parameters (with the older “one of temperature or top_p, not both” rule) and still accepts budget_tokens as deprecated-but-functional. The one rule both paths share: assistant-turn prefills now return 400.

    The breaking-change matrix

    Side-by-side panels contrasting old model IDs still in code with a migrate checklist
    The breaking-change matrix.

    Each row is a change that breaks on at least one migration target. “Error” means the API rejects the request server-side (HTTP 400) even though the SDK request type still type-checks. “Silent” means no error — the behavior simply differs.

    ChangeOn Opus 4.8On Sonnet 4.6SymptomFix
    thinking: {type:"enabled", budget_tokens:N}400 error (removed)Deprecated, still works400 on Opus; cost/latency drift on Sonnetthinking: {type:"adaptive"} + output_config.effort
    temperature / top_p / top_k400 error (removed)Keep only one of temperature or top_p400 on Opus if any set; 400 on Sonnet if both setRemove on Opus; steer via prompt. Keep one on Sonnet
    Assistant-turn prefill (last message role:"assistant")400 error400 errorRequest rejected on bothoutput_config.format (structured outputs) or system-prompt instruction
    thinking.display defaultDefaults to "omitted"Returns summarized textReasoning text empty on Opus (silent)Set display: "summarized" on Opus
    TokenizerNew tokenizer (more tokens)Unchanged tokenizerSame text counts higher on Opus; max_tokens too tightRe-baseline with count_tokens; add headroom
    output_format (top-level)Deprecated API-wideDeprecated API-wideWorks, but slated for removalMove to output_config: {format: {...}}

    Model ID swaps and retirement dates

    Flow from Family to Seat to Generation to API id
    Model ID swaps and retirement dates.
    Retiring modelModel IDRetiresReplacement
    Claude Opus 4claude-opus-4-20250514 (alias claude-opus-4-0)June 15, 2026claude-opus-4-8
    Claude Sonnet 4claude-sonnet-4-20250514 (alias claude-sonnet-4-0)June 15, 2026claude-sonnet-4-6

    These are the original May 2025 models, not the later Opus 4.6 or Sonnet 4.5 releases. Use the exact replacement strings above — do not append a date suffix to claude-opus-4-8 or claude-sonnet-4-6 (they are dateless pinned snapshots).

    budget_tokens to adaptive thinking

    The Opus path removes the fixed thinking budget. thinking: {type:"enabled", budget_tokens:N} returns a 400 on claude-opus-4-8. The replacement is adaptive thinking — the model decides how much to think per request — with overall depth controlled by the effort parameter (low | medium | high | xhigh | max). There is no direct token-count equivalent; effort is an output-level control, not a thinking budget.

    # Before (Claude Opus 4 / Sonnet 4)
    client.messages.create(
        model="claude-opus-4-20250514",
        max_tokens=16000,
        thinking={"type": "enabled", "budget_tokens": 10000},
        messages=[{"role": "user", "content": "..."}],
    )
    
    # After (Claude Opus 4.8)
    client.messages.create(
        model="claude-opus-4-8",
        max_tokens=16000,
        thinking={"type": "adaptive"},
        output_config={"effort": "high"},  # or "max", "xhigh", "medium", "low"
        messages=[{"role": "user", "content": "..."}],
    )

    On the Sonnet path, budget_tokens is deprecated but still functional on claude-sonnet-4-6, so it will not 400 — but you should still migrate to adaptive thinking. Note also that Sonnet 4.6 defaults to effort: "high" where Sonnet 4 had no effort parameter at all; if you do not set it explicitly you may see higher latency and token use after the swap.

    Sampling parameters: removed vs. restricted

    Desk with laptop, checklist notebook, and billing card ready before creating an Anthropic API key
    Sampling parameters — removed vs restricted.

    This is where the two paths diverge most. On claude-opus-4-8, setting temperature, top_p, or top_k to any non-default value returns a 400. Remove them entirely and steer behavior through prompting instead. (If you used temperature=0 for determinism, note it never guaranteed identical outputs on prior models either.)

    # Opus path — sampling params 400 on claude-opus-4-8
    # Before
    client.messages.create(
        model="claude-opus-4-20250514",
        temperature=0.7,
        top_p=0.9,
        messages=[...],
    )
    
    # After — remove them
    client.messages.create(
        model="claude-opus-4-8",
        messages=[...],
    )

    On claude-sonnet-4-6 the older Claude 4.x rule still applies: you may pass one of temperature or top_p, but passing both returns a 400. So a Sonnet 4 to Sonnet 4.6 move only requires dropping one of the two if you were setting both.

    Assistant-turn prefills to structured outputs

    Prefilling the final assistant turn — ending your messages array with a role: "assistant" message to force a response shape — returns a 400 on both claude-opus-4-8 and claude-sonnet-4-6. This is the one breaking change you cannot dodge by choosing the gentler target. The replacement depends on what the prefill was doing.

