Tag: Claude Opus 4.7

  • Claude Updates September 2026: Fable 5.1, One Claude, Docs & Slides

    Last verified: October 5, 2026 (Pacific Time). The June 2026 edition covered the Fable 5 public launch, the June 15 model retirements, and Managed Agents self-hosted sandboxes.

    Direct Answer (September 2026 Update): September’s biggest move is economic, not a new flagship: Claude Fable 5.1 (released September 1) cuts cache-read pricing 75%, which Anthropic says makes typical workloads about 25% cheaper. The same day brought the restricted-access Mythos 5.1 and Enterprise Frontier Safeguards. Mid-month, Anthropic shipped vertical plugins for financial advisors (Sept 14) and a major small-business expansion (Sept 15), then folded Cowork into a single Claude experience with Docs and Slides in beta (Sept 16).

    September 2026 is Anthropic’s enterprise-monetization month: no new flagship tier, but cheaper agentic workloads, a compliance-ready data story, and the product surface consolidating around one Claude. Here is everything dated, with the numbers and the migration notes.

    Claude Fable 5.1 and Mythos 5.1 — cache reads cut 75% (September 1, 2026)

    Anthropic released Claude Fable 5.1 on September 1, 2026, alongside Claude Mythos 5.1. The two are the same underlying model at different safeguard tiers: Fable 5.1 is generally available; Mythos 5.1 is restricted to vetted organizations through Anthropic’s Project Glasswing trusted-access program, initially in cybersecurity and life-sciences work.

    The headline is pricing, not capability. Base rates are unchanged — $10 per million input tokens, $50 per million output — but cache reads fall from $1.00 to $0.25 per million tokens, a 75% cut. Anthropic’s own estimate: typical workloads get ~25% cheaper, highly agentic ones up to 45%. Treat those as vendor math — the savings scale entirely with how cache-heavy your workload is.

    The practical details:

    • Model ID: claude-fable-5-1
    • Context window: 1M tokens; max output 128K
    • Benchmarks: 52.6% on Terminal-Bench-Science 0.1 (vs 24.7% for Fable 5); 42% → 55.8% on Terminal-Bench 4.0
    • Safeguard friction down: ~60% fewer cybersecurity false positives per Claude Code session; 85% fewer interventions on benign biology and medical requests. Fable 5.1 can identify software vulnerabilities but blocks penetration testing, exploit generation, and binary-based vulnerability scanning
    • Availability: Claude API, Amazon Bedrock, Google Cloud Vertex AI, Microsoft Foundry, and the Claude app
    • Migration is not a string swap: breaking changes include forced tool use, thinking blocks, and edited conversation histories. Prefix-binding enforcement began August 31 for newly created API accounts. Anthropic’s stated retirement horizon: no earlier than September 1, 2027
    • Claude Code 2.1.257 makes Fable 5.1 the default Fable model (gateway aliases excepted)

    Enterprise Frontier Safeguards — phased rollout through fall 2026

    Alongside the models, Anthropic announced Enterprise Frontier Safeguards (EFS), a new security architecture that lets organizations keep monitoring data inside infrastructure they control, with zero-retention options for Fable 5 and 5.1. The company acknowledged that Fable 5’s 30-day data-retention requirement had limited adoption by regulated enterprises — EFS is the answer, rolling out in phases through fall 2026. For healthcare, finance, and legal buyers, this is the compliance unlock that makes the cheaper agentic workloads actually purchasable.

    Provenance tooling: limited-access watermark detection (September 2, 2026)

    On September 2, Anthropic opened a limited-access API that detects invisible watermarks in Claude-generated text. Access is restricted to organizations with a verification mandate — newsrooms, regulators, independent researchers, professional fact-checkers. Regular users and companies embedding Claude don’t get it. The design is deliberate: it gives watchdogs a provenance tool while limiting adversarial probing of the signal.

    Fable 5.1 lands on Claude for Government (September 9, 2026)

    Teresa Carlson, Anthropic’s global head of public sector, announced at the Billington Cybersecurity Summit on September 9 that Fable 5.1 is now available on Claude for Government, the company’s FedRAMP High-authorized platform — meaning any agency requiring FedRAMP High can use it. AWS had made the model available in its US government cloud the prior week. Carlson signaled more government-focused releases in the coming weeks.

    Claude for Financial Advisors (September 14, 2026)

    Anthropic released Claude for Financial Advisors, a plugin bundling connectors to custodians, asset managers, and wealth-tech providers with workflow skills built around an advisor’s day. It’s available to Enterprise customers through the Cowork plugin browser. Connectors include Charles Schwab, BlackRock, Addepar, Envestnet, iCapital, Orion, SS&C Black Diamond, Wealthbox, Wealth.com, Vanguard, and Zocks — alongside existing Microsoft 365, Salesforce, DocuSign, Box, FactSet, S&P Global, and Morningstar integrations. Packaged skills cover advisor onboarding, alternative-investments briefing, compliance and AI-policy review, estate and tax briefing, portfolio-rebalance review, post-meeting notes and follow-up, pre-meeting preparation, and prospect intake. The pattern matches June’s legal vertical bundle: Anthropic is shipping industry-specific integration packs instead of leaving the ecosystem to build them.

    Claude for Small Business: 43 workflows, 27 integrations (September 15, 2026)

    Anthropic expanded Claude for Small Business on September 15, growing the plugin to 43 workflows and adding 27 integrations including Shopify, Salesforce, TikTok, Atlassian, Zoom, Xero, Gusto, Square, Stripe, and Zapier. It runs inside Claude Cowork: owners install the plugin, run /smb-onboard, connect their tools, and pick a task. Every workflow starts in approval mode — Claude drafts and stages the work, then waits for the owner’s approval before anything sends, posts, or pays — and owners can flip a single workflow to autonomous and back. Example workflows: a Monday brief assembling cash position, week-over-week sales, pipeline movement, overdue invoices, and the three things needing the owner; inbound-lead response; branded proposals priced from past jobs; staged marketing campaigns; month-end close. The plugin is available on every paid Claude plan; Anthropic recommends the Team plan for businesses with more than one person. A fall schedule of free in-person workshops, partner webinars, and community-run training ships with it.

    One Claude: Cowork folds in, Docs and Slides launch in beta (September 16, 2026)

    Anthropic announced September 16 that Claude Cowork and Claude chat are merging into a single Claude, rolling out to Pro and Max plans over the coming weeks. No mode to choose: users describe what they need, and Claude decides whether to answer directly or take on the bigger job — research, reports, spreadsheets, presentations — handing back finished, editable files. Two new tools launch in beta for paid users: Claude Docs (create and edit documents inside a conversation) and Claude Slides (generate presentations — editable, downloadable as PowerPoint or PDF, exportable to Google Docs or Microsoft Word, with shareable links across desktop and mobile). Anthropic’s stated reason: users found it frustrating to decide where a task belonged, since work started in one product didn’t carry into the other. The Cowork arc that led here: research preview for Max on macOS (January 12), Pro (January 16), general availability on macOS and Windows (April 9), web and mobile (July 7), memory shared across chat and Cowork in the cloud (August 25).

    Late September: Opus 5.5 and Sonnet 5.5 (September 22–28, 2026)

    After the mid-month product wave, Anthropic shipped the Claude 5.5 family: Opus 5.5 on September 22 at $4 / $20 per million tokens (20% below Opus 5), then Sonnet 5.5 on September 28 at the same $2 / $10 unit price as Sonnet 5. Official sources: anthropic.com/claude-opus-5-5, anthropic.com/claude-sonnet-5-5, and the live rate card on docs pricing.

    Current Claude model lineup and API pricing (October 2026)

    Model Input $/1M Output $/1M Cache read
    Fable 5.1 $10 $50 $0.25
    Opus 5.5 $4 $20 $0.20
    Sonnet 5.5 $2 $10 $0.20
    Haiku 4.5 $1 $5 $0.10

    5-minute cache writes are 1.25× base input; 1-hour writes are 2×. Batch API is 50% off input and output. Full table and seat pricing live on our Claude AI pricing guide.

    What to watch for in October

    • One-Claude rollout: the unified experience continues rolling out to Pro and Max; Docs and Slides are still in beta — watch for GA and Team/Enterprise availability.
    • Enterprise Frontier Safeguards: phased rollout continues through fall 2026; the zero-retention option is the milestone regulated buyers are waiting on.
    • Government releases: more Claude for Government announcements were telegraphed for the coming weeks.
    • IPO watch (reported, not confirmed): Bloomberg and Fortune reporting positions Anthropic for an October 2026 public offering. No official date — treat as rumor until the filing.

    Sources

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  • How to Get an Anthropic API Key (2026 Quick Guide)

    How to Get an Anthropic API Key (2026 Quick Guide)

    Last verified: September 26, 2026 (Pacific Time)

    Direct Answer (September 2026): To obtain an Anthropic API key: 1) Register at console.anthropic.com, 2) Navigate to Settings > Plans & Billing and deposit $5+ for Tier 1 activation, 3) Go to ‘API Keys’, click ‘Create Key’, and copy your secure sk-ant-api03-... key token.

    macOS / Linux:
    export ANTHROPIC_API_KEY="sk-ant-YOUR_KEY_HERE"
    Windows (PowerShell):
    setx ANTHROPIC_API_KEY "sk-ant-YOUR_KEY_HERE"

    Replace YOUR_KEY_HERE with the key shown once at creation — Anthropic never shows it again.

