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.
What you need before you start
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
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
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
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
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)
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):
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, including the June 2026 lineup with Fable 5).
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.
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.
What models can a new key use? The current lineup as of June 2026 — including Claude Fable 5, Opus 4.8, Sonnet 4.6, and Haiku 4.5; see everything that changed in June 2026.
Get alerted when Claude pricing or limits change
We track Anthropic’s models, pricing, and limits daily and send a short note when something changes that affects what you pay or build. Occasional, no spam.
Last verified: June 11, 2026 (Pacific Time). This is the June edition of our monthly Claude updates series — the May 2026 edition covered the Opus 4.8 launch, the SpaceX compute deal, and Managed Agents memory features.
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)
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)
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
claude-opus-4-8
1M
128K
$5.00
$25.00
Claude Sonnet 4.6
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
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.
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 — the new current flagship model, succeeding Opus 4.8. 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.
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)
Opus 4.8 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 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.
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 — 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
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.
Anthropic’s Claude pricing covers six tiers — Free, Pro, Max 5x, Max 20x, Team, and Enterprise — plus a separate pay-per-token API. Choosing the wrong path can cost you significantly more than necessary. Here’s what each option actually includes in 2026.
What Are Claude’s Subscription Plans and Prices?
Claude offers six tiers: Free ($0), Pro ($20/month), Max 5x ($100/month), Max 20x ($200/month), Team (from $20/seat/month billed annually), and Enterprise (custom pricing).
The Free plan gives you access to Claude on web, iOS, Android, and desktop with no credit card required, subject to rolling usage limits.
The Free plan gives you access to Claude on web, iOS, Android, and desktop with no credit card required. It includes text, image, and code generation plus web search. Usage limits are intentionally opaque — Anthropic doesn’t publish exact message caps — but limits reset on a rolling 5-hour window. The Free tier is designed for exploration, not sustained daily work.
Is Claude Pro Worth $20 a Month?
Pro delivers substantially more usage than Free, plus Claude Code, unlimited projects, the Research feature, and Google Workspace integration — sufficient for most individual developers and writers.
Pro delivers substantially more usage than Free, Claude Code in the terminal, unlimited projects, the Research feature, file creation, code execution, and Google Workspace integration. Usage still has limits — Anthropic does not publish exact message counts, but heavy sessions will reach the ceiling — but it’s sufficient for most individual developers and writers. Annual billing brings the effective rate to $17/month.
What Is the Difference Between Claude Max 5x and Max 20x?
Max 5x ($100/month) gives you 5x Pro’s per-session usage; Max 20x ($200/month) gives you 20x — enough that rate limits stop being a practical concern for full-day development work.
Max 5x provides 5x Pro’s per-session headroom at $100/month. Max 20x at $200/month delivers 20x Pro usage — enough that rate limits stop being a practical concern for most full-day development work. Both tiers include Claude Code, with access to Claude Opus 4.8 and Sonnet 4.6, and a 1M token context window.
Extra usage is available on Pro, Max 5x, and Max 20x — when you hit your included limit, you can continue at standard API-rate billing with a spending cap you set.
How Does Claude Team Plan Pricing Work?
Team requires a minimum of 5 seats: Standard seats at $20/seat/month billed annually ($25 monthly) include collaboration features but not Claude Code; Premium seats at $100/seat/month billed annually ($125 monthly) add Claude Code for developers.
Team requires a minimum of 5 seats and comes in two flavors. Standard seats at $20/seat/month billed annually ($25 billed monthly) include 1.25x more usage per session than Pro with a weekly reset, plus collaboration features, central billing, SSO, and Microsoft 365 and Slack integrations. Standard seats do not include Claude Code.
Premium seats at $100/seat/month billed annually ($125 monthly) add Claude Code, making them the right choice for engineering team members. You can mix Standard and Premium seats within one Team plan — so non-technical staff get Standard while developers get Premium.
Enterprise Plan — Custom Pricing
Enterprise is for organizations with compliance, data residency, or governance requirements. It includes access to the full 1M token context window, HIPAA readiness, SAML SSO, domain capture, spend controls, and dedicated support. Based on user reports, pricing starts around $60/seat with a 70-seat minimum, putting the floor near $50,000 annually — contact Anthropic sales for exact figures. Training on customer data is disabled contractually at this tier.