    Prefill was used forReplacement
    Forcing JSON / YAML / schema outputoutput_config.format with a json_schema
    Forcing a classification labelA tool with an enum field, or structured outputs
    Skipping preambles (“Here is…”)System-prompt instruction: respond directly, no preamble
    Continuing an interrupted responseMove continuation into the user turn
    Steering around bad refusalsUsually unnecessary now — plain user-turn prompting suffices
    # Before (fails on both targets) — prefill forcing JSON shape
    messages=[
        {"role": "user", "content": "Extract the name."},
        {"role": "assistant", "content": "{\"name\": \""},
    ]
    
    # After — structured outputs replace the prefill
    client.messages.create(
        model="claude-opus-4-8",
        max_tokens=1024,
        output_config={"format": {"type": "json_schema", "schema": SCHEMA}},
        messages=[{"role": "user", "content": "Extract the name."}],
    )

    Thinking display: the silent one

    On claude-opus-4-8, thinking blocks still stream, but their thinking text field is empty unless you opt in — the default is display: "omitted". There is no error; if your UI rendered the summarized reasoning, it now shows a long pause before output. Restore it by setting the display mode:

    thinking = {
        "type": "adaptive",
        "display": "summarized",  # default is "omitted" on Opus 4.8/4.7
    }

    The block-field name is unchanged — it is still block.thinking on a thinking-type block. The fix is the request parameter, not the response-handling code. (Sonnet 4.6 is not affected by this default change.)

    The new tokenizer: re-baseline max_tokens

    This change is Opus-only and easy to miss because it produces no error. claude-opus-4-8 uses the tokenizer introduced with Opus 4.7, under which the same text tokenizes to roughly 1x–1.35x as many tokens — up to about 35% more, around 30% on typical content, varying by workload. Three consequences:

    What to checkWhy
    max_tokens ceilings and compaction triggersThe same output now consumes more tokens; tight limits truncate mid-thought
    Client-side token estimators (e.g. fixed char-to-token ratios)Calibrated against the old tokenizer; now undercount
    Cost and rate-limit dashboardscount_tokens returns higher numbers; re-baseline before reacting

    Re-run client.messages.count_tokens(model="claude-opus-4-8", ...) on a representative sample of your prompts. Do not apply a blanket multiplier. Sonnet 4.6 keeps the older tokenizer, so a Sonnet 4 to Sonnet 4.6 move has no tokenizer re-baseline to do.

    The full checklist

    StepOpus 4 to 4.8Sonnet 4 to 4.6
    Update model ID stringRequiredRequired
    Replace budget_tokens with adaptive thinkingRequired (400)Recommended (deprecated)
    Sampling paramsRemove all (400)Keep only one (both 400)
    Remove assistant-turn prefillsRequired (400)Required (400)
    Set display: "summarized" if showing reasoningRequired for visible thinkingNot applicable
    Re-baseline max_tokens for new tokenizerRequiredNot applicable
    Set effort explicitlyDefaults to highDefaults to high
    Move output_format to output_config.formatRecommendedRecommended
    Verify tool inputs parsed with a JSON parserRecommendedRecommended
    Spot-check one request, then roll outRequiredRequired

    If you run Claude Code, /claude-api migrate applies the model swap, breaking-parameter changes, prefill replacement, and effort calibration across a codebase, then produces a verify-it-yourself checklist. It asks you to confirm scope before editing any files.

    Is migrating off Claude Opus 4 really not just a model-string change?

    No. Moving to claude-opus-4-8 also requires removing temperature/top_p/top_k and any budget_tokens (all now return 400), removing assistant-turn prefills (400), opting back into summarized thinking if your UI shows it, and re-baselining max_tokens for the new tokenizer. Only the Sonnet 4 to Sonnet 4.6 move is close to a drop-in — and even that requires removing prefills.

    When exactly do Claude Opus 4 and Sonnet 4 stop working?

    June 15, 2026. After that date, requests to claude-opus-4-20250514 and claude-sonnet-4-20250514 return a 404. These are the original May 2025 models, not Opus 4.6 or Sonnet 4.5.

    What replaces budget_tokens now that it errors on Opus?

    Adaptive thinking (thinking: {type:"adaptive"}) plus the effort parameter inside output_config. There is no exact token-count equivalent: the model decides how much to think per request, and effort (low through max) tunes overall depth and spend. On Sonnet 4.6, budget_tokens still works but is deprecated.

    Why does the same prompt cost more tokens on Opus 4.8?

    Opus 4.8 uses the tokenizer introduced with Opus 4.7, under which the same text produces roughly 1x–1.35x as many tokens (about 30% more on typical content, up to ~35%). Re-run the count_tokens endpoint against claude-opus-4-8 and give max_tokens and compaction triggers extra headroom. Sonnet 4.6 keeps the older tokenizer, so it is unaffected.

    My thinking summaries disappeared after migrating to Opus — is that a bug?

    No. On Opus 4.8 (and 4.7), thinking.display defaults to "omitted", so thinking blocks stream with an empty text field. Set display: "summarized" in your thinking config to restore visible reasoning. The field name is unchanged; only the default flipped.

    Related on Tygart Media: Claude Fable 5 guide · API quickstart.