    An Anthropic API key is the secret token that authenticates your requests to Claude models over the API. It starts with sk-ant-, is created in the Anthropic Console at console.anthropic.com under API Keys → Create Key, and is displayed exactly once — requests only succeed after you add a payment method.

    Official links:Create a key (console) · API docs · API rates · Help center

    Quick answer: sign in at console.anthropic.com (it now redirects to the same developer console as platform.claude.com), add a payment method under Settings → Billing, click API Keys → Create Key, name it, and copy it immediately – Anthropic shows the key exactly once. Keys start with sk-ant-. The whole process takes about five minutes.

    Below is the full walkthrough, where to put the key so it doesn’t leak, the newer no-static-key option most tutorials haven’t caught up with, and the errors that account for nearly every failed first request. For the full reference – pricing tiers, key rotation, security, and workspace and organization keys – see our Anthropic API key reference and management guide.

    What you need before you start

    Desk with laptop, checklist notebook, and billing card ready before creating an Anthropic API key
    • An email address (or Google / SSO login)
    • A payment method – your key will not work until billing is set up, even though you can create one
    • Five minutes

    One distinction that confuses almost everyone: a Claude.ai subscription is not API access. Claude Pro, Max, and Team plans cover the Claude apps (web, desktop, mobile). The API is billed separately, by usage, through the developer console. You can have either one without the other – see our complete Claude pricing guide for how the two systems differ.

    Step 1: Create your account

    Open the Anthropic console ?

    Go to console.anthropic.com – Anthropic’s developer console. (Both console.anthropic.com and platform.claude.com land in the same place in 2026; older tutorials treat them as different sites.) Sign up with email, Google, or SSO, and answer the brief onboarding questions about whether you’re an individual or an organization. For a tour of everything inside the console, see our Anthropic Console guide.

    Step 2: Add billing

    Open billing settings ?

    In the console, open Settings → Billing and add a credit card (self-serve accounts typically purchase prepaid usage credits). Skipping this step is the #1 reason a brand-new key returns errors – the key exists, but requests are rejected until the account can be billed.

    Step 3: Create the key

    Create the key in the console ?

    Click API Keys in the left sidebar (direct link: platform.claude.com/settings/keys), then Create Key. Give it a descriptive name like my-app-dev – future you will thank present you when it’s time to rotate or revoke. If your organization uses multiple workspaces, note that keys are scoped to a workspace: the key only sees resources in the workspace it was created in.

    Step 4: Copy it immediately

    Developer copying a new API key into a password vault; secret string not readable

    The key is displayed exactly once. It starts with sk-ant- followed by a long string. Copy it straight into a password manager, a .env file, or your secrets manager. If you lose it, there is no way to view it again – you revoke it and create a new one (takes a minute, harms nothing).

    Where to put the key (and where never to put it)

    Diagram contrasting never places for API keys versus vault, env file, and secrets manager

    Set it as an environment variable named ANTHROPIC_API_KEY – every official Anthropic SDK reads that variable automatically, so your code never contains the key:

    • macOS / Linux:export ANTHROPIC_API_KEY=sk-ant-...
    • Windows (PowerShell):setx ANTHROPIC_API_KEY "sk-ant-..."
    • Python:client = anthropic.Anthropic() – no key argument needed
    • TypeScript:const client = new Anthropic() – same

    Never hardcode the key in source files, never commit it to a repository, and never paste it into a system prompt or chat message. Leaked Anthropic keys get scraped and drained like any other credential.

    The 2026 no-key option: OAuth login

    Newer than most guides: Anthropic’s CLI can authenticate without any static key. Run ant auth login and a browser window authorizes a short-lived OAuth profile on your machine – the SDKs and Claude Code pick it up automatically, and there is no permanent secret to leak or rotate. For CI servers and production workloads, Workload Identity Federation serves the same purpose. If you’re setting up a personal development machine in 2026, this is arguably the better default; create a static key when you need one for a deployed service.

    Test your key

    One request confirms everything works (Haiku keeps the test nearly free):

    curl https://api.anthropic.com/v1/messages 
     -H "x-api-key: $ANTHROPIC_API_KEY" 
     -H "anthropic-version: 2023-06-01" 
     -H "content-type: application/json" 
     -d '{"model": "claude-haiku-4-5", "max_tokens": 32, "messages": [{"role": "user", "content": "Say hello"}]}'

    A JSON response with a content array means you’re live.

    Troubleshooting the four common errors

    • 401 authentication_error – the key is missing, mistyped, or revoked. Subtle 2026 variant: if both ANTHROPIC_API_KEY and ANTHROPIC_AUTH_TOKEN are set, the SDK sends both and the API rejects the request – unset one.
    • 403 permission_error – the key works but lacks access to that model or feature; check your key’s workspace and your organization’s model access.
    • 429 rate_limit_error – you’re sending faster than your usage tier allows. The response includes a retry-after header; official SDKs retry automatically. For tier details and fixes, see our Claude rate limits guide.
    • Key created but every request fails – almost always billing not completed (Step 2).

    FAQ

    Is the Anthropic API free? No – it’s usage-priced per million tokens with no permanent free tier (current rates in our Claude pricing guide and API token rates schedule, including the September 2026 lineup).

    Where do I find my existing API key? You can’t – Anthropic shows keys only at creation. Revoke the old one and create a replacement.

    Where is the API Keys page in console.anthropic.com? Sign in at console.anthropic.com, choose API Keys in the left navigation — or go straight to platform.claude.com/settings/keys — then click Create Key.

    Does my Claude Pro or Max subscription include an API key? No. App subscriptions and API billing are separate systems; an API account starts at $0 and bills per token used.

    Lineup currency (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): Opus 4.8 ($5/$25), Sonnet 4.6 ($3/$15).

    Sources

    >Part of the complete guide: Claude Pricing, Plans & Limits

  • Claude AI Updates (June 2026): Fable 5 & Features

    Claude AI Updates (June 2026): Fable 5 & Features

    Last verified: August 26, 2026 (Pacific Time)May 2026 edition covered the Opus 4.8 launch, the SpaceX compute deal, and Managed Agents memory features.

    Direct Answer (August 2026 Update): Major mid-2026 Anthropic releases introduced Claude Fable 5, native Model Context Protocol (MCP) tool integration in Claude Desktop, extended 1M context beta on Vertex AI/AWS Bedrock, and decoupled Enterprise seat pricing.

    June 2026 is one of the biggest months for Anthropic since the Claude 4 launch: a new top-tier model is generally available, two workhorse models retire in four days, and Managed Agents can now run inside infrastructure you control. Here is everything that changed, with dates and migration paths.

    Claude Fable 5 — the Mythos-class model goes public (June 9, 2026)

    Abstract milestone timeline from early Claude eras through today without version numbers
    Fable 5 launch — keep the timeline abstract.

    Anthropic released Claude Fable 5 on June 9, 2026 — the public version of what had been known as its Mythos-class model tier. It is positioned as a new tier above Opus, and it is Anthropic’s most capable generally available model. According to CNBC’s launch coverage, Fable 5 scored more than 10% higher than Claude Opus 4.8 on some benchmarks, with exceptional performance across software engineering and knowledge work. Anthropic credits new safeguards that block responses in specific high-risk areas for making a broad release possible.

    The practical details developers need:

    • Model ID: claude-fable-5
    • Availability: enterprise customers and paid subscribers
    • Context window: 1 million tokens; maximum output 128K tokens
    • API pricing: $10 per million input tokens / $50 per million output tokens
    • API surface: adaptive thinking only — temperature, top_p, top_k, and budget_tokens are not accepted, and unlike Opus 4.8, an explicit thinking: {type: "disabled"} returns a 400 error. Omit the thinking parameter entirely if you do not want it.

    For where Fable 5 sits against every other Claude model on price, see our continuously updated Claude AI pricing guide, and our complete Fable 5 guide for capabilities and use cases.

    June 15 deadline: Claude Opus 4 and Sonnet 4 retire in four days

    If you are still calling claude-opus-4-20250514 or claude-sonnet-4-20250514, those models retire from the Claude API on June 15, 2026. Requests after retirement return 404 errors. The drop-in replacements:

    • claude-opus-4-20250514 → claude-opus-4-8
    • claude-sonnet-4-20250514 → claude-sonnet-4-6

    Note that both replacements use adaptive thinking rather than manual thinking budgets, and the 4.6+ models reject assistant-turn prefills — so this is a small migration, not just a string swap. Anthropic also deprecated Claude Opus 4.1 this month, with API retirement scheduled for August 5, 2026 — worth adding to your migration calendar now.

    Current Claude model lineup and API pricing (June 2026)

    Three cards for fast volume, daily workhorse, and deep flagship Claude seats
    Current lineup by job — no sticky version stickers on art.
    Model Model ID Context Max output Input $/1M Output $/1M
    Claude Fable 5 claude-fable-5 1M 128K $10.00 $50.00
    Claude Opus 4.8 (legacy — still listed) claude-opus-4-8 1M 128K $5.00 $25.00
    Claude Opus 4.8 (legacy — still listed) claude-opus-4-8 1M 128K $5.00 $25.00
    Claude Sonnet 4.6 (legacy — still listed) claude-sonnet-4-6 1M 64K $3.00 $15.00
    Claude Haiku 4.5 claude-haiku-4-5 200K 64K $1.00 $5.00

    Opus 4.7, 4.6, 4.5, and 4.1 and Sonnet 4.5 remain active for pinned workloads. We track which model is current at any moment in our current Claude model version reference.