How Much Does the Claude API Cost Per Token?
As of May 2026: Claude Sonnet 4.6 costs $3.00 input / $15.00 output per million tokens; Opus 4.6 costs $5.00 / $25.00; Haiku 4.5 costs $1.00 / $5.00.
The API is entirely separate from subscription plans. You pay per million tokens (MTok) with no monthly minimum. Current rates as of June 10, 2026 (verified June 10, 2026 from Anthropic’s official models page):
Claude Opus 4.8: $5.00 input / $25.00 output per MTok
Claude Sonnet 4.6: $3.00 input / $15.00 output per MTok
Claude Haiku 4.5: $1.00 input / $5.00 output per MTok
Prompt caching cuts input costs by up to 90% for repeated context. The Batch API processes requests within 24 hours at a flat 50% discount on all tokens — ideal for content pipelines, data enrichment, and any workload where real-time responses aren’t required. As of March 2026, Anthropic eliminated long-context surcharges, so a 900K-token request costs the same per-token rate as a 9K one.
June 2026 — Professional Services Pricing
Managed Agents
Token rates + $0.08/session-hour active runtime. No surcharge for Orchestration or Outcomes (public beta).
Claude Security Beta
Included in Enterprise during beta. Powered by Opus 4.8 ($5/$25 per MTok at API rates).
Start with Pro for individual use, move to Max 5x if you regularly hit limits, choose Max 20x for full-day heavy use, and use Team for groups of 5+ where Standard seats cover non-technical staff and Premium covers developers.
Start with Pro if you’re an individual who hits Free limits regularly. Move to Max 5x if you’re a developer doing focused coding sessions. Max 20x makes sense if Claude is your primary tool throughout the workday. For teams, buy Standard seats for non-technical staff and Premium seats for developers who need Claude Code. If you’re building an application or automation that calls Claude programmatically, use the API — subscription plans don’t provide API credits and don’t reduce API costs.
Claude API Pricing: Pay-Per-Token Rates for Every Model
The Claude API is priced separately from claude.ai subscriptions. You pay per million tokens (MTok) consumed — input and output priced separately. There is no monthly minimum; you add credits and they deplete as you use the API.
Prompt caching reduces costs significantly for repeated context: cache write is 25% of base input price, cache read is 10%. The Batch API offers 50% off all models for non-time-sensitive work. For a full breakdown of how to minimize token spend, see Claude on a Budget: the Complete Guide.
How Does Claude Pricing Compare to GPT-4o and Gemini 2.0?
Claude Sonnet 4.6 sits above GPT-4o on price but competes at or above it on reasoning tasks. Claude Haiku 4.5 is the cost-competitive option for high-volume pipelines. Gemini 2.0 Flash is significantly cheaper for commodity tasks; the trade-off is reasoning depth and context handling on complex documents.
How Much Does a Claude License Cost for Business?
A Claude business license is sold per seat: Team Standard seats cost $20/seat/month billed annually ($25 monthly), Team Premium seats with Claude Code cost $100/seat/month billed annually ($125 monthly), with a 5-seat minimum. Enterprise licenses are custom-priced annual contracts.
License type
Annual billing
Monthly billing
Minimum seats
Claude Code
Team Standard seat
$20/seat/month
$25/seat/month
5
No
Team Premium seat
$100/seat/month
$125/seat/month
5
Yes
Enterprise license
Custom (annual contract — contact sales)
~70 (reported)
Yes
If you’re writing a budget request or procurement document, here are the numbers that matter: a 10-person team with 7 Standard and 3 Premium seats runs $440/month on annual billing — $5,280/year. Licenses are managed centrally with consolidated billing, SSO, and admin controls, and you can mix Standard and Premium seats within one plan. A Claude license covers the claude.ai apps and (on Premium seats) Claude Code; it does not include API credits, which are billed separately per token. There is no perpetual or one-time license option — all Claude licensing is subscription-based.
How Much Does Claude Code Cost?