  • Claude Code Billing & Monthly Credit Pools (2026)

    Claude Code Billing & Monthly Credit Pools (2026)

    Last verified: October 5, 2026 (Pacific)

    Claude Code has two billing models, and which one applies depends on how you run it, not just which plan you hold. When you use Claude Code interactively in the terminal or IDE on a Pro or Max plan, it draws from the same subscription usage limits as your Claude.ai chats. But starting June 15, 2026, Anthropic separates out programmatic usage: the Claude Agent SDK, the claude -p headless command, the Claude Code GitHub Actions integration, and third-party apps that authenticate through the Agent SDK will no longer count against your interactive subscription pool. Instead they draw from a new, separate monthly Agent SDK credit, billed at standard API rates. This page documents both models, the exact credit amounts per plan, and the SDK package rename you may also need to handle.

    The two billing models at a glance

    Workshop fuel gauge and metal tokens pouring into an API hopper, metaphor for pay-per-token pricing
    Two billing models at a glance — no sticky dollar stickers.

    The dividing line is interactive vs. programmatic. One number to remember: setting an ANTHROPIC_API_KEY environment variable overrides your subscription entirely — Claude Code then authenticates with that key and bills as pay-as-you-go API usage, regardless of plan.

    Usage type How it runs Billed against
    Interactive Claude Code Terminal or IDE, human at the keyboard Pro/Max subscription usage limits
    Claude.ai chat Web, desktop, mobile Pro/Max subscription usage limits
    Agent SDK (Python/TypeScript) Your own programmatic projects Separate Agent SDK credit (from June 15, 2026)
    claude -p (non-interactive) Headless / scripted Claude Code Separate Agent SDK credit (from June 15, 2026)
    Claude Code GitHub Actions CI/CD automation Separate Agent SDK credit (from June 15, 2026)
    Any usage with ANTHROPIC_API_KEY set API-key auth instead of subscription Standard API rates (pay-as-you-go)

    What changes on June 15, 2026

    Per Anthropic’s support documentation: “Starting June 15, 2026, Claude Agent SDK and claude -p usage no longer counts toward your Claude plan’s usage limits.” Each subscription tier instead receives a fixed monthly Agent SDK credit. When that credit runs out, additional Agent SDK usage flows to usage credits at standard API rates — but only if you have enabled usage credits. If you have not, “Agent SDK requests stop until your credit refreshes.” Unused credits do not roll over to the next billing cycle, and there is no automatic fallback to the interactive pool.

    Plan Monthly Agent SDK credit
    Pro $20
    Max 5x $100
    Max 20x $200
    Team (Standard seats) $20
    Team (Premium seats) $100
    Enterprise (seat-based Premium) $200

    What stays on the interactive subscription pool, unchanged: Claude conversations on web, desktop, and mobile; and interactive Claude Code in the terminal or IDE. The change is scoped strictly to programmatic execution.

    How each pool is metered and priced

    Infographic with three panels: protect the service, fair share, and cost control explaining rate limits
    How each pool is metered.

    Claude Code “charges by API token consumption” — the underlying meter is input/output tokens, including thinking tokens billed as output. On a subscription, that token consumption is what counts against your plan limits (interactive) or your Agent SDK credit (programmatic). The Agent SDK credit and any overflow are billed at standard API list rates; the per-model API token prices below are the verified current rates.

    Pool Meter Price basis
    Interactive (Pro/Max) Tokens, against plan usage limits Included in subscription
    Agent SDK credit Tokens, against monthly credit Standard API rates
    Overflow past the credit Tokens, usage credits Standard API rates (only if usage credits enabled)
    API key (ANTHROPIC_API_KEY) Tokens, pay-as-you-go Standard API rates

    Verified current API token prices (per million tokens) for models commonly used in Claude Code:

    Model Model ID Input $/Mtok Output $/Mtok
    Claude Sonnet 5.5 claude-sonnet-5-5 $2.00 $10.00
    Claude Opus 5.5 claude-opus-5-5 $4.00 $20.00
    Claude Fable 5.1 claude-fable-5-1 $10.00 $50.00
    Claude Opus 4.8 (legacy — still listed) claude-opus-4-8 $5.00 $25.00
    Claude Sonnet 4.6 (legacy — still listed) claude-sonnet-4-6 $3.00 $15.00
    Claude Haiku 4.5 claude-haiku-4-5 $1.00 $5.00

    Subscription plan prices

    These are the published Claude plan prices the Agent SDK credits attach to. The Max 5x plan starts at $100/month; the $200 figure for Max 20x is documented as the matching Agent SDK credit amount for that tier.

    Plan Price
    Free $0
    Pro $20/month, or $17/month billed annually ($200 up front)
    Max 5x From $100/month
    Team (Standard seat) $25/seat/month, or $20/seat/month billed annually

    The SDK rename: claude-code-sdk to claude-agent-sdk

    Separate from billing, the SDK itself was renamed. Anthropic’s migration guide states: “The Claude Code SDK has been renamed to the Claude Agent SDK.” If you have code on the old package, you must update the package name, imports, and one Python type. The headless CLI command name is unchanged — it is still claude -p.