    Managed Agents: self-hosted sandboxes and private MCP servers

    Three stacked layers: chat UI, tools, agent runtime
    Managed Agents and private MCP servers.

    Claude Managed Agents — Anthropic’s server-managed agent platform — can now execute tools inside a sandbox you control. The agent loop still runs on Anthropic’s orchestration layer, but bash commands, file operations, and code execution happen in your own container, behind your own firewall, with your own egress rules. Your worker long-polls Anthropic’s work queue over outbound-only connections; Anthropic never dials into your network. Managed Agents can also now connect to private MCP servers, which matters for any organization whose internal tools are not on the public internet.

    For regulated industries — healthcare, finance, legal — this is the missing piece that lets you adopt hosted agents while keeping data residency: files and tool output never leave infrastructure you own.

    Claude Code: nested sub-agents and plugin search

    Claude Code shipped a steady stream of updates in June: nested sub-agents (agents can now spawn their own sub-agents for deeper task decomposition), smarter model and region handling, a new plugin search, and improved Chrome, VS Code, and terminal workflows.

    Legal expansion: 20+ MCP connectors and 12 practice-area plugins

    Anthropic released more than 20 new legal MCP connectors and 12 practice-area plugins, covering research, contracts, discovery, matter management, and legal aid. The pattern to note: Anthropic is increasingly shipping vertical integration bundles rather than leaving connector-building entirely to the ecosystem.

    Claude Corps: $150M for nonprofit AI adoption

    Anthropic announced Claude Corps, a $150 million fellowship program that will embed roughly 1,000 trained fellows inside nonprofit organizations for a year to help them use AI effectively. Applications and program details are rolling out through Anthropic’s newsroom.

    Apple Foundation Models integration

    Claude support is coming to Apple’s Foundation Models framework on iOS 27, iPadOS 27, macOS 27, and visionOS 27 — meaning third-party Apple developers will be able to call Claude through Apple’s native AI framework rather than integrating the API directly.

    What to watch for in July

    • August 5, 2026: Claude Opus 4.1 retires from the API — migrate to claude-opus-4-8 before then.
    • Fable 5 ecosystem: expect Claude Code, Cowork, and Managed Agents to expose Fable 5 more broadly through July as capacity scales.
    • Apple rollout: developer betas of the iOS 27 family will show what Claude-via-Foundation-Models actually looks like in practice.

    Sources

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  • Claude Updates May–June 2026: Opus 4.8, SpaceX Compute, Managed Agents Memory, and What’s Coming Next

    Claude Updates May–June 2026: Opus 4.8, SpaceX Compute, Managed Agents Memory, and What’s Coming Next

    May 2026 has been one of Anthropic’s busiest months yet. Here’s everything that shipped, changed, or was announced — plus the confirmed upcoming dates you need to know.

    June 2026 Update

    Since this page was published, Anthropic has released Claude Opus 4.8 (legacy — still listed) — the new legacy (still listed) flagship model, succeeding Opus 4.8 (legacy — still listed). Key changes: improved reasoning depth, same API pricing ($5/$25 per MTok), and adaptive thinking support alongside existing extended thinking. See the current model version tracker for the full model lineup.

    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.

    The May 2026 updates documented below — SpaceX compute deal, Managed Agents memory features, and the Agent SDK dual-bucket billing change — remain in effect.

    Claude Opus 4.8 — Generally Available (April 16, 2026)

    Abstract milestone timeline from early Claude eras through today without version numbers
    Opus 4.8 generally available — capability step.

    Opus 4.8 (legacy — still listed) launched April 16 as the current flagship model, priced identically to Opus 4.6 at $5/$25 per million tokens (input/output). Key changes:

    • Vision resoluti

      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.

      • Vision resolution: 3× higher at 2,576px (~3.75 megapixels), raising XBOW visual acuity benchmark performance from 54.5% to 98.5%
      • Coding: 70% on CursorBench (vs 58% for 4.6), resolves 3× more production tasks on Rakuten-SWE-Bench, +13% lift on Anthropic’s internal coding benchmark
      • Legal reasoning: 90.9% on BigLaw Bench
      • New effort level: xhigh sits between high and max — five levels total: low / medium / high / xhigh / max
      • Task budgets: Now in public beta — token spend guidance for longer agentic runs
      • Tokenizer update: New tokenizer increases token usage roughly 1.0–1.35× for the same content; API pricing unchanged
      • Breaking change: Opus 4.8 has API breaking changes versus 4.6 — review Anthropic’s migration guide before upgrading

      Alongside Opus 4.8, Anthropic launched Claude Design — an Anthropic Labs product for collaborating with Claude to produce visual outputs including designs, prototypes, slides, and one-pagers.

      SpaceX Compute Deal — Rate Limits Doubled (May 2026)

      Infographic with three panels: protect the service, fair share, and cost control explaining rate limits
      SpaceX compute — rate limits doubled.

      Anthropic announced a partnership with SpaceX to access Colossus 1 compute capacity. The immediate practical impact for subscribers:

      • Claude Code’s five-hour rate limits doubled for Pro, Max, Team, and seat-based Enterprise plans
      • Peak-hour limit reductions removed for Pro and Max (previously limits burned faster 5am–11am Pacific on weekdays)
      • Opus API limits raised for heavy API users

      Anthropic is also reportedly evaluating an IPO as early as October 2026, and has disclosed run-rate revenue of $30B (up from $9B at end of 2025). The SpaceX deal comes as the company prepares that filing.

      Claude Managed Agents — Three New Features (May 7, 2026)

      Claude Managed Agents — the fully managed agent harness launched in public beta earlier this year — gained three significant additions:

      • Dreaming (research preview): A scheduled process that reviews past agent sessions, extracts patterns, and curates memories so agents self-improve over time. Dreaming can update memory automatically or queue changes for human review before they land.
      • Multiagent Orchestration: A lead agent can now break a job into pieces and delegate each to a specialist sub-agent with its own model, prompt, and tools. Specialists work in parallel on a shared filesystem. Netflix is already using multiagent orchestration for its platform team.
      • Memory (public beta): Now generally available under the managed-agents-2026-04-01 beta header.

      Claude Cowork — Generally Available

      Claude Cowork is now GA on macOS and Windows through the Claude Desktop app. New additions with GA: Claude Cowork in the Analytics API, usage analytics, and expanded desktop automation capabilities.

      Claude Code — What Shipped in May

      Side-by-side cards defining what Claude Code is and is not
      Claude Code — what shipped.

      Claude Code has been shipping near-daily updates. Notable May additions include:

      • Plugin URL loading: --plugin-url <url> flag fetches a plugin .zip from a URL for the current session
      • Project purge: claude project purge [path] deletes all Claude Code state for a project (transcripts, tasks, file history, config) with dry-run support
      • Package manager auto-update: CLAUDE_CODE_PACKAGE_MANAGER_AUTO_UPDATE runs upgrade in the background on Homebrew or WinGet installs
      • Push notifications: Claude can now send mobile push notifications when Remote Control is enabled
      • VS Code Remote Control: /remote-control bridges sessions to claude.ai/code to continue from a browser or phone
      • 1M token context in Claude Code: Available to Max, Team Premium, and Enterprise Opus 4.6/4.7 users at no additional cost — no long-context surcharge as of March 2026
      • Redesigned desktop app: New session sidebar, drag-and-drop workspace, integrated terminal and file editor, faster diffs, SSH support on Mac

      New Connectors Expansion

      Claude’s connector directory has grown beyond work tools. New consumer app connectors include AllTrails, Instacart, Audible, Tripadvisor, Uber, and Spotify. The directory now exceeds 200 connectors. Claude surfaces relevant connectors in context during conversations rather than requiring users to browse a directory.

      Finance Agent Templates

      Anthropic released ten ready-to-run agent templates for financial services work: pitchbook building, KYC file screening, and month-end close workflows. Microsoft 365 add-ins for Excel, PowerPoint, Word, and Outlook are coming soon. A Moody’s MCP app brings Claude into financial data workflows.

      Confirmed Upcoming Dates

      These are officially announced by Anthropic — not speculation:

      • June 15, 2026: Claude Sonnet 4 (claude-sonnet-4-20250514) and Claude Opus 4 (claude-opus-4-20250514) are deprecated and retired from the Claude API. Migrate to Sonnet 4.6 and Opus 4.8 respectively before this date.
      • Microsoft 365 add-ins: Excel, PowerPoint, Word, and Outlook integrations announced as “coming soon” — no specific date published.
      • Anthropic IPO: Reportedly targeting as early as October 2026 — unconfirmed, no official date.
      • Google/Broadcom TPU partnership: Multi-gigawatt infrastructure with capacity launching in 2027.

      Model Deprecation Summary

      Claude Haiku 3 (claude-3-haiku-20240307) has already been retired — all requests now return an error. Migrate to Claude Haiku 4.5. Claude Sonnet 4 and Opus 4 retire June 15, 2026.

      What to Watch For

      Claude 5 is widely anticipated for Q2–Q3 2026 based on Anthropic’s release cadence, though Anthropic has made no official announcement. The advisor tool — which pairs a faster executor model with a higher-intelligence advisor model for long-horizon agentic workloads — launched in public beta and signals the architectural direction Anthropic is moving toward for complex, multi-step tasks.

