Category: Anthropic

Most Claude API usage works the same way: your application makes a call to api.anthropic.com across the public internet. For consumer apps and developer projects, that’s fine. For enterprises handling sensitive data — healthcare, finance, legal, government — “fine” isn’t the bar. The Fortress Architecture runs Claude inference through Google Cloud’s Vertex AI from inside a private VPC, so sensitive data never crosses a public network boundary.

The Core Architecture

Instead of calling the Anthropic API directly, your application calls Claude through Vertex AI from within a GCP Compute Engine VM or Cloud Run service inside your VPC. VPC Service Controls create a security perimeter around your Vertex AI resource. Requests to Claude stay inside that perimeter — they originate from your private network, route through Google’s internal infrastructure to Vertex AI, and return inside the same boundary.

From a data flow perspective: your application → private VPC → Vertex AI API (Google internal) → Claude model inference → back through VPC → your application. No public internet hop at any point.

Why a VM Instead of a Direct API Call

Running Claude through a VM — rather than a developer’s laptop or a serverless function with public internet access — gives you several properties that matter at enterprise scale:

Consistent identity. All Claude calls originate from a known service account with specific IAM permissions. There’s no risk of a developer accidentally using personal credentials or exposing an API key.

Network isolation. The VM sits inside a VPC with firewall rules. You control exactly what it can reach and what can reach it. No lateral movement from a compromised endpoint reaches your Claude integration.

Audit trail. Every Claude API call through Vertex AI generates Cloud Logging entries. You get a complete, immutable record of what was asked and when — essential for compliance in healthcare and financial services.

Centralized cost control. All AI spend flows through one GCP project with budget alerts and quotas. No shadow AI spending from individual developers using personal API keys.

Implementation Pattern

The standard setup: a Cloud Run service or Compute Engine VM runs your Claude-connected application code inside a VPC. A service account with roles/aiplatform.user is the only identity that can call Vertex AI. VPC Service Controls restrict Vertex AI access to requests originating from your perimeter. Cloud Logging captures all API activity. Budget alerts on the GCP project catch unexpected usage spikes.

The application code itself is straightforward — the Anthropic Python or Node.js SDK with the Vertex AI configuration flag set. The security comes from the infrastructure layer, not the application layer.

When This Architecture Is Worth the Setup

For a solo developer or small startup, this is overkill. The setup overhead — VPC configuration, service accounts, VPC Service Controls, Cloud Logging — is a full day of infrastructure work. For organizations where a data breach involving patient records, financial data, or privileged legal communications would be catastrophic, that day of setup is a trivial cost against the risk.

The categories where this architecture is essentially required: HIPAA-covered healthcare applications, financial services with SOC 2 or PCI requirements, legal services handling privileged communications, government contractors, and any application processing PII at scale.

The Real Operational Benefit Beyond Security

The compliance story is obvious. The less-discussed benefit is operational consistency. When all Claude usage flows through a single controlled channel, you get uniform behavior (same model version, same parameters, same rate limits), centralized prompt management (update the system prompt in one place, not in every developer’s local config), and predictable costs. The Fortress Architecture is as much an operational discipline as it is a security model. See The Fortress Architecture: Full Guide for the complete technical breakdown and Claude on Vertex AI: Why Route Through GCP for the Vertex AI setup.

Anthropic has released over a dozen Claude models since the first public launch in March 2023. This page is the complete record — every model, its release date, the key capability it introduced, and its current status. It’s updated when Anthropic ships new releases.

The Complete Claude Model Timeline

The Generational Leaps That Mattered Most

Claude 3.5 Sonnet (June 2024) — The Benchmark Flip

This was the release that established Claude as a serious competitor to GPT-4. Claude 3.5 Sonnet outperformed Claude 3 Opus on most benchmarks at half the cost — the first time a Sonnet-tier model beat the prior generation’s flagship. It also introduced Artifacts, the interactive output canvas that became a defining Claude feature. Every generation since has followed this pattern: new Sonnet outperforms prior Opus.