Claude Code has no standalone price — it’s included with Pro ($20/month), Max 5x ($100/month), Max 20x ($200/month), Team Premium seats ($100/seat/month annual), and Enterprise. Alternatively, run it against an API key and pay per token.
Plan
Claude Code included?
Usage headroom
Free
No
—
Pro ($20/mo)
Yes
Standard Pro limits — enough for an hour or two of daily coding
Max 5x ($100/mo)
Yes
5x Pro — sustained daily development
Max 20x ($200/mo)
Yes
20x Pro — full-day heavy use and parallel sessions
Team Standard
No
—
Team Premium ($100/seat annual)
Yes
Per-seat developer allocation
Enterprise
Yes (Premium seats)
Custom
API key (pay-per-token)
Yes
No plan limits — billed at standard model token rates
For automation — cron jobs, CI pipelines, claude -p scripts — note the June 15, 2026 change: subscription plans get a monthly Agent SDK credit pool (Pro $20, Max 5x $100, Max 20x $200, Team Standard $20/seat, Team Premium $100/seat), with overage billed at API rates. Full details in the Agent SDK dual-bucket billing guide. For the complete tier-by-tier breakdown including API-key economics, see the full Claude Code pricing guide.
What Are Claude’s Usage Limits and Extra Usage Costs?
Every Claude plan has usage limits that reset on a rolling 5-hour window, plus weekly caps on paid tiers. When you hit a paid plan’s limit, you can either wait for the reset or buy extra usage at standard API token rates with a spending cap you control.
Plan
Relative usage
Reset window
Extra usage available?
Free
Baseline (light use)
Rolling 5 hours
No — upgrade required
Pro
~5x Free
Rolling 5 hours + weekly cap
Yes — API rates, capped by you
Max 5x
5x Pro
Rolling 5 hours + weekly cap
Yes
Max 20x
20x Pro
Rolling 5 hours + weekly cap
Yes
Team Standard
1.25x Pro per seat
Weekly reset
Yes (admin-controlled)
Team Premium
Higher, includes Claude Code
Weekly reset
Yes (admin-controlled)
Anthropic intentionally doesn’t publish exact message counts — limits are measured in compute, so long conversations, large file uploads, and Opus-heavy sessions consume your window much faster than short Haiku chats. For the full mechanics, see Claude Team plan usage limits and Claude API rate limits.
Claude Pricing by Country: UK, Australia, India, and Canada
Anthropic charges the same USD list price in every country — Claude Pro is $20/month worldwide. Your bank converts to local currency, and applicable local tax (VAT or GST) is added at checkout.
Country
Claude Pro (approx. local)
Claude Max 5x (approx. local)
Tax added at checkout
United Kingdom
≈ £16/month
≈ £79/month
20% VAT
Australia
≈ A$31/month
≈ A$153/month
10% GST
India
≈ ₹1,700/month
≈ ₹8,600/month
18% GST
Canada
≈ C$27/month
≈ C$137/month
GST/HST (5–15% by province)
New Zealand
≈ NZ$33/month
≈ NZ$166/month
15% GST
Local-currency figures are approximate conversions at June 2026 exchange rates — your card statement reflects your bank’s rate plus any foreign-transaction fee. There is no region-specific discount pricing for claude.ai plans, and API token rates are likewise USD-denominated everywhere. Prices shown on Anthropic’s pricing page exclude applicable tax.
Frequently Asked Questions: Claude Pricing
How much does Claude cost per month?
Claude costs $0 (Free), $20/month (Pro), $100/month (Max 5x), or $200/month (Max 20x) for individual plans. Team plans start at $20/seat/month (annual billing, 5-seat minimum). API access is pay-per-token with no monthly minimum.
Is there a free version of Claude?
Yes. The Free plan gives access to Claude on web, iOS, Android, and desktop with no credit card required. Usage limits apply and reset on a rolling 5-hour window. The Free tier is suitable for light, exploratory use but not sustained daily work.
What does Claude Pro include at $20/month?
Pro includes approximately 5x the usage of Free, Claude Code in the terminal, unlimited projects, the Research feature, file creation, code execution, and Google Workspace integration. Annual billing brings the effective rate to $17/month.