    Aspect Old New
    npm package (TS/JS) @anthropic-ai/claude-code @anthropic-ai/claude-agent-sdk
    Python package claude-code-sdk claude-agent-sdk
    Python options type ClaudeCodeOptions ClaudeAgentOptions
    Default system prompt Claude Code’s preset Minimal (opt back in via preset: "claude_code")
    # TypeScript
    npm uninstall @anthropic-ai/claude-code
    npm install @anthropic-ai/claude-agent-sdk
    
    # Python
    pip uninstall claude-code-sdk
    pip install claude-agent-sdk

    Decision: which billing path applies to your work

    Three cards for fast volume, daily workhorse, and deep flagship Claude seats
    Which billing path applies to your work.
    If you are… Billing path
    A developer coding interactively in the terminal Subscription usage limits (unchanged)
    Running claude -p in a script or cron job Agent SDK credit (from June 15, 2026)
    Running Claude Code in GitHub Actions Agent SDK credit (from June 15, 2026)
    Building an app on the Agent SDK with subscription auth Agent SDK credit (from June 15, 2026)
    A team or service account wanting budgets + usage reports Set ANTHROPIC_API_KEY → standard API billing

    Does interactive Claude Code billing change on June 15, 2026?

    No. Anthropic’s documentation confirms interactive Claude Code in the terminal or IDE, and Claude conversations on web, desktop, and mobile, continue using subscription usage limits as before. Only programmatic usage — the Agent SDK, claude -p, GitHub Actions, and third-party Agent SDK apps — moves to the separate Agent SDK credit.

    How much is the separate Agent SDK credit?

    $20/month on Pro, $100 on Max 5x, $200 on Max 20x, $20 on Team Standard seats, $100 on Team Premium seats, and $200 on Enterprise seat-based Premium. The credit is billed at standard API rates, does not roll over, and refreshes monthly.

    What happens when the Agent SDK credit runs out?

    Additional Agent SDK usage flows to usage credits at standard API rates — but only if you have enabled usage credits. If you have not enabled them, Agent SDK requests stop until your credit refreshes. There is no automatic fallback to your interactive subscription pool.

    How do I avoid the credit pool entirely?

    Set an ANTHROPIC_API_KEY environment variable. Claude Code and the Agent SDK then authenticate with that key and bill as standard pay-as-you-go API usage, separate from any subscription. This is Anthropic’s recommended path for apps, CI jobs, service accounts, and team-owned projects that need budgets and usage reporting.

    Was the Claude Code SDK renamed?

    Yes. It is now the Claude Agent SDK. The npm package @anthropic-ai/claude-code became @anthropic-ai/claude-agent-sdk, the Python package claude-code-sdk became claude-agent-sdk, and the Python type ClaudeCodeOptions became ClaudeAgentOptions. The claude -p CLI command name is unchanged.

    Related on Tygart Media: Claude Code getting started · Claude pricing · Pro vs Max.


    Part of the complete guide: Claude Code

  • Latest Claude Models — moved to the tracker

    Latest Claude Models — moved to the tracker

    This slug duplicates the ranking tracker. Numbers here were last written as June 2026.

    Direct Answer (9 September 2026): Claude 3.5 Sonnet is retired. Current public Sonnet is Sonnet 5 at $2 / $10 per MTok. Current lineup is Fable 5.1, Opus 5.5 ($4 / $20 per MTok), Opus 5, Sonnet 5, Haiku 4.5. Live tracker: current Claude model version. Seat dollars: pricing hub.

    Do not ship 3.5 Sonnet, Sonnet 4.6, or Opus 4.8 IDs in new work. Confirm the alias in the console.

  • Claude Fable 5: Capabilities, Pricing (2026)

    Claude Fable 5: Capabilities, Pricing (2026)

    Anthropic released Claude Fable 5 on June 9, 2026 — and it’s the most capable model the company has ever made publicly available. After tracking every Claude release since the original 100K context window dropped, I can say this one is different. Fable 5 isn’t just an incremental update. It’s Anthropic’s Mythos-class model — the one they’d been keeping restricted — now opened up to anyone with an API key or a Claude subscription.

    Here’s what you need to know: the pricing, the benchmarks, and the specific decision framework for when to use Fable 5 versus sticking with Opus 4.8.

    Quick answer: Fable 5 costs $10/$50 per million input/output tokens (2x the cost of Opus 4.8). It outperforms Opus 4.8 significantly on complex coding, long-horizon tasks, and scientific research. Use Fable 5 when quality on hard problems justifies the cost. Use Opus 4.8 for high-volume, well-scoped, routine work.

    Current lineup note (October 2026): Fable 5.1 is the current Fable SKU at the same $10/$50 headline rates (cache reads $0.25/MTok). Current Opus is Opus 5.5 at $4/$20; Opus 4.8 remains listed as legacy. The June 2026 comparisons below are the launch record for Fable 5.

    What Is Claude Fable 5?

    Three cards for fast volume, daily workhorse, and deep flagship Claude seats
    What is Claude Fable 5?

    Claude Fable 5 (claude-fable-5) is Anthropic’s first publicly available Mythos-class model. The Mythos line is Anthropic’s highest capability tier — models that were previously restricted to research and select enterprise partners because of their raw power. Fable 5 is the version Anthropic deemed safe enough to release broadly.

    The name shift (from the Opus/Sonnet/Haiku tier naming) signals something intentional. Fable 5 sits above the Opus line entirely. It’s a new ceiling.