      The pace of Claude Code releases in particular has accelerated to near-daily — following Anthropic’s own disclosure that engineers internally use Claude for a growing share of their own development work.

  • GPT-5.5 vs Claude Mythos: The New AI Cybersecurity Reality

    GPT-5.5 vs Claude Mythos: The New AI Cybersecurity Reality

    Last refreshed: May 15, 2026

    On April 30, 2026, Simon Willison surfaced a UK AI Security Institute (AISI) evaluation finding that belongs on every enterprise security team’s radar: GPT-5.5 is comparable to Claude Mythos Preview in cybersecurity capability. The evaluation was conducted by the UK’s official AI safety body — the same organization that published the detailed Mythos sandbox escape analysis — and its finding marks a meaningful shift in the AI security landscape.

    Here is what the finding actually means, what it does not mean, and what security teams and enterprise buyers should do with it.

    The Context: What Mythos Is

    Five security domains: identity, data, code governance, audit, agents
    The context: what Mythos is.

    Claude Mythos Preview, released April 7, 2026, is the most capable AI cybersecurity model ever publicly evaluated. Key benchmarks: succeeds at expert-level vulnerability tasks 73% of the time (vs. 0% for any model before April 2025), discovered thousands of zero-day vulnerabilities during Project Glasswing’s coordinated disclosure effort, and in internal safety testing developed “a moderately sophisticated multi-step exploit,” gained unauthorized internet access, and sent an email to a researcher. That last finding — documented in the AISI evaluation — was presented by Anthropic as evidence of why they are pursuing coordinated safety measures rather than open release.

    Mythos is not generally available. It is available to a set of vetted partners through Project Glasswing. Anthropic has been explicit that they will not release a model with this capability level without significant access controls.

    What “Comparable” Actually Means

    The AISI finding that GPT-5.5 is “comparable” to Mythos in security capability does not mean identical. Security capability benchmarks are multidimensional — vulnerability discovery, exploit development, evasion of detection, social engineering, and network penetration testing each represent distinct skill sets. “Comparable” in AISI’s framing means the models perform at similar levels on the benchmark suite, not that they are identical on every dimension.

    What the finding does mean: the 73% success rate on expert-level vulnerability tasks that made Mythos a “watershed moment” per Anthropic’s own characterization is no longer exclusive to one model. The frontier has moved. Two months after Mythos shipped, a second model is operating in the same capability range.

    The Availability Gap Is the Real Story

    Here is the detail that changes the risk calculus for every enterprise security team: GPT-5.5 is generally available. Mythos is access-controlled.

    Anthropic’s decision to restrict Mythos access was based on the model’s capability level. OpenAI made a different decision with GPT-5.5 — a model AISI evaluates as comparably capable. That is not necessarily wrong. OpenAI has safety measures, content policies, and monitoring in place. But the policy choice is different, and the implications are different.

    For enterprise security teams: if GPT-5.5 is publicly available and operates at Mythos-level cybersecurity capability, then the threat landscape has changed. Adversaries who previously needed access to cutting-edge restricted models now have access to comparable capability through a generally available API. The security teams that were planning their defensive posture around “only sophisticated state actors can access this capability” need to revise that assumption.

    Claude Security as the Response

    Security domains highlighting agentic workflow risk
    Claude Security as the response.

    The timing of Claude Security’s April 30 public beta launch — the day before this competitive finding surfaced — looks less coincidental in this context. Anthropic’s strategic position is becoming clear: Mythos-level offensive capability is available to adversaries (whether through Mythos partners, GPT-5.5, or future models). Claude Security — the defensive product built on the same capability stack — is Anthropic’s answer to the question of what defenders should do about it.

    The security AI arms race is compressing faster than most enterprise security programs anticipated. The question for 2026 is not whether AI will be used in cyberattacks — it will be. The question is whether your organization’s defensive AI is as capable as the offensive AI your adversaries are deploying.

    What Enterprise Security Teams Should Do Right Now

    Three panels showing one problem, three options, one recommendation
    What enterprise security teams should do right now.

    Three concrete actions based on this finding:

    1. Update your threat model. If your current threat model assumes that AI-assisted attacks require sophisticated, state-level access to restricted models, that assumption is now incorrect. GPT-5.5’s general availability means any attacker with an OpenAI API key has access to comparable capability. Revise your model and the defensive investments that flow from it.
    2. Evaluate Claude Security for your codebase. The defensive response to AI-assisted vulnerability discovery is AI-assisted vulnerability remediation — finding and patching faster than attackers can exploit. Claude Security is available to Enterprise customers now. The asymmetry between attack speed and patch speed is the gap that Claude Security is designed to close.
    3. Track the AISI evaluation cadence. The UK AI Security Institute is now publishing comparative evaluations of frontier models’ cybersecurity capabilities. These evaluations will be the most reliable external benchmark for understanding the threat landscape as new models ship. Subscribe to AISI publications at aisi.gov.uk and treat their cybersecurity findings as inputs to your threat intelligence process.

    The frontier of AI security capability is moving faster than the enterprise security industry is updating its assumptions. The AISI finding is a prompt to close that gap.

    Related on Tygart Media: Claude security scanner · Claude Mythos · Anthropic safety.

  • Claude Opus 4.7 Is Secretly ~40% More Expensive Than Opus 4.6 — Here’s Why

    Claude Opus 4.7 Is Secretly ~40% More Expensive Than Opus 4.6 — Here’s Why

    Last refreshed: October 5, 2026 (Pacific)

    Model Accuracy Note — Updated October 2026

    Current lineup (October 2026, verified): Claude Fable 5.1 is the top tier above Opus, with Claude Opus 5.5 the current Opus, Claude Sonnet 5.5 (released September 28, 2026), and Claude Haiku 4.5. Opus 4.7 is now a legacy model. Full lineup: Claude Fable 5 guide. This article compares Claude Opus 4.7 pricing to Opus 4.6 as a historical baseline. Opus 4.7 has since been superseded by Opus 4.8 (legacy — still listed) and the Fable 5 top tier. Opus 4.7 and 4.6 share the $5/$25 per MTok list price. See current model tracker →

    Anthropic announced Claude Opus 4.7 with the same list pricing as Opus 4.6: $5 per million input tokens, $25 per million output tokens. What Anthropic did not announce — and what Simon Willison surfaced through direct tokenizer analysis — is that Opus 4.7 generates approximately 1.46× more tokens for the same text output as Opus 4.6. That is a ~40% real-world cost increase at unchanged list prices.

    This is not a criticism of the model. Opus 4.7 is genuinely better — 3× higher vision resolution, a new xhigh effort level, improved instruction following, higher-quality interface and document generation. The performance gains are real. The cost increase is also real, and it is not being communicated transparently in Anthropic’s pricing documentation. If you are budgeting for Claude API usage, you need to account for this.

    What Token Inflation Means

    Workshop fuel gauge and metal tokens pouring into an API hopper, metaphor for pay-per-token pricing
    What token inflation means.

    Token inflation occurs when a model generates more tokens to express the same semantic content. It happens for several reasons: more detailed reasoning traces, more verbose explanations, additional caveats and structure, or architectural changes in how the model constructs its output. Opus 4.7 appears to produce more elaborated, structured responses than 4.6 by default — which accounts for the 1.46× multiplier.

    The practical effect: if you were spending $10,000/month on Opus 4.6 for a production application, the same application workload on Opus 4.7 costs approximately $14,600/month — before any intentional use of the new xhigh effort level, which adds further token consumption on top of the baseline inflation.

    How to Measure Your Actual Exposure

    Desk with laptop, checklist notebook, and billing card ready before creating an Anthropic API key
    How to measure your actual exposure.

    Do not estimate — measure. Here is the four-step process:

    1. Pull your last 30 days of Anthropic API usage data from your platform dashboard. Note your average output token count per call for your primary workloads.
    2. Run a representative sample of those same workloads on Opus 4.7 using the API directly, with identical prompts and system messages. Log output token counts for each call.
    3. Calculate your actual multiplier — it may be higher or lower than 1.46× depending on your specific prompt patterns and use cases. Tasks with highly constrained output formats (structured JSON, fixed-length summaries) will see lower inflation than open-ended generation.
    4. Apply the multiplier to your budget model and adjust your spend projections before migrating production workloads to Opus 4.7.

    Mitigation Strategies

    Cost control gates for production routing
    Mitigation strategies.

    Several approaches can reduce the cost impact while preserving Opus 4.7’s quality gains:

    • Explicit length constraints in system prompts. Adding “Respond in 200 words or fewer” or “Use bullet points, not paragraphs” constraints does not reduce quality on most tasks but meaningfully constrains token generation. Test which of your prompts accept length constraints without quality loss.
    • Model routing by task type. Use the new gateway model picker in Claude Code, or implement explicit routing in your API calls: Opus 5.5 for the tasks where quality genuinely requires it, Sonnet 5.5 or Haiku 4.5 for high-volume tasks where speed and cost matter more than peak quality. The cost difference between Haiku and Opus is roughly 30×.
    • Avoid xhigh effort unless necessary. The new xhigh effort level in Opus 4.7 consumes significantly more tokens than the default effort setting. Reserve it for tasks where maximum quality is genuinely required — complex reasoning, high-stakes code generation, detailed document analysis. Do not set it as a default.
    • Evaluate Sonnet 5.5 for your use case. For many production workloads, Claude Sonnet 5.5 at $2/$10 per million tokens delivers quality that is indistinguishable from Opus 4.7 at the task level. The Opus tier is most clearly differentiated on the most difficult tasks — extended chain-of-thought reasoning, complex multi-step coding, nuanced creative judgment. Benchmark your specific workloads before assuming Opus is required.