What is the cheapest way to use Claude?
The Free plan is the cheapest at $0. For API access, Claude Haiku 4.5 at $1 input / $5 output per MTok is the most cost-efficient model. Combined with the Batch API (50% discount) and prompt caching, high-volume workflows can run at a fraction of standard API cost.
What is Claude Max and is it worth $100–$200 per month?
Claude Max comes in two tiers: Max 5x at $100/month gives 5x Pro’s per-session usage, and Max 20x at $200/month gives 20x. Max is worth it if you’re hitting Pro limits regularly during development or coding sessions. Both include Claude Code and the full 1M token context window with Claude Opus 4.8 and Sonnet 4.6.
How does Claude Team pricing work?
Team plans require a minimum of 5 seats. Standard seats cost $20/seat/month billed annually ($25 monthly) and include collaboration features. Premium seats cost $100/seat/month billed annually ($125 monthly) and add Claude Code — the right choice for developers on the team. You can mix Standard and Premium seats within the same Team plan.
Does Claude Pro give you access to Claude Opus 4.8?
Pro gives you access to Claude’s models including Opus 4.8 for complex tasks, Sonnet 4.6, and Haiku 4.5, subject to usage limits. The Max tiers give you significantly more headroom to use Opus 4.8 for extended sessions. For unlimited, predictable API access to Opus 4.8, use the API directly at $5 input / $25 output per million tokens.
What is the Claude API cost per million tokens in 2026?
As of June 2026 (verified from Anthropic’s official docs): Claude Opus 4.8 costs $5.00 input / $25.00 output per million tokens; Claude Sonnet 4.6 costs $3.00 input / $15.00 output; Claude Haiku 4.5 costs $1.00 input / $5.00 output. The Batch API offers 50% off all models for non-real-time work.
Does Claude have a student discount?
There is no individual self-serve student discount, but Anthropic now offers an Education plan with discounted rates for universities and their members — check whether your institution participates. Otherwise students can use the Free tier without a credit card, and the cheapest paid path is Pro at $17/month with annual billing.
Can I use Claude without a subscription by paying per use?
Not directly through claude.ai — the website only offers Free, Pro, Max, and Team subscription plans. Pay-per-use access is available only through the Claude API, which requires a developer account. API pricing starts at $1 input / $5 output per million tokens for Haiku 4.5 with no monthly minimum charge.
How much does the Anthropic Console (Claude Console) cost?
The Anthropic Console itself is free — it’s the developer dashboard for managing API keys, tracking usage, and testing prompts in the Workbench. You only pay for the API tokens you consume, starting at $1 input / $5 output per million tokens for Haiku 4.5. You add prepaid credits to get started; there is no monthly platform fee.
How much is a Claude license for business?
Claude business licensing is per-seat: Team Standard seats cost $20/seat/month billed annually ($25 monthly), and Team Premium seats with Claude Code cost $100/seat/month billed annually ($125 monthly), with a 5-seat minimum. Enterprise licenses are custom annual contracts. There is no perpetual license — all Claude licensing is subscription-based.
Does the Claude desktop app cost extra?
No. The Claude desktop app for Windows and macOS is included with every plan, including Free. Desktop, web, and mobile all share the same account and the same usage limits — there is no separate desktop pricing.
Is Claude cheaper in India, the UK, or Australia?
No — Anthropic charges the same USD list price worldwide. Claude Pro is $20/month everywhere; your bank converts it to local currency (roughly £16, A$31, or ₹1,700) and local VAT or GST is added at checkout where applicable. There is no regional discount pricing.
Is Claude available on Azure, AWS, or Google Cloud?
Yes. Claude models are available through Amazon Bedrock and the Claude Platform on AWS, Google Cloud’s Vertex AI, and Microsoft Foundry. Cloud-platform pricing is token-based and aligned with Anthropic’s API rates, billed through your existing cloud account — useful if your organization has cloud spend commitments to draw down.
Does Anthropic offer nonprofit pricing?
Anthropic doesn’t list a standing nonprofit discount on its pricing page as of June 2026. Nonprofits typically start with Team at standard rates or contact Anthropic sales about Enterprise terms. An Education plan with discounted rates does exist for universities and their members.