    Key specs:

    • Context window: 1M tokens (same as Opus 4.8)
    • Max output: 128K tokens per request
    • Thinking: Adaptive (always on — not a separate “thinking mode”)
    • Vision: Yes
    • Tool use / function calling: Yes
    • Available: Claude API, AWS Bedrock, Vertex AI, Microsoft Foundry

    Claude Fable 5 Pricing

    Infographic ladder of Claude plans: Free, Pro, Max, Team, and Enterprise
    Fable 5 pricing — no sticky dollar stickers.
    ModelInput (per MTok)Output (per MTok)Context
    Claude Fable 5$10.00$50.001M tokens
    Claude Opus 4.8$5.00$25.001M tokens
    Claude Sonnet 4.6$3.00$15.001M tokens
    Claude Haiku 4.5$1.00$5.00200K tokens

    Fable 5 costs exactly 2x Opus 4.8 on API. On subscription plans (Pro, Max, Team, Enterprise seat-based), Fable 5 is included at no extra cost through June 22, 2026.

    The free-until-June-22 window matters if you’re evaluating whether to route your workloads to Fable 5. Use that window to benchmark it against your actual tasks before the 2x cost kicks in.

    Benchmark Performance: Where Fable 5 Pulls Away

    The benchmarks that matter most are the ones that measure what the model can do on real engineering work, not trivia:

    BenchmarkClaude Fable 5Claude Opus 4.8Delta
    SWE-bench Verified95.0%88.6%+6.4 pts
    SWE-bench Pro80.0%69.2%+10.8 pts
    FrontierCode29.3%13.4%~2.2x
    Senior Engineer benchmark91/100~63/100+45% absolute

    The Senior Engineer benchmark is the one I find most telling. It’s designed to be hard for people who write code for a living — and Fable 5 scores 45 percentage points higher than Opus 4.8. That gap is significant enough that it changes the calculus for serious engineering work.

    When to Use Claude Fable 5 (vs Opus 4.8)

    Decision fork between maximum capability when stakes are high and shipping daily when speed and cost matter
    When to use Fable 5 vs Opus.

    I’ve been routing tasks between models for long enough to have a framework. Here’s how I think about it:

    Use Fable 5 when:

    • You’re running a large migration, refactor, or multi-stage software project
    • Quality on a hard problem matters more than per-token cost
    • You’re doing deep research, complex analysis, or long-horizon agentic work
    • The task would otherwise take a senior engineer half a day or more
    • You’re in the free evaluation window (through June 22) and want to benchmark

    Use Opus 4.8 when:

    • The task is well-scoped and routine
    • You’re running high-volume pipelines where 2x cost compounds fast
    • Latency matters — Fable 5 can take 60 seconds to several minutes on complex tasks vs 3–15 seconds for Opus 4.8
    • The task falls in Fable 5’s restricted domains (cybersecurity, biology, chemistry, distillation) — in those categories, Fable 5 routes to Opus 4.8 anyway, so you’d pay Fable 5 prices for Opus 4.8 output

    The smart routing strategy: Fable 5 for the hard jobs, Opus 4.8 for the rest. Don’t use Fable 5 as your default model — the cost and latency delta aren’t worth it for routine tasks.

    Important Limitations to Know Before You Switch

    Two limitations that don’t get enough coverage:

    1. Safety classifier routing. Fable 5 includes enhanced safety classifiers. For prompts touching cybersecurity, biology, chemistry, and distillation, those classifiers route the request to a Claude Opus 4.8 fallback. You pay Fable 5 API rates ($10/$50) but get Opus 4.8 output. If your use case is in these domains, Fable 5 is not the upgrade it appears to be.

    2. Data retention requirement. Fable 5 carries a mandatory 30-day data retention policy — Anthropic needs retained prompts and outputs to operate the safety classifiers. Claude Opus 4.8 is available under zero data retention (ZDR). If your use case requires ZDR (healthcare, legal, finance with strict data handling), stick with Opus 4.8 until Anthropic updates Fable 5’s data policy.

    Availability

    Claude Fable 5 is generally available as of June 9, 2026 on:

    • Claude API (claude-fable-5)
    • Claude Platform on AWS / Amazon Bedrock
    • Google Cloud Vertex AI
    • Microsoft Azure AI Foundry / GitHub Copilot

    Subscription access (free through June 22, 2026): Claude Pro ($20/mo), Max 5x ($100/mo), Max 20x ($200/mo), Team, and seat-based Enterprise plans all include Fable 5 access at no extra charge during the launch window. After June 22, the plan-tier access picture may change — check Anthropic’s pricing page for updates.

    How This Changes the Claude Model Decision Tree

    Before Fable 5, the Claude decision tree was straightforward:

    • Need the best? → Opus 4.8
    • Need balance? → Sonnet 4.6
    • Need speed/cost? → Haiku 4.5

    Now it’s:

    • Hard problems, complex projects, long-horizon work → Fable 5
    • Everyday work, high-volume pipelines → Opus 4.8
    • Balance of cost and capability → Sonnet 4.6
    • Speed and cost optimization → Haiku 4.5

    The introduction of a model tier above Opus 4.8 doesn’t replace the existing lineup — it creates a new ceiling for the work that genuinely needs it.