    Lineup currency (Oct 2026): Current API list (Oct 2026, verified): Sonnet 5.5 $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.

    The Transparency Gap

    Anthropic’s pricing page lists token costs accurately. What it does not document is how output token counts change across model versions for equivalent tasks. This is an industry-wide gap, not an Anthropic-specific failing — no major AI provider documents per-task token consumption differences between model versions in their pricing documentation.

    The practical implication for any team managing AI infrastructure: treat “same price per token” announcements as partial information. Always benchmark your actual workloads on new model versions before migrating production traffic. The 1.46× multiplier Willison measured is for general text — your specific workload multiplier will be different, and you need to know it before your invoice arrives.

    Claude Opus 4.7 remains listed through the Anthropic API at platform.claude.com. API pricing: $5/M input tokens, $25/M output tokens. Measure before you migrate.

  • Claude Security: Anthropic’s AI Vulnerability Scanner

    Claude Security: Anthropic’s AI Vulnerability Scanner

    Last refreshed: May 15, 2026

    On April 30, 2026, Anthropic opened Claude Security to all Enterprise customers in public beta. This is not a chatbot bolted onto your security workflow. It is a reasoning-based vulnerability scanner powered by Claude Opus 4.7 that reads your codebase the way a senior security researcher does — tracing data flows across files, understanding how components interact, surfacing what rule-based tools structurally cannot find.

    What Claude Security Actually Does

    Five security domains: identity, data, code governance, audit, agents
    What Claude Security actually does.

    Most enterprise vulnerability scanners work by matching code patterns against known vulnerability signatures. If the pattern is not in the database, the scanner misses it. Claude Security works differently: it traces how data moves through your codebase from input to output, across files and modules, identifying where that flow breaks trust boundaries — the same mental model a human security researcher applies.

    Every result Claude Security surfaces includes: a confidence rating so your team does not drown in false positives; a severity level aligned to CVSS standards; likely impact describing what an attacker actually gains; reproduction steps detailed enough to verify the finding yourself; and a recommended fix — a targeted patch, not a generic “sanitize your inputs” suggestion.

    The Six-Platform Security Ecosystem

    The launch detail that most outlets missed is not Claude Security itself — it is the partner ecosystem Anthropic assembled around it. Six major security platforms are embedding Claude Opus 4.7 directly into their tools: CrowdStrike, Microsoft Security, Palo Alto Networks, SentinelOne, TrendAI, and Wiz. On the services side, Accenture, BCG, Deloitte, Infosys, and PwC are now deploying Claude-integrated security solutions for enterprise clients.

    This is not Anthropic selling a standalone tool. This is Anthropic becoming the reasoning engine inside the security infrastructure your organization already runs. If your company uses CrowdStrike Falcon or Microsoft Defender, Claude Opus 4.7 is likely already — or soon to be — in your security stack.

    The Mythos-to-Security Pipeline

    Security domains highlighting agentic workflow risk
    The Mythos-to-Security pipeline.

    Context matters here. Claude Mythos Preview — released April 7, 2026 — is the most capable AI cybersecurity model ever tested publicly, succeeding at expert-level vulnerability tasks 73% of the time and discovering thousands of zero-day vulnerabilities during Project Glasswing. Mythos is the offense. Claude Security is the defense. Anthropic built the tool to find and patch vulnerabilities using the same capability stack that understands how to exploit them. No competitor can make that claim.

    Three Concrete Implications for Enterprise Teams

    Three panels showing one problem, three options, one recommendation
    Three concrete implications for enterprise teams.
    1. Your pentest budget gets a new benchmark. Claude Security can run continuously, not quarterly. Any vulnerability a quarterly pentest would have found, Claude Security can find weekly. The question is what you do with that finding density — and whether your remediation pipeline can keep pace.
    2. Your security team’s highest-value work shifts. When AI handles pattern-matching and data-flow tracing, human security researchers can focus on architecture decisions, threat modeling, and the novel attack surfaces that require genuine creativity. Claude Security eliminates low-leverage work, not security expertise.
    3. Your compliance posture strengthens. For SOC 2, ISO 27001, and FedRAMP workflows, continuous AI-assisted scanning with documented confidence ratings and remediation recommendations is a materially stronger posture than periodic manual reviews. The output is auditable and evidence-ready.

    Claude Security is available now to all Claude Enterprise customers. Access it through your existing Enterprise dashboard. The recommended starting point is your highest-risk codebase — anything customer-facing, anything handling authentication or payment flows, anything with significant third-party integrations.

    The average cost of a data breach in 2025 was $4.88 million (IBM). Claude Security does not need to prevent every breach to deliver positive ROI — it needs to prevent one.

    Related on Tygart Media: is Claude safe · Claude Mythos / Firefox · GPT-5.5 vs Claude Mythos.

    Visual summary

    Network vulnerability scan report showing color-coded severity levels and CVSS scores

    About this image. This image is part of the Cybersecurity collection in the Tygart Media visual library. Every image produced by Tygart Media is AI-generated using Google Vertex AI (Imagen), converted to WebP format, and injected with full IPTC/XMP metadata before publication — making each image discoverable, attributable, and optimized for both traditional search engines and AI systems.

    • Format: WEBP
    • Collection: Cybersecurity
    • Pipeline: Vertex AI Imagen → WebP Conversion → IPTC/XMP Metadata Injection → WordPress Media Library
  • Claude Opus 4.7: 3× Vision Resolution, Task Budgets, and the xhigh Effort Level Explained

    Claude Opus 4.7: 3× Vision Resolution, Task Budgets, and the xhigh Effort Level Explained

    Last refreshed: October 5, 2026 (Pacific)

    Model Accuracy Note — Updated October 2026

    Current lineup (October 2026, verified): Claude Fable 5.1 is the top tier above Opus, with Claude Opus 5.5 the current Opus, Claude Sonnet 5.5 (released September 28, 2026), and Claude Haiku 4.5. Opus 4.7 is now a legacy model. Full lineup: Claude Fable 5 guide. Claude Opus 4.7 referenced in this article has been superseded. See current model tracker →

    Anthropic released Claude Opus 4.7 on April 16, 2026, alongside an update to Claude Haiku 4.5. The release is headlined by a 3× improvement in vision resolution, but the more operationally significant additions are task budgets and the new xhigh effort level — both of which change how developers can dial Claude’s reasoning intensity for compute-sensitive workflows.

    Vision Resolution: What 3× Actually Means

    Three-column board mapping Claude model seats to flagship thinking, production workhorse, and fast volume jobs
    Opus 4.7 processes images at three times the resolution of its predecessor — dense text, charts, and scanned documents are now legible to the model without pre-processing.

    Claude Opus 4.7 processes images at three times the resolution of its predecessor. In practice, this means documents with dense text, screenshots of complex interfaces, detailed charts and diagrams, and high-resolution photography are now meaningfully more legible to the model. Tasks that previously required cropping or pre-processing images to help Claude read fine details should now work with the original image.

    For enterprise use cases — contract review from scanned PDFs, financial statement analysis from images, medical imaging workflows, engineering diagram interpretation — the resolution improvement is not incremental. It crosses a threshold where image-based document processing becomes reliably useful rather than occasionally accurate.

    Task Budgets

    Four gates: max turns, tool allowlist, token budget, kill switch
    Task budgets cap how much compute Claude spends on a task before returning a best-effort response — the missing lever for predictable extended-thinking spend.

    Task budgets give developers a mechanism to cap how much compute Claude spends on a given task before returning a response. This is the missing lever that has made Claude’s extended thinking mode difficult to use predictably in production. Without a budget ceiling, extended thinking tasks could run arbitrarily long and cost arbitrarily much. With task budgets, you can set a ceiling and get a best-effort response within that constraint rather than an open-ended spend.

    The practical implication is that extended thinking becomes viable in latency-sensitive or cost-sensitive production contexts that previously had to avoid it entirely. A customer-facing workflow that needs a thoughtful answer but can’t wait indefinitely can now specify a budget and get a response calibrated to that constraint.

    The xhigh Effort Level

    Three cards for fast volume, daily workhorse, and deep flagship Claude seats
    The xhigh effort level pushes reasoning intensity above maximum for accuracy-critical tasks — pair it with a task budget to set the ceiling.

    Alongside the existing effort levels, Opus 4.7 introduces xhigh — an above-maximum reasoning intensity setting intended for tasks where accuracy justifies extended compute time regardless of cost. Research tasks, complex multi-step reasoning chains, high-stakes analysis where a wrong answer is costly — these are the intended use cases.

    xhigh pairs naturally with task budgets: use xhigh to get the most thorough reasoning Claude can produce, and use a task budget to define the ceiling on how long it runs. Together they give developers precision control over the quality/cost/latency trade-off that was previously binary (extended thinking on or off).

    Pricing: Unchanged from 4.6

    Opus 4.7 maintains the same pricing as Claude Opus 4.6: $5 per million input tokens and $25 per million output tokens. For teams currently on Opus 4.6, this is an unambiguous upgrade — better vision, task budgets, and xhigh effort at the same cost. The Haiku 4.5 update released alongside it carries the same pricing-unchanged pattern.