May 2026: Managed Agents & Claude Security Pricing
Updated June 10, 2026
Anthropic’s professional services now include Managed Agents and Claude Security. Pricing for both is API-based, not subscription-based.
Claude Managed Agents Pricing
Managed Agents pricing follows the standard API token rates for whichever Claude model you use inside the agent pipeline — there’s no separate Managed Agents surcharge on top of model costs. You pay for the tokens the models consume:
The Dreaming advisor tool uses a short-plan generation (typically 400–700 tokens) at the advisor model’s rate, while the executor handles full output at its lower rate — keeping combined cost well below running the advisor model end-to-end. Use max_uses to cap advisor calls per request. Requires beta header: anthropic-beta: advisor-tool-2026-03-01. Docs: platform.claude.com/docs/en/managed-agents/dreams
Claude Security Beta Pricing
Claude Security is currently in public beta for Enterprise customers. Anthropic has not published a standalone per-scan or per-seat price for Claude Security Beta — access is included as part of Enterprise during the beta period. Underlying model is Claude Opus 4.8 ($5 input / $25 output per million tokens at API rates). For Enterprise pricing including Claude Security, contact Anthropic sales.
Claude Mythos Preview Pricing (Project Glasswing)
Claude Mythos Preview is not available via standard API or any subscription tier. Through Project Glasswing (invitation-only, defensive cybersecurity workflows): $25 per million input tokens, $125 per million output tokens. No self-serve access — contact Anthropic for Glasswing information at anthropic.com/glasswing.
What to do next
Now that you have the price — here’s how to actually run it
Knowing the cost is step one. The harder questions are whether Managed Agents is the right architecture for your use case, how it compares to building on the raw API, and what a realistic monthly bill looks like at scale.
Use this tool to figure out which Claude plan actually fits your usage, what you’d pay on the API equivalent, and how the new June 15, 2026 Agent SDK billing change affects your costs. All rates verified against Anthropic’s official pricing documentation as of June 10, 2026.
Tell us how you use Claude
2 = roughly 30 hours of normal Claude use per month
Output is typically ~25% of input for chat work
$ value of unattended Claude work (cron jobs, scripts, GitHub Actions). 0 if you only chat.
Your estimated costs
Email me this breakdown
Get your numbers in your inbox so you can compare plans later — or forward them to whoever approves the budget.
This calculator uses Anthropic’s published API rates as of June 10, 2026. Subscription pricing reflects current public plans. The Agent SDK monthly credit pool launches June 15, 2026 — Pro $20, Max 5x $100, Max 20x $200, Team Standard $20/seat, Team Premium $100/seat.
What Claude Actually Costs: Six Worked Examples (June 2026)
The calculator above is interactive; these are the same calculations worked through for six common usage profiles, using Anthropic’s published rates as of June 10, 2026. API-equivalent figures assume standard rates with no prompt caching or batch discounts.
Profile
Monthly usage
Best plan
Plan cost
API equivalent
Casual user — questions a few times a week
0.5M in / 0.13M out (Sonnet 4.6)
Free, or Pro for headroom
$0–$20
≈ $3.45/mo
Individual writer or analyst — daily use
2M in / 0.5M out (Opus 4.8)
Pro
$20 ($17 annual)
≈ $22.50/mo
Developer — focused daily coding with Claude Code
10M in / 2.5M out (Opus 4.8)
Max 5x
$100
≈ $112.50/mo
Power user — Claude open all day, parallel sessions
30M in / 7.5M out (Opus 4.8)
Max 20x
$200
≈ $337.50/mo
5-person team — 3 non-technical, 2 developers
Mixed
Team: 3 Standard + 2 Premium
$260/mo (annual billing)
Varies by usage
High-volume pipeline — classification or enrichment
50M in / 10M out (Haiku 4.5, Batch API)
API direct
—
≈ $50/mo (after 50% batch discount)
The pattern: subscriptions beat the API whenever usage is steady and interactive — Pro pays for itself at roughly 2M input tokens a month on Opus 4.8. The API wins for spiky automated workloads, anything that can use the Batch API, and pipelines that run on Haiku 4.5. A reasonable rule of thumb: if your monthly API equivalent lands more than about 50% above a subscription price, take the subscription.