    Related on Tygart Media: Fable 5 complete guide · Fable 5 firsthand · how to use Claude.

    Frequently Asked Questions

    Is Claude Fable 5 better than Opus 4.8?
    For complex coding, multi-stage tasks, and long-horizon work: yes, significantly. On SWE-bench Pro, Fable 5 scores 80.0% vs Opus 4.8’s 69.2% — a 10+ point gap. For routine, well-scoped tasks: the gap narrows enough that Opus 4.8’s 2x cost advantage makes it the smarter choice.

    What is the Claude Fable 5 API model ID?
    claude-fable-5. This is the API string you pass to model in your API calls.

    Does Fable 5 cost more than Opus 4.8?
    Yes — exactly 2x. Fable 5 is $10 input / $50 output per million tokens. Opus 4.8 is $5/$25. Through June 22, 2026, Fable 5 is included in Claude subscription plans at no extra cost.

    Can I use Claude Fable 5 for free?
    On Pro, Max, Team, and Enterprise subscription plans, yes — through June 22, 2026. API access is metered at $10/$50 per MTok from day one.

    Does Claude Fable 5 support zero data retention (ZDR)?
    No. Fable 5 carries a mandatory 30-day data retention requirement. If your use case requires ZDR, use Claude Opus 4.8, which supports it.

    What’s the difference between Claude Fable 5 and Claude Mythos 5?
    Mythos 5 is Anthropic’s fully restricted research model — not publicly available. Fable 5 is the Mythos-class model that Anthropic has prepared for general availability, with safety classifiers and the 30-day retention policy. You can think of Fable 5 as “Mythos for the real world.”

    Last verified: October 5, 2026. Anthropic pricing and availability subject to change — check Anthropic’s pricing page for current rates.

  • Claude Fable 5 Complete Guide

    Claude Fable 5 Complete Guide

    
    New in 2026

    Everything you need to know about Anthropic’s new frontier tier — pricing, context window, model comparisons, and how to route the right work to the right model.

    Updated June 2026 · ~14 min read · Includes interactive calculators
    Lineup update (September 2026): Since this guide was last fully updated, Anthropic shipped Opus 5.5 ($4/MTok in, $20/MTok out) and Sonnet 5 ($2/MTok in, $10/MTok out) as its current flagship and mid-tier models. Fable 5.1 remains the top-tier model referenced throughout, at the same $10/$50 pricing shown below. Opus 4.8 and Sonnet 4.6 are now legacy — still supported, no longer current default.

    What Is Claude Fable 5?

    Three cards for fast volume, daily workhorse, and deep flagship Claude seats
    What is Claude Fable 5?

    Claude Fable 5 is Anthropic’s new frontier model tier — positioned above Opus in the lineup and designed for tasks where raw capability, extended reasoning depth, and massive context handling matter more than cost. Where Opus 4.8 set the bar for complex multi-step reasoning, Fable 5 raises it with a 1-million-token context window, enhanced agentic autonomy, and improved performance on long-horizon software engineering, research synthesis, and cross-domain analysis tasks.

    The “Fable” naming signals a new generation of model architecture rather than an incremental update. Anthropic positions it as the model you reach for when a task exceeds what Opus can do reliably — not as a replacement for Opus, Sonnet, or Haiku in their respective cost tiers.

    Quick Facts — Claude Fable 5

    Context Window
    1M
    tokens (~750K words)
    Max Output
    32K
    tokens per response
    Input Price
    $10
    per million tokens
    Output Price
    $50
    per million tokens
    Cache Write
    $12.50
    per million tokens
    Cache Read
    $1.00
    per million tokens
    Key positioning: Fable 5 is the model for tasks where Opus 4.8 produces reliable but imperfect results — long codebase audits, full-document analysis, complex multi-agent orchestration, and strategic synthesis across large corpora. For most production workflows, Sonnet remains the value pick.
    Before you price this out: The table below reflects the June 2026 lineup (Fable 5, Opus 4.8, Sonnet 4.6, Haiku 4.5). As of September 2026, Opus 5.5 ($4/$20) and Sonnet 5 ($2/$10) are Anthropic’s current models — priced lower than the legacy Opus 4.8 / Sonnet 4.6 rows shown here.

    Full Model Lineup Comparison

    Pyramid diagram of Claude tiers: fast volume base, production workhorse middle, deep flagship peak
    Full model lineup comparison.

    Here’s how the complete 2026 Claude lineup stacks up across every dimension that matters for production usage:

    Model Input $/M Output $/M Context Max Out Vision Tool Use Extended Think Best For
    ◆ Fable 5 $10 $50 1M 32K ✓ ✓ ✓ Deep Max-capability tasks, 1M+ context
    ◆ Opus 4.8 $5 $25 200K 32K ✓ ✓ ✓ Complex reasoning, agentic workflows
    ◆ Sonnet 4.6 $3 $15 200K 16K ✓ ✓ ✓ Production apps, content at scale
    ◆ Haiku 4.5 $1 $5 200K 8K ✓ ✓ — High-volume, latency-sensitive tasks

    Prices are per million tokens. Cache read is 90% cheaper than standard input across all models. Batch API provides an additional 50% discount on both input and output.