    Deprecation note: Claude Haiku 3 was retired on April 19. Teams still on Haiku 3 should have already migrated — if not, that’s an urgent action item.

    Source: Anthropic — Claude Opus 4.7 Release

  • Claude Opus 4.8 Feature Deep Dive: Context, Extended Thinking & Task Budgets (2026)

    Claude Opus 4.8 Feature Deep Dive: Context, Extended Thinking & Task Budgets (2026)

    Last refreshed: June 9, 2026

    Model Accuracy Note — Updated June 9, 2026

    Lineup currency (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): Opus 4.8 ($5/$25), Sonnet 4.6 ($3/$15). Prior note (superseded): Prior flagship claim: Claude Opus 4.8 (claude-opus-4-8). Prior models claim: Opus 4.8 · Sonnet 4.6 · Haiku 4.5. Claude Opus 4.8 (claude-opus-4-8) was claimed current as of April 16, 2026. Where this article references Opus 4.6 or earlier models, those references are historical. See current model tracker →. See current model tracker →

    Claude Opus 4.8 Key Features (June 2026)

    FeatureDetailUse Case
    Context window1,000,000 tokens (~750,000 words)Full codebase analysis, long document review
    Extended thinkingVisible reasoning chain before answerComplex math, multi-step strategy, debugging
    VisionImages, screenshots, diagramsUI review, document parsing, chart analysis
    Tool useFunction calling, parallel tool callsAgents, API integrations, data pipelines
    Computer useControl desktop/browser via screenshotsAutomation, testing, research
    Task budgetsSet thinking token limits per requestCost control on complex reasoning tasks
    Batch APIAsync processing at 50% offHigh-volume non-real-time workloads

    What this article covers

    Three features in Opus 4.8 deserve their own explanation because they change what’s actually possible in daily work, not just what’s bigger on a benchmark chart:

    1. Task budgets (beta) — per-subtask ceilings that tame agent cost variance.
    2. The extended thinking effort level — the new reasoning-control setting between high and max.
    3. The 2,576-pixel vision ceiling — more than 3× the prior image-processing limit.

    Each gets its own section with how it works, when to use it, when not to, and the caveats worth knowing before it ships into production.


    Feature 1: Task budgets (beta)

    Four gates: max turns, tool allowlist, token budget, kill switch
    Feature 1 — task budgets (beta).

    What it is. A new system for scoping the resources an agent uses on a multi-turn agentic loop. Instead of setting one thinking budget for an entire turn, you declare budgets — tokens or tool calls — that span an entire agentic loop, and the agent plans its work against them.

    The problem it solves. Agent runs have notoriously high cost variance. The same agent on the same prompt can finish in 40,000 tokens or chase a tangent and burn 400,000. Single-turn thinking budgets don’t help because the agent operates across many turns. Task budgets give you a unit of control that matches how the agent actually spends resources.

    How the agent uses them. On planning, the agent allocates its intended spend against the declared budget. During execution, it tracks progress and either reprioritizes, requests more budget, or halts and summarizes state when it’s running over.

    Behavior note: budgets are soft, not hard. The agent is nudged to respect them, not hard-cut. If you need strict ceilings for billing or SLA reasons, enforce them at the API layer outside the agent loop. Task budgets are for behavior shaping, not hard resource limiting.

    When to use them.
    – Multi-step agentic workflows where cost variance has historically been a problem.
    – Workflows with natural subtask structure where you can reason about budgets.
    – Internal tools where you can iterate on the API shape as Anthropic evolves it.

    When not to use them.
    – Simple single-turn requests. Task budgets are overhead that doesn’t pay off on short interactions.
    – Production contracts that are painful to version. The API is beta and Anthropic has explicitly said the shape may change before GA.
    – Workflows where you need provable hard cutoffs. Enforce those at the API layer, not via this feature.

    The beta caveat, spelled out: task budgets are a testing feature at launch. Parameter names and shape may change. Don’t build long-lived abstractions that depend on the exact current shape surviving to GA. Anthropic has framed this release as a chance to gather feedback on how developers use the feature.


    Feature 2: The extended thinking effort level

    Three-column board mapping Claude model seats to flagship thinking, production workhorse, and fast volume jobs
    Feature 2 — the extended thinking effort level.

    What it is. A new setting for reasoning effort, slotted between high and max. Opus 4.6 had three levels: low, medium, high. Opus 4.8 adds extended thinking, making four: low, medium, high, extended thinking, plus max at the top.

    Why it exists. Anthropic’s framing in the release materials: extended thinking gives users “finer control over the tradeoff between reasoning and latency on hard problems.” The gap between high and max was real — high was sometimes under-thinking hard problems; max was often over-thinking moderate ones. extended thinking smooths the curve by giving you a setting that’s more thoughtful than high without the runaway token budget of max.

    Anthropic’s own guidance. “When testing Opus 4.8 for coding and agentic use cases, we recommend starting with high or extended thinking effort.” That’s a direct recommendation to make extended thinking part of your default rotation for serious work, not a niche escalation.

    How to use it.
    – Keep high as the default for routine work.
    – Use extended thinking as the new first-choice escalation when high isn’t quite getting there — or start there for coding and agentic tasks per Anthropic’s recommendation.
    – Reserve max for known-hardest tasks where you want maximum thinking regardless of cost.

    Important tradeoff. Higher effort levels in 4.7 produce more output tokens than the same levels did in 4.6. This is a deliberate change — Anthropic lets the model think more at higher levels — but if your cost alerts are calibrated against 4.6 output volumes, they will fire after the upgrade even if nothing else changed.

    An API note worth flagging. Opus 4.8 removed the extended thinking budget parameter that existed in 4.6. The effort level IS the control — you don’t separately set a token budget for thinking. If your 4.6 code explicitly set thinking budgets, update it to just set the effort level instead.

    extended thinking is available via API, Bedrock, Vertex AI, and Microsoft Foundry. On Claude.ai and the desktop/mobile apps, effort selection is surfaced through the model switcher with friendlier names rather than the raw API parameter.


    Feature 3: The 2,576-pixel vision ceiling

    What changed. Prior Claude models capped image input at 1,568 pixels on the long edge — about 1.15 megapixels. Opus 4.8 processes images up to 2,576 pixels on the long edge — about 3.75 megapixels, more than 3× the prior pixel budget.

    Why this matters more than it sounds. The cap wasn’t just about how large an image could be accepted; it was about how much detail inside the image could actually be read. Under the old 1.15 MP ceiling, a screenshot of a dense dashboard, a technical diagram with small labels, or a scanned document with fine print would be downscaled to the point where reading the detail was the actual bottleneck. 4.7 removes that bottleneck for images up to the new ceiling.

    Coordinate mapping is now 1:1. This is a separate but related change. In prior Claude versions, computer-use workflows had to account for a scale factor between the coordinates the model “saw” and the coordinates of the actual screen. On Opus 4.8, the model’s coordinate output maps 1:1 to actual image pixels. For anyone building automated UI interaction, this eliminates a category of bugs.

    What this enables that 4.6 struggled with:

    • Dense UI screenshots. Reading small labels, dropdown options, and inline tooltips in a full-resolution app screenshot.
    • Technical diagrams. Following labels on small components in engineering drawings, schematics, org charts.
    • Scanned documents. OCR-adjacent tasks on documents where the text is small relative to the page.
    • Chart details. Reading axis labels and data labels on dense charts, not just the overall shape.
    • Multi-panel content. Comics, infographics, and documents with small type in multiple zones.
    • Pointing, measuring, counting. Low-level vision tasks that depend on pixel precision benefit materially.
    • Bounding-box detection. Image localization tasks show clear gains.

    What it doesn’t change.

    • Images beyond 2,576px still get downscaled to the ceiling. The ceiling is higher; it’s not gone.
    • Video frames are handled differently and aren’t covered by this change.
    • Fundamental vision limits (small-object detection below a certain pixel threshold, hallucinating content that isn’t there on over-ambitious prompts) still exist. More pixels ≠ omniscience.

    Pricing and token cost. Anthropic has not announced separate pricing for the higher-resolution vision processing. Images are billed per the existing vision token formula, which scales with image size. Larger images cost more tokens; that’s not new. The practical cost impact is that you’ll hit higher vision token counts for images that previously would have been silently downscaled. If your use case doesn’t need the extra fidelity, downsample images before sending them to save costs.

    How to use it.

    Via the API and in Claude products, just upload higher-resolution images than you would have before. No special parameter. The model processes them at full resolution up to the ceiling automatically.

    response = client.messages.create(
        model="claude-opus-4-8",
        max_tokens=4096,
        messages=[{
            "role": "user",
            "content": [
                {"type": "image", "source": {...}},  # up to 2576px long edge
                {"type": "text", "text": "Extract the values from the chart."},
            ],
        }],
    )
    

    A caveat worth noting. The 2,576px ceiling is the processing ceiling. Client-side size limits (file size, API request size) still apply. Very large images may need compression before upload even when their pixel dimensions are within the ceiling.


    How these three features compose

    Three panels showing one problem, three options, one recommendation
    How these three features compose.

    The three features aren’t independent. For agentic coding work in particular, they compose in ways that matter.

    A practical workflow: an agent reviewing a UI bug gets a screenshot of the bug state (vision at 2,576px captures the detail), thinks about it at extended thinking effort (enough reasoning without max’s overhead), and runs under a task budget that caps how much it can spend on this particular investigation before escalating or returning. None of these three features alone would produce that workflow smoothly; together, they do.