Claude 3.7 Sonnet (February 2025) — Extended Thinking

Extended thinking gave Claude an explicit reasoning layer before responding — the model could work through a problem step-by-step before committing to an answer. This was Anthropic’s answer to OpenAI’s o1 and marked the beginning of “reasoning models” as a mainstream concept in Claude’s lineup.

Claude Sonnet 4 (May 2025) — Coding Leadership

The Claude 4 launch pushed Claude to the top of SWE-bench Verified, the real-world software engineering benchmark that matters most to developers. Claude Code launched alongside it and reached $1B in annualized revenue by November 2025 — one of the fastest-growing developer tools in history.

Claude Sonnet 4.6 (February 2026) — Computer Use at Scale

The 4.6 generation’s most significant practical advance was dramatically improved computer use — Claude’s ability to navigate browsers, fill forms, click through interfaces, and operate software autonomously. Combined with the 1M token context window reaching general availability, this made Claude genuinely useful for long-horizon agentic tasks that previously required constant human intervention.

What Comes Next

Claude 5 has not been officially announced as of May 2026. No official announcement as of June 2026. The pattern suggests Claude 5 Sonnet will outperform current Opus 4.6 at lower cost — consistent with every prior generation transition. See Claude 5 Release Date: What We Know.

For current API strings and deprecation deadlines, see the Current Claude Model Version Tracker.

Anthropic shipped a significant number of product updates in April 2026. This digest covers everything that changed — model deprecations, Cowork updates, Claude Code releases, and API additions — in one place. Bookmark this and check the Current Claude Model Tracker for the latest model strings.

Model Changes

Claude 4.0 Deprecation — Action Required by June 15

Anthropic announced the deprecation of claude-sonnet-4-20250514 and claude-opus-4-20250514 — the original Claude 4.0 model versions from May 2025. Both retire from the Anthropic API on June 15, 2026. If you have either string in production code, migrate to claude-sonnet-4-6 and claude-opus-4-7 respectively. Full migration guide: Claude 4 Deprecation: What to Migrate To.

1M Token Context Window — Now Generally Available

The 1 million token context window for Claude Opus 4.7 and Claude Sonnet 4.6 is now generally available at standard pricing with no long-context surcharge. Previously in beta, this window supports approximately 750,000 words or about 2,500 pages of text in a single session. Also available on Vertex AI for both models.

Cowork Updates

Cowork Generally Available

Claude Cowork reached general availability on macOS and Windows via Claude Desktop this month, exiting the research preview label. The GA release added expanded usage analytics, OpenTelemetry support for monitoring Cowork activity, and role-based access controls for Enterprise plans so admins can customize which Claude capabilities each team group can access.

Computer Use in Cowork

Pro and Max plan users can now give Claude access to computer use within Cowork — meaning Claude can open files, run dev tools, navigate browsers, point, click, and interact with what’s on screen to complete tasks autonomously. No setup required for Pro/Max users. This makes Cowork’s Dispatch feature substantially more capable, letting Claude take multi-step actions on your computer while you’re away.

Scheduled and Recurring Tasks

Cowork now supports creating and scheduling both recurring and on-demand tasks from within the app. Previously this required configuration outside the main interface. A new Customize section in Claude Desktop groups skills, plugins, and connectors in one place.

Plugin Marketplace

Anthropic launched a new plugin marketplace for Team and Enterprise plans with admin controls for managing which plugins are available to which users. Enterprise admins can approve, restrict, or block specific plugins org-wide.

Claude Code Updates

Vertex AI Setup Wizard

Claude Code v2.1.98 and later include a /setup-vertex wizard that automates Google Cloud Vertex AI configuration — project selection, region, model pinning — without manually setting environment variables. Run claude --version to check if you’re on a supported version. Full setup guide: How to Run Claude Code on Vertex AI.