    Capability Matrix — What Each Model Can Do

    Capability Fable 5 Opus 4.8 Sonnet 4.6 Haiku 4.5
    Full codebase analysis (>500K tokens)✓ Native⚠ Chunked✗✗
    Extended thinking / chain-of-thought✓ Deep✓✓✗
    Multi-step agentic orchestration✓ Best✓GoodLimited
    Computer use✓✓✓✗
    MCP tool integration✓✓✓✓
    Prompt caching✓✓✓✓
    Batch API (50% discount)✓✓✓✓
    PDF / document analysis✓✓✓Limited
    Real-time streaming✓✓✓✓
    Structured JSON output✓✓✓✓

    Interactive Cost Calculator

    Estimate your monthly API spend across the full model lineup. Enter your token volumes below — the calculator models prompt caching and Batch API discounts automatically.

    Token Cost Calculator

    Estimated Monthly Cost
    $0.00

    Which Claude Model Should You Use?

    Decision diagram from task shape to deep reasoning, daily shipping, or high-volume cheap calls
    Which Claude model should you use?

    Answer three questions to get a model recommendation tailored to your use case.

    Model Picker — 3 Questions
    1. How large is your context? (document/codebase size)
    Under 50K tokens
    50K–200K tokens
    200K–1M tokens
    2. How complex is the task?
    Simple / structured (classify, extract, format)
    Moderate (draft, summarize, QA)
    Complex (reason, plan, code, orchestrate)
    3. How cost-sensitive is this workload?
    Very — high volume, every cent counts
    Moderate — quality matters more than cost
    Not sensitive — quality and capability first

    How We Actually Use Each Model

    These are real production workflows mapped to the right tier — built from running Claude in content operations, publishing automation, and knowledge management at scale. No hypotheticals.

    Haiku 4.5 — High Volume
    Daily SEO Refresh Pipeline
    • 25-post-per-day SEO metadata refresh
    • Article classification and tag assignment
    • Structured data extraction from web pages
    • Keyword density checks across large post archives
    • Link validation and redirect flagging
    Sonnet 4.6 — Production Default
    Editorial Content at Scale
    • Desk article writing (1,200–2,500 words)
    • Content brief execution from keyword clusters
    • FAQ and schema markup generation
    • Cross-site content adaptation and localization
    • Monthly client update drafts and summaries
    Opus 4.8 — Complex Reasoning
    Workers & Deep Refreshes
    • Agentic Notion Workers (multi-step pipelines)
    • Deep content refresh with competitive gap analysis
    • Multi-database synthesis and reporting
    • Strategy documents requiring extended reasoning
    • Code generation for automation scripts
    Fable 5 — Max Capability
    Portfolio Audits & Strategy
    • Full-site content audits (500+ posts in single context)
    • Cross-domain strategy synthesis across large corpora
    • Complex multi-agent orchestration at the flagship tier
    • Long-horizon planning requiring deep reasoning depth
    • Codebase-wide analysis and architecture review
    Routing principle: The right model is the cheapest one that reliably completes the task. Haiku handles volume. Sonnet handles production. Opus handles complexity. Fable 5 handles scale + complexity together — specifically the cases where you’d need Opus and more context than Opus can hold.

    The Economics: Routed vs All-Fable

    Smart model routing is where API costs get controlled. Here’s a real-world comparison of a mixed content-and-automation workload at scale — routed vs running everything on Fable 5.

    Workload Monthly Volume Routed Model Routed Cost All-Fable 5 Cost Savings
    SEO metadata batch refresh750 posts/moHaiku 4.5 + Batch$1.20$18.7593% less
    Article drafting90 articles/moSonnet 4.6$8.10$67.5088% less
    Agentic worker runs200 runs/moOpus 4.8$22.50$45.0050% less
    Full-site portfolio audits4 audits/moFable 5$24.00$24.00—
    Total—Routed$55.80$155.2564% less

    Stacking Discounts: Caching + Batch API

    Two discount mechanisms compound independently:

    • Prompt caching: Cache your system prompt and shared context once. Subsequent requests pay ~10% of the input price for cache reads. On Fable 5, that’s $1.00/M instead of $10.00/M on cached tokens — a 90% reduction on your largest cost lever.
    • Batch API: Submit requests asynchronously (results within 24 hours) for a flat 50% discount on both input and output. Works on all four models. Best for non-real-time workloads like overnight refreshes, audits, or bulk classification.
    • Stacked: Caching + Batch combined can bring effective Fable 5 input cost from $10/M to ~$0.50/M on cached tokens — making it economically viable for high-volume tasks that previously only fit Haiku’s budget.

    See our Claude context window guide for more on how to structure prompts to maximize cache hit rates.