Next Steps: What to Read After This
You came here for pricing. Depending on what you actually need to do next, these are the right places to go:
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
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
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 concrete actions based on this finding:
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.
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.
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.
Current flagship: Claude Opus 4.7 (claude-opus-4-7). Current models: Opus 4.7 · Sonnet 4.6 · Haiku 4.5. This article compares Claude Opus 4.7 pricing to Opus 4.6 as a historical baseline. Opus 4.7 is the current flagship. Both models share the $5/$25.00 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
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
Do not estimate — measure. Here is the four-step process:
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.
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.
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.
Apply the multiplier to your budget model and adjust your spend projections before migrating production workloads to Opus 4.7.
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 4.7 for the tasks where quality genuinely requires it, Sonnet 4.6 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 4.6 for your use case. For many production workloads, Claude Sonnet 4.6 at $3/$15 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.
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 is available now through the Anthropic API at platform.claude.com. API pricing: $5/M input tokens, $25/M output tokens. Measure before you migrate.
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
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
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
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.
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.
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.
Current flagship: Claude Opus 4.7 (claude-opus-4-7). Current models: Opus 4.7 · Sonnet 4.6 · Haiku 4.5. 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
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
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
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 4.7: $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.
Current flagship: Claude Opus 4.8 (claude-opus-4-8). Current models: Opus 4.8 · Sonnet 4.6 · Haiku 4.5. Claude Opus 4.8 (claude-opus-4-8) is the current flagship 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)
Feature
Detail
Use Case
Context window
1,000,000 tokens (~750,000 words)
Full codebase analysis, long document review
Extended thinking
Visible reasoning chain before answer
Complex math, multi-step strategy, debugging
Vision
Images, screenshots, diagrams
UI review, document parsing, chart analysis
Tool use
Function calling, parallel tool calls
Agents, API integrations, data pipelines
Computer use
Control desktop/browser via screenshots
Automation, testing, research
Task budgets
Set thinking token limits per request
Cost control on complex reasoning tasks
Batch API
Async processing at 50% off
High-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:
Task budgets (beta) — per-subtask ceilings that tame agent cost variance.
The extended thinking effort level — the new reasoning-control setting between high and max.
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)
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
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
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 (claude-opus-4-8) is Anthropic’s current flagship model with a 1 million token context window, extended thinking (visible 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 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 ($3/$15 per MTok, 40% cheaper) for most everyday tasks — writing, coding, analysis — where Opus-level reasoning is not needed.
Current flagship: Claude Opus 4.8 (claude-opus-4-8). Current models: Opus 4.8 · Sonnet 4.6 · Haiku 4.5. Claude Opus 4.8 (claude-opus-4-8) is the current flagship 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)
Attribute
Claude Opus 4.8
GPT-5
Gemini 2.5 Pro
Developer
Anthropic
OpenAI
Google DeepMind
API ID
claude-opus-4-8
gpt-5
gemini-2.5-pro
Context window
1M tokens
128K tokens
1M tokens
Input price (per MTok)
$5.00
$15.00
$3.50
Output price (per MTok)
$25.00
$75.00
$10.50
Multimodal
Text + vision
Text + vision + audio
Text + vision + audio
Best for
Long-context reasoning, coding, writing
Broad capability, tool use
Google 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
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
$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
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
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?
Significantly. At $2/$12 per million input/output tokens vs. Opus 4.8’s $5/$25, 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 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’s $5/$25. Claude Opus 4.8 generally rates higher on reasoning and coding benchmarks. Gemini 2.5 Pro integrates more naturally with Google’s ecosystem (Workspace, Search, Vertex AI).
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 ($5/$25) or GPT-5 ($15/$75). The right choice depends on task complexity and volume.
Is GPT-5 worth the higher price vs Claude Opus 4.8?
For most text and coding workloads, no. Claude Opus 4.8 at $5/$25 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 ($3/$15) or Gemini 2.5 Pro ($3.50/$10.50). For complex reasoning and large documents: Claude Opus 4.8 ($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.