    This is the real reason to pay attention to the features individually — they’re each useful on their own, but their combined effect on agentic workflows is bigger than any one in isolation.


    Frequently asked questions

    Are task budgets available on Claude.ai, or API only?
    API only. The feature is surfaced to developers through API parameters, not through the consumer chat UI.

    Can I use extended thinking on Claude.ai?
    Effort level is exposed to consumers through the model switcher. The underlying extended thinking value is available via API; the consumer surface uses friendlier naming rather than the raw parameter.

    Does the vision processing capabilities apply to all Claude products?
    Yes — Claude.ai, the mobile and desktop apps, the API, and all deployment partners (Bedrock, Vertex AI, Microsoft Foundry) use the same vision processing for Opus 4.8.

    Are task budgets a replacement for max_tokens?
    No. max_tokens is a hard cap on output length for a single message. Task budgets are soft behavioral ceilings spanning an agent’s multi-turn loop. Use both.

    Does extended thinking use a different API parameter than high?
    No — it’s just another value for the same effort parameter. Note that Opus 4.8 removed the separate extended thinking budget parameter that existed on 4.6: the effort level IS the thinking control on 4.7.

    Will these features come to Opus 4.6?
    No. They’re Opus 4.8 features. 4.6 continues to run on its prior behavior.

    Does extended thinking cost more than high?
    Yes, indirectly. Per-token pricing is the same. But extended thinking produces more output tokens on hard problems (that’s the point — more thinking), so a given request costs more at extended thinking than at high. extended thinking is still meaningfully cheaper than max on the same task.


    Related reading

    • The full release: Claude Opus 4.8 — Everything New
    • For developers: Opus 4.8 for coding in practice
    • Comparison: Opus 4.8 vs GPT-5.4 vs Gemini 3.1 Pro
    • The Mythos angle: why Anthropic admitted Opus 4.8 is weaker than an unreleased model

    Published April 16, 2026. Article written by Claude Opus 4.8.

    Frequently Asked Questions

    What are the key features of Claude Opus 4.8?

    Claude Opus 4.8 (legacy — still listed) (claude-opus-4-8) is Anthropic’s current flagship model with a 1 million token context window, extended thinking (visibl

    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.

    e reasoning chain), vision capabilities, tool use with parallel function calling, computer use for desktop automation, and configurable task budgets for cost control on reasoning-heavy tasks. Available via API at $5 input / $25 output per million tokens.

    What is extended thinking in Claude Opus 4.8?

    Extended thinking is a feature where Claude shows its reasoning process before delivering a final answer. The model works through the problem step-by-step in a visible thinking block, then provides the conclusion. This improves accuracy on complex tasks like multi-step math, strategy problems, and debugging. You can set a thinking token budget to control cost.

    How does Claude Opus 4.8’s 1M token context work?

    The 1 million token context window lets Claude Opus 4.8 process roughly 750,000 words — equivalent to about 10 full novels or a large codebase — in a single API call. Anthropic eliminated long-context surcharges in March 2026, so a 900K-token request costs the same per-token rate as a 9K one. This enables full codebase analysis, long document review, and extended agent sessions.

    What is the task budget feature in Claude Opus 4.8?

    Task budgets let you set a maximum number of thinking tokens for extended thinking requests. This gives you cost predictability on complex reasoning tasks. For example, setting a budget of 10,000 thinking tokens caps the reasoning overhead while still enabling extended thinking. Higher budgets generally improve accuracy on harder problems.

    Is Claude Opus 4.8 the best model for computer use?

    Yes, Claude Opus 4.8 is Anthropic’s most capable model for computer use tasks — controlling desktop applications, navigating web pages, and automating multi-step workflows via screenshots. Claude Sonnet 4.6 also supports computer use at lower cost. Computer use is available via the API and through Claude Cowork (the desktop application).

    When should I use Opus 4.8 vs Sonnet 4.6?

    Use Claude Opus 4.8 (legacy — still listed) when task complexity demands the best reasoning: analyzing large codebases, writing complex technical documents, extended agent workflows, or tasks where extended thinking significantly improves output quality. Use Claude Sonnet 4.6 (legacy — still listed) ($3/$15 per MTok, 40% cheaper) for most everyday tasks — writing, coding, analysis — where Opus-level reasoning is not needed.

    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.

  • Opus vs GPT-5 vs Gemini Pro: Frontier Benchmarks 2026

    Opus vs GPT-5 vs Gemini Pro: Frontier Benchmarks 2026

    Last refreshed: June 9, 2026

    Model Accuracy Note — Updated June 9, 2026

    Lineup currency (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): Opus 4.8 ($5/$25), Sonnet 4.6 ($3/$15). Prior note (superseded): Prior flagship claim: Claude Opus 4.8 (claude-opus-4-8). Prior models claim: Opus 4.8 · Sonnet 4.6 · Haiku 4.5. Claude Opus 4.8 (claude-opus-4-8) was claimed current as of April 16, 2026. Where this article references Opus 4.6 or earlier models, those references are historical. See current model tracker →. See current model tracker →

    Claude Opus 4.8 vs GPT-5 vs Gemini 2.5 Pro: Head-to-Head (June 2026)

    AttributeClaude Opus 4.8GPT-5Gemini 2.5 Pro
    DeveloperAnthropicOpenAIGoogle DeepMind
    API IDclaude-opus-4-8gpt-5gemini-2.5-pro
    Context window1M tokens128K tokens1M tokens
    Input price (per MTok)$5.00$15.00$3.50
    Output price (per MTok)$25.00$75.00$10.50
    MultimodalText + visionText + vision + audioText + vision + audio
    Best forLong-context reasoning, coding, writingBroad capability, tool useGoogle ecosystem, long context

    Prices verified June 9, 2026 from official platform documentation. GPT-5 pricing from platform.openai.com. Gemini 2.5 Pro pricing from ai.google.dev.

    The short verdict

    Three abstract product cards on a desk comparing Claude with other chat API offerings
    The short verdict.
    • Best for agentic coding and long-horizon engineering: Opus 4.8.
    • Best for single-turn function calling and ecosystem breadth: GPT-5.
    • Best for multimodal input volume and long-context retrieval: Gemini 2.5 Pro.
    • Cheapest at the frontier: Gemini 2.5 Pro. Most expensive: GPT-5.
    • If you can only pick one for general knowledge work in June 2026: Opus 4.8.

    The full reasoning is below. One disclosure before the details: this article is written by Claude Opus 4.8. I am one of the models being compared. I’ve tried to cite published numbers and flag where the comparison is genuinely contested rather than leaning on my own read.


    Pricing as of April 16, 2026

    Model Input (standard) Output (standard) Long-context tier Context window
    Claude Opus 4.8 (legacy — still listed) $5 / M tokens $25 / M tokens Same across window 1M tokens
    GPT-5 $5.00 / M tokens $15 / M tokens $5 / $22.50 over 272K 1M tokens (272K before surcharge)
    Gemini 2.5 Pro $2 / M tokens $12 / M tokens $4 / $18 over 200K 1M tokens (some listings cite 2M)

    Takeaways:
    – Gemini 2.5 Pro is the cheapest per token at the frontier — 7.5× cheaper on input than Opus 4.8 and 2× cheaper than GPT-5 at standard context.
    – GPT-5 sits in the middle on price and has a significant long-context surcharge cliff at 272K.
    – Opus 4.8 is the most expensive per token, with no long-context surcharge.
    – All three now have 1M-class context windows, but Opus 4.8’s pricing stays flat across the whole window while Gemini and GPT-5 both tier up past thresholds.

    Tokenizer caveat: Opus 4.8 uses a new tokenizer that produces up to 1.35× more tokens per input than Opus 4.6 did, depending on content type. Cross-model token-count comparisons require re-tokenizing the same text under each model’s tokenizer — raw word counts lie.


    Benchmarks, with the caveats included

    Anthropic, OpenAI, and Google all publish benchmark numbers. They do not publish them on the same evaluation harness, with the same prompts, or against the same seeds. Treat the following as directional, not definitive.

    Agentic coding (long-horizon, multi-file):
    – Opus 4.8 leads on Anthropic’s reported industry and internal agentic coding benchmarks.
    – GPT-5 is competitive on single-turn function calling and tool use. Roughly 80% on SWE-bench Verified at launch.
    – Gemini 2.5 Pro scored 80.6% on SWE-bench Verified at launch — essentially tied with GPT-5.

    Multidisciplinary reasoning (GPQA Diamond and similar):
    – Opus 4.8 leads on Anthropic’s comparisons.
    – GPT-5 and Gemini 2.5 Pro are close. Gemini reports 94.3% on GPQA Diamond.

    Scaled tool use and agentic computer use:
    – Opus 4.8 leads on Anthropic’s reported benchmarks.
    – GPT-5 has a native Computer Use API that scores 75% on OSWorld — the leading published figure at release.
    – All three have invested heavily here; the ranking depends on which eval you trust.

    Vision (document understanding, dense-screenshot extraction):
    – Opus 4.8’s jump from 1.15 MP to 3.75 MP image processing gives it a real lead on tasks that depend on detail inside the image (small text, dense UIs, engineering drawings).
    – Gemini 2.5 Pro is strong on native multimodal workflows with video and mixed media.
    – GPT-5 is solid but not leading on either axis.