Advisor Tool — Public Beta

The Anthropic API now supports a public beta advisor tool (beta header: advisor-tool-2026-03-01). The pattern: pair a faster executor model with a higher-intelligence advisor model that provides strategic guidance mid-generation. Long-horizon agentic workloads get close to advisor-solo quality at executor-model costs. Useful for tasks where you want Opus-level reasoning with Sonnet-level speed on the bulk of token generation.

Worktree Switching and PreCompact Hooks

Claude Code added a path parameter to the EnterWorktree tool for switching into existing worktrees, PreCompact hook support (hooks can now block compaction by returning a decision block), and background monitor support for plugins via a top-level monitors manifest key.

Interactive Connectors in Claude Mobile

The Claude mobile app can now connect to fully interactive apps — live charts, diagrams, and shareable assets rendered visually inside conversations. Pull up live data, sketch diagrams, and build assets directly in the mobile chat interface.

What to Watch in May 2026

The June 15 deprecation deadline for Claude 4.0 models is the immediate action item for any team running the original 4.0 model strings. Claude 5 remains unannounced but expected Q2-Q3 2026 based on release cadence — see Claude 5 Release Date: What We Know. The advisor tool beta is worth testing for any team running complex agentic pipelines.

Claude Code is Anthropic’s terminal-native coding agent. By default it bills through your Anthropic account. But you can route it entirely through Google Cloud’s Vertex AI — meaning it charges your GCP account instead, and you can use existing GCP credits, startup credits, or free trial credits to run it at no incremental cost. Here’s the exact setup.

What You Need Before Starting

A Google Cloud account with a project created. Vertex AI API enabled on that project. Claude models requested and approved in Vertex AI Model Garden. Claude Code installed (npm install -g @anthropic-ai/claude-code). The gcloud CLI installed and authenticated. That’s it — no Anthropic API key required once this is configured.

Step 1: Enable Vertex AI and Request Claude Model Access

In the Google Cloud Console, go to Vertex AI > Model Garden and search for “Claude.” Request access to at least Claude Sonnet 4.6 (the primary Claude Code model) and Claude Haiku 4.5 (used for lightweight operations). Without Haiku, Claude Code will use Sonnet for everything — slower and more expensive for simple tasks. Enable Opus 4.6 as well if you need maximum capability for complex tasks.

Model access approval is typically instant for most GCP accounts.

Step 2: Authenticate with Google Cloud

Run both commands below — the first authenticates your user account, the second sets application default credentials that Claude Code will pick up automatically:

Set your project: gcloud config set project YOUR-PROJECT-ID

Enable the Vertex AI API: gcloud services enable aiplatform.googleapis.com

Step 3: Configure Claude Code to Use Vertex AI

Set these environment variables. On macOS/Linux, add them to your ~/.zshrc or ~/.bashrc. On Windows, use PowerShell’s [System.Environment]::SetEnvironmentVariable at the User level so they persist across sessions.

Step 4: Verify the Setup

Launch Claude Code and run /status. You should see API provider: Google Vertex AI and your GCP project ID. If you see the Anthropic API provider instead, your environment variables haven’t loaded — restart your terminal and try again.

Step 5: Use the New Wizard (Claude Code v2.1.98+)

If you’re on Claude Code version 2.1.98 or later, you can skip manual environment variable setup. Run /setup-vertex inside Claude Code and the wizard walks you through project selection, region, and model pinning automatically. Run claude --version to check your version first.

Region Selection: Global vs Regional Endpoints

Use CLOUD_ML_REGION=global unless you have specific compliance reasons to pin to a region. Global endpoints get the latest models first, have better availability, and don’t incur the 10% regional pricing premium. If you need data residency in a specific geography, use us-east5, us-central1, or europe-west1 — but verify your target Claude models are available in that region first, as not all models are available in all regions.