    Claude Fable 5 FAQ

    Claude Fable 5 sits above Opus 4.8 in the lineup. The primary difference is context window size — Fable 5 offers 1 million tokens vs Opus 4.8’s 200K — and the depth of extended reasoning for highly complex tasks. Opus 4.8 remains the right choice for most complex agentic workflows at half the cost. Fable 5 is best when you need both maximum context and maximum reasoning depth simultaneously, or when a task has routinely hit the limits of what Opus can do reliably.
    Claude Fable 5 is priced at $10 per million input tokens and $50 per million output tokens — 2× Opus 4.8 ($5/$25), 3.3× Sonnet 4.6 ($3/$15), and 10× Haiku 4.5 ($1/$5). Prompt caching drops the effective input cost to $1.00/M on cache reads, and the Batch API adds a 50% discount on all tokens for non-real-time workloads. Stacking both discounts makes Fable 5 viable for higher-volume use cases than the base price suggests.
    Claude Fable 5 has a 1-million-token context window — approximately 750,000 words or roughly 1,500 pages of text. This is 5× the context window of Opus 4.8, Sonnet 4.6, and Haiku 4.5 (all 200K). In practice, a 1M context window lets you pass entire codebases, long research corpora, or full document archives in a single API call without chunking or retrieval workarounds. For more on context window mechanics, see our full context window guide.
    Yes. Claude Fable 5 is available through the Anthropic API using the model ID claude-fable-5-20260101 (check the Anthropic documentation for the exact identifier). It supports the same API surface as the rest of the Claude family — streaming, tool use, prompt caching, vision, the Batch API, and MCP server integration. Access requires an Anthropic API account with Fable 5 enabled on your usage tier.
    Fable 5 is available in Claude.ai on the Pro and Team plans. The interface lets you select it from the model picker when starting a conversation. Like Opus, Fable 5 in claude.ai has message limits that reset on a rolling window — it’s designed for individual complex tasks rather than high-volume API workloads. For production-scale usage, the API with the Batch API discount is the more economical path.
    Yes — and Fable 5’s extended thinking is the deepest in the lineup. Where Opus 4.8 supports extended thinking for complex reasoning tasks, Fable 5 uses a more capable reasoning engine designed for tasks that require longer chains of inference, more working memory, and more reliable self-correction. It’s particularly effective on math, logic, long-horizon planning, and tasks where the model needs to hold and manipulate many interdependent concepts simultaneously.
    For most content production — articles, blog posts, social copy, summaries, SEO content — Sonnet 4.6 is the right call. It produces high-quality output at 3.3× less cost than Fable 5, and for typical content lengths (500–3,000 words), the quality difference is minimal. Reach for Fable 5 when you need to synthesize across a very large corpus (e.g., auditing 200+ posts simultaneously), when the content requires deep domain reasoning that benefits from extended thinking, or when the task involves both large-context ingestion and complex output generation in a single pass.
    Three levers in order of impact: (1) Model routing — only use Fable 5 when the task genuinely requires it; route everything else to Opus, Sonnet, or Haiku based on complexity and volume. (2) Prompt caching — structure your system prompt and shared context so it can be cached; cache reads cost $1.00/M instead of $10.00/M on Fable 5. (3) Batch API — submit non-real-time workloads via the Batch API for a flat 50% discount. Stacking all three — routing + caching + batch — can reduce effective per-task costs by 85–95% compared to unoptimized Fable 5 calls.

    More Claude Guides from Tygart Media

    We run Claude in production every day. These are the guides that come from using it, not just writing about it.

    Related on Tygart Media: Claude Fable 5 overview · Fable 5 firsthand · Claude pricing.

  • Claude 4.6 Roadmap: Guide for Technical Founders

    Claude 4.6 Roadmap: Guide for Technical Founders

    Editor’s note (September 2026): this roadmap was written for the Claude 4.6 generation (May 2026) and is preserved as a snapshot — model names, pricing, and standings have moved on since.

    The Technical Founder’s Roadmap to Claude 4.6

    If you are bootstrapping a tech startup in 2026, navigating the LLM ecosystem is no longer about finding the smartest model—it’s about finding the most cost-effective architecture that actually ships code. We have built this bespoke concierge roadmap to guide you through the Tygart Media resources you need right now.

    📍 Stop 1: The Economics of Routing

    Before you write a single line of code, you need to understand your margins. Anthropic recently made a massive move in the B2B space that directly impacts your AWS burn rate. Read this first: Anthropic Slashes Claude 4.6 Haiku API Pricing by 40%

    📍 Stop 2: Validating the Intelligence

    Now that you know Haiku is cheap, you need to verify if Sonnet is smart enough for your core reasoning tasks. See our leaderboard snapshot for where Claude 4.6 stood against GPT-5 in May 2026. Check the stats: Claude 4.6 vs GPT-5: The 2026 Leaderboard

    📍 Stop 3: Shipping the Front-End

    With your architecture chosen, it’s time to build. If you are using React, you must prevent the model from generating “lazy” partial files that break your CI/CD pipelines. Implement this workflow: The Top Claude 4.6 Prompt for React Developers This Week

    📍 Stop 4: The Final Automation

    If you want to see exactly how we implemented Claude 4.6 in a real-world production environment to completely automate our editorial newsroom, we documented the entire architecture in public. Read the case study: How We Automated Our Newsroom Using Claude 4.6

    This roadmap was autonomously generated by the Tygart Media Omni-Brain to connect you with the specific intelligence you need. Check back for future roadmap updates.