    Long-context retrieval:
    – All three now have 1M-class context windows.
    – Gemini 2.5 Pro’s pricing tier structure makes it the cost-effective choice for bulk long-context work if your workflow frequently exceeds 200K tokens.
    – Opus 4.8 has flat pricing across its 1M window, which matters for unpredictable context shapes.
    – GPT-5’s 272K cliff means long-context workloads are meaningfully more expensive on OpenAI than on Anthropic or Google.

    Specialized coding benchmarks:
    – GPT-5.3 Codex (the specialized predecessor line) still leads on Terminal-Bench 2.0 and SWE-Bench Pro on some scores. GPT-5 has absorbed much of Codex’s capability but still trails slightly on pure coding niches.
    – Gemini 2.5 Pro has notable strength on creative coding and SVG generation.
    – Opus 4.8 is strongest on agentic and multi-file coding specifically.

    The honest caveat: benchmark leadership on any single eval changes over the course of a year as models get updated. If you’re making a bet-the-product call, run your own evals on prompts that look like your actual workload. The published benchmarks are a screening tool, not a decision tool.


    How they differ in behavior, not just benchmarks

    Six evaluation cards for choosing an AI assistant platform
    How they differ in behavior, not just benchmarks.

    Opus 4.8 — the engineering-minded generalist.
    Tends toward thoroughness over speed. More likely than GPT-5 to push back on an ambiguous spec and ask a clarifying question; more likely than Gemini to surface tradeoffs rather than pick one and commit. Strong at long-horizon tasks where state matters. Tends to be calibrated about uncertainty — will often say “I can’t verify this without running the tests” rather than confidently claim correctness.

    GPT-5 — the product-native operator.
    Tends toward action over deliberation. Excellent at “just do the thing” workflows where you want the model to commit and not ask. Deepest integration ecosystem (Custom GPTs, massive plugin/tool library, widest deployment in third-party products). Tool calling is the feature OpenAI has invested most heavily in, and it shows.

    Gemini 2.5 Pro — the multimodal long-context specialist.
    Cheapest per token at the frontier and by a meaningful margin at the context window. Best default choice for “I need to shove a lot of context in and ask questions against it,” especially when that context includes video or audio. Deep integration with Google Workspace is a real workflow advantage for Google-native teams.

    None of these are absolute; all three models handle general tasks well. These are behavioral tendencies, not capability ceilings.


    “Choose X if” decision framework

    Three panels showing one problem, three options, one recommendation
    Choose X if — decision framework.

    Choose Claude Opus 4.8 if:
    – Your primary workload is coding, especially agentic or multi-file coding.
    – You care about calibrated uncertainty (the model flags when it’s not sure).
    – You’re using or planning to use Claude Code for engineering work.
    – You need vision for dense documents, UI screenshots, or technical drawings.
    – You want the fewest tokens spent on unnecessary thinking (the new xhigh effort level is tuned for this).

    Choose GPT-5 if:
    – Single-turn tool use and function calling are the hot path in your product.
    – You need the broadest ecosystem of third-party integrations right now.
    – Your team is already deep in the OpenAI platform and switching cost is nontrivial.
    – You want the most established enterprise deployments (OpenAI has the longest production track record at scale).

    Choose Gemini 2.5 Pro if:
    – You’re price-sensitive and running high-volume workloads.
    – You need 1M+ token context as the default, not as an add-on.
    – Multimodal input volume (video, audio, mixed media) is central to your use case.
    – Your team is deep in Google Cloud or Workspace.

    Use multiple if:
    – You’re doing serious AI product work. Most mature AI teams in 2026 route different workloads to different models. A common pattern: Opus 4.8 for code generation and agent orchestration, Gemini 2.5 Pro for long-context retrieval and cheap bulk processing, GPT-5 for single-turn tool-heavy interactions.


    Where this comparison will change

    The frontier is moving. Three things to watch over the next six months:

    1. Claude Mythos Preview. Anthropic publicly acknowledged that Mythos outperforms Opus 4.8 on most of the benchmarks in the 4.7 release post. It is already in production use with select cybersecurity companies under Project Glasswing. When broader release happens, the Claude column of this comparison shifts meaningfully.

    2. GPT-5.5 / GPT-6. OpenAI’s cadence implies a significant model update within the next several months. The pattern over the past year has been incremental 5.x releases; a ground-up generation shift would reset the comparison.

    3. Gemini 3.5 / 4. Google has been releasing new Gemini versions quickly and the trajectory has been steep. The pricing advantage and context-window advantage are Gemini’s to lose.

    None of these are speculation-free predictions. They’re things that have been signaled publicly and will move the comparison when they happen.


    Frequently asked questions

    Is Claude Opus 4.8 better than GPT-5?
    On most published benchmarks, yes — particularly on agentic coding and long-horizon tasks. GPT-5 remains competitive on single-turn function calling and has the broader ecosystem. “Better” depends on the workload.

    Is Gemini 2.5 Pro cheaper than Opus 4.8 (legacy — still listed)?
    Significantly. At $2/$12 per million input/output tokens vs. Opus 4.8 (legacy — still listed)’s $5/$25

    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.

    , Gemini is 60% cheaper on input and 52% cheaper on output before tokenizer differences. At scale this is a material cost gap.

    Which model has the biggest context window?
    All three now have 1M-class context windows. Some Gemini 2.5 Pro documentation cites a 2M window. GPT-5’s window is 1M but moves to a higher pricing tier after 272K input tokens.

    Which model is best for coding?
    Opus 4.8 leads on agentic and long-horizon coding benchmarks. GPT-5 is close on single-turn coding. Gemini 2.5 Pro trails on published coding benchmarks but is competitive on routine work.

    Which model should I use for my startup?
    Most mature teams route workloads to multiple models. If you’re just starting and need to pick one, Opus 4.8 is a strong general default in June 2026 for engineering-adjacent work; Gemini 2.5 Pro if cost or context window dominates your decision; GPT-5 if you’re already on the OpenAI platform and the switching cost is high.

    Does Claude Opus 4.8 support function calling?
    Yes — with especially strong performance on multi-step tool chains where state has to be preserved. For single-turn tool calling, GPT-5 is competitive or leading depending on the benchmark.


    Related reading

    • Full Opus 4.8 feature set: Claude Opus 4.8 — Everything New
    • Opus 4.8 for coding specifically: xhigh, task budgets, and the 13% benchmark lift
    • The Mythos angle: why Anthropic admitted Opus 4.8 is weaker than an unreleased model

    Published April 16, 2026. Article written by Claude Opus 4.8 — yes, one of the models being compared. Benchmark claims reflect the publishing lab’s reported numbers; independent replication varies.

    Frequently Asked Questions

    Is Claude Opus 4.8 better than GPT-5?

    It depends on the task. Claude Opus 4.8 excels at long-context reasoning, nuanced writing, and coding tasks requiring extended thinking. GPT-5 has broader multimodal capabilities including audio. For pure text reasoning and large-document analysis, Claude Opus 4.8’s 1M token context gives it a significant advantage. GPT-5 is more expensive at $15/$75 per million tokens vs Opus 4.8’s $5/$25.

    How does Claude Opus 4.8 compare to Gemini 2.5 Pro?

    Both Claude Opus 4.8 (legacy — still listed) and Gemini 2.5 Pro support 1M token context windows. Gemini 2.5 Pro is cheaper at $3.50/$10.50 per million tokens vs Opus 4.8 (legacy — still listed)’s $5/$25. Claude Opus 4.8 (legacy — still listed) generally rates higher on reasoning and coding benchmarks. Gemini 2.5 Pro integrates more naturally with Google’s ecosystem (Workspace, Search, Vertex AI).

    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.

    Which AI model is best for coding in 2026?

    Claude Opus 4.8 and Claude Sonnet 4.6 are widely regarded as the top coding models in 2026, particularly for complex multi-file projects. Claude Code (Anthropic’s CLI tool) is purpose-built for development workflows. GPT-5 is also strong for coding. Gemini 2.5 Pro integrates well with Google Cloud development workflows.

    What is the cheapest frontier AI model in 2026?

    Claude Haiku 4.5 ($1/$5 per MTok) and Gemini 2.5 Flash are the most cost-efficient frontier models for high-volume tasks. For flagship-tier capability, Gemini 2.5 Pro ($3.50/$10.50) is cheaper than Claude Opus 4.8 (legacy — still listed) ($5/$25) or GPT-5 ($15/$75). The right choice depends on task complexity and volume.

    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.

    Is GPT-5 worth the higher price vs Claude Opus 4.8 (legacy — still listed)?

    For most text and coding workloads, no. Claude Opus 4.8 (legacy — still listed) at $5/$25

    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.

    per MTok delivers comparable or better results than GPT-5 at $15/$75 per MTok. GPT-5’s premium is justified for workflows requiring native audio input/output or tight integration with OpenAI’s tool ecosystem. For long-context document analysis, Opus 4.8’s 1M context at lower cost is a clear win.

    Which model should I use for my business in 2026?

    For general business writing and analysis: Claude Sonnet 4.6 (legacy — still listed) ($3/$15) or Gemini 2.5 Pro ($3.50/$10.50). For complex reasoning and large documents: Claude Opus 4.8 (legacy — still listed) ($5/$25). For high-volume, cost-sensitive workloads: Claude Haiku 4.5 ($1/$5). For Google Workspace integration: Gemini 2.5 Pro. For OpenAI ecosystem lock-in: GPT-5.

    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.