Model Pinning for Teams

If you’re deploying Claude Code to multiple team members, pin specific model versions rather than using aliases. Model aliases like “sonnet” resolve to the latest version, which may not be enabled in your Vertex AI project when Anthropic ships an update. Pinning prevents silent failures on update day:

Common Error: 429 Resource Exhausted

If you see 429 errors after setup, your project’s Vertex AI quota for Claude models needs to be increased. Go to Cloud Console > IAM & Admin > Quotas, filter by “anthropic,” and request an increase for the models you’re using. Approvals are typically fast for standard business accounts.

Anthropic offers two ways to access Claude programmatically: directly through the Anthropic API, or through Google Cloud’s Vertex AI. They run the same models with the same capabilities. The difference is infrastructure, billing, compliance, and control. Here’s when each makes sense — and why teams running production AI workloads on GCP increasingly choose Vertex.

What You Actually Get Through Vertex AI

When you access Claude through Vertex AI, the request routes through Google Cloud infrastructure rather than Anthropic’s own endpoints. You get access to every Claude model — Opus 4.6, Sonnet 4.6, Haiku 4.5 — with the same capabilities including the 1M token context window on Opus and Sonnet. Nothing is stripped down. The key differences are on the infrastructure and billing side, not the model side.

Five Reasons to Route Through GCP Instead of Direct API

1. Consolidated GCP billing

If your organization already runs on Google Cloud, adding Claude through Vertex AI means all AI spending appears on a single GCP bill. No separate Anthropic invoice, no separate API key management system, no separate budget approval process. For enterprise finance teams, this is often the deciding factor — Claude becomes a line item on the existing cloud budget rather than a new vendor relationship.

2. Use existing GCP credits

Google Cloud offers $300 in free credits to new accounts, startup credits through various programs, and committed use discounts for larger organizations. All of these apply to Claude usage through Vertex AI. Teams with unused GCP credit can run substantial Claude workloads at no incremental cost. New GCP accounts can effectively run Claude Code for free until credits are exhausted.

3. IAM and access control

Vertex AI integrates with Google Cloud IAM, meaning you can control who in your organization can access Claude using the same permission system you use for every other GCP service. Roles, service accounts, audit logs — all standard GCP tooling applies. This eliminates the need for a separate API key distribution system and makes access revocation immediate and centralized.

4. VPC Service Controls and private networking

For organizations with strict data residency or network isolation requirements, Vertex AI supports VPC Service Controls that prevent Claude API calls from leaving your private network perimeter. Claude requests originate from inside your GCP VPC rather than from an internet-facing endpoint. This is the core of what some teams call a “Fortress Architecture” — running AI inference inside a secured cloud environment where data never traverses the public internet. For regulated industries (healthcare, finance, legal), this is often a compliance requirement, not a preference. See The Fortress Architecture: Why Regulated Industries Need Their Own Cloud for the full architecture breakdown.

5. Regional data residency

Vertex AI lets you pin Claude requests to specific GCP regions — US, EU, or specific regional endpoints. For organizations subject to GDPR or other data residency requirements, this ensures AI processing stays within the required geographic boundary. The Anthropic direct API does not offer equivalent regional controls.

When the Direct Anthropic API Is Better

Vertex AI adds setup overhead — you need a GCP project, Vertex AI enabled, model access requested in Model Garden, and IAM configured. For individual developers, startups, and teams that don’t already run on GCP, this overhead isn’t worth it. The direct Anthropic API is faster to set up (generate a key, start calling), has the best rate limits for getting started, and doesn’t require cloud infrastructure knowledge.

Also: new Claude models appear in the direct API before they appear in Vertex AI’s Model Garden. If you need day-one access to new releases, direct is faster.

Pricing Comparison

Global endpoint pricing matches Anthropic direct. Regional endpoints add a 10% premium for the data residency guarantee. If you don’t need regional pinning, use the global endpoint and pay identical rates.