Claude 4 Arrives: The «AI model family» That Marries 200 K-Token Context, Multi-Hour “Extended Thinking,” and Production-Ready Developer Tools

Graziano Stefanelli
16 hours ago
5 min read

Claude 4, released by Anthropic on 22 May 2025, features two new models—Opus 4 and Sonnet 4—with a groundbreaking 200,000-token context window and multi-hour “Extended Thinking”.

This means the models can now handle extensive reasoning tasks and interact continuously with tools over extended periods.

Both models set new benchmarks in coding tasks, while the update also includes the general availability of Claude Code, complete with IDE plug-ins (VS Code and JetBrains) and a robust new SDK for automated developer workflows.

ARTICLE INDEX:

1. A milestone release on 22 May 2025

Anthropic has steadily climbed the language-model leaderboards since the first Claude preview in 2023, but the Claude 4 twins—Opus 4 and Sonnet 4—mark its boldest leap yet. Both models sit on a redesigned transformer stack, trained with an order-of-magnitude more “constitutional” feedback and a new self-critique loop tuned for long-form reasoning. The headline promise is simple: you can throw a novel’s worth of context at the model, leave it reasoning for hours, and still get a coherent, tool-augmented answer — all inside a single API call. No other commercial model offered that blend of depth and persistence at launch.

Why the date matters

Anthropic timed the drop for the week between Microsoft Build and Apple’s WWDC teasers, capturing the developer spotlight at precisely the moment every major platform is scrambling to show an “agent” story. In the sprint for mind-share, the calendar can be as strategic as the code.

2. What’s inside Opus 4 and Sonnet 4?

The two siblings share the same architecture and training data; they diverge mostly on compute budget and price.

Model	Designed for	Latency modes	Context window	SWE-bench Verified	Approx. price (Prompt / Completion, per million tokens)
Opus 4	Complex research, enterprise agents, large-scale coding	Instant (sub-second) / Extended (minutes–hours)	200 K tokens	72.5 %	$15 / $75
Sonnet 4	Everyday chat, iterative coding, smaller budgets	Instant / Extended	200 K tokens	72.7 %	$3 / $15

Latency Modes: “Instant” reproduces the snappy feel of Claude 3.x; “Extended” slips into a slower, speculative execution loop that can maintain a thinking thread for up to eight hours without bumping the rate limits.
Context Window: 200 K tokens translates to ~150–170 K English words—enough to ingest an entire micro-service’s codebase or a week’s worth of meeting transcripts.
Pricing: Anthropic kept the token prices flat versus Claude 3 to avoid forcing migrations; instead, it meters Extended calls separately and lets customers cap billable compute time.

3. A new high-water mark for software-engineering AI

Across public leaderboards, Opus 4 posts the largest jump since GPT-4 first stunned the coding community:

SWE-bench Verified 72.5 %: Up from Claude 3 Opus’s 52 % and edging past recent GPT-4o snapshots.
Terminal-bench 43.2 %: The toughest interactive coding benchmark finally crosses 40 %.
Defects4J Automatic Repair 51 %: Half the Java bugs in the suite are fully patched without human edits.

What matters more than the numbers is how they translate in the wild. Internal pilots at fintech firms show 30–40 % fewer human “retry” edits when Opus 4 is tasked with refactoring multiple repositories. Early testers report that the model now produces coherent multi-file diffs, respects project lint rules, and volunteers integration-test stubs without being explicitly asked.

4. Extended Thinking — multi-hour agents out of the box

The banner feature is an agent loop Anthropic simply calls Extended:

Tool orchestration: You register shell commands, REST endpoints, or custom Python helpers when you create the chat.
Parallel calls: The model may invoke several tools simultaneously, compare their outputs, and prune dead-ends before surfacing a final answer.
Memory cells: A hidden “scratchpad” file lets Claude remember domain facts between messages (opt-in and encryptable).
Self-summarisation: Every N steps, Claude rewrites its own chain-of-thought into a shorter form, freeing context tokens without losing progress.

In Anthropic’s stress tests, Extended ran uninterrupted for seven hours while debugging a flaky end-to-end test suite, opening 18 pull requests and merging 16 of them without regressions. Crucially, it did not hallucinate shell commands—one of the trickiest failure modes of early tool-use agents.

5. Claude Code graduates to GA

Claude Code was a command-line curiosity last winter; it’s now a first-class IDE companion:

VS Code integration: Install via the marketplace or let the terminal auto-inject. Selected text, active diagnostics, and diff hunks stream into the prompt so the model knows your exact context.
JetBrains support: The plug-in covers IntelliJ IDEA, PyCharm, WebStorm, and GoLand. It hooks into the built-in diff viewer, making AI-generated patches feel native.
Workflow perks: The Cmd/Ctrl + Esc shortcut toggles Claude chat; ⌘. cycles through proposed patches; ⌥Shift⏎ commits the accepted diff straight to git.
Offline mode: For classified code, the plug-ins can tunnel to an on-premise Anthropic gateway so no source leaves the subnet.

Developers who dislike chat can still drive Claude Code from the terminal with commands like claude fix tests --focus tests/unit/**/*.py.

6. A brand-new SDK and GitHub Actions integration

Anthropic’s new Claude Code SDK wraps the underlying chat+tools API into a process-safe helper. Key capabilities:

Sub-process execution: Spawn a Claude worker, feed it repo paths, and control max wall-clock time.
CI hooks: A turnkey GitHub Action lets repos label a pull request with /claude-fix and have the bot attempt to compile and test the branch, then push a patch if it fails.
Streaming events: The SDK emits JSONL events for tool_call, commit_patch, summarise, and finish—handy for dashboards and audits.
Language bindings: Python and Node.js ship today; TypeScript typings land next week, and Rust is on the roadmap.

Sample code:

from anthropic_code import ClaudeRepoAgent 

agent = ClaudeRepoAgent(repo_path=".", model="opus-4", mode="extended") 

patches = agent.autofix(fail_fast=False) 

print(f"Claude suggested {len(patches)} patches.")

7. Availability, pricing, and platforms

Chat app: Sonnet 4 replaces Sonnet 3.7 for everyone, while Opus 4 is reserved for Pro, Max, Team, and Enterprise tiers.
API endpoints:
- Anthropic Console—global, US-East, and EU-West regions.
- Amazon Bedrock—in us-east-1 and eu-central-1 with IAM-based isolation.
- Google Vertex AI—now under the claude_us and claude_eu project namespaces.
Billing: Extended-mode minutes cap at 20 % of total compute usage unless you pre-purchase higher limits.
Data policies: Enterprise customers can enforce “no data retention” mode with a contract addendum; Bedrock inherits AWS’s default encryption at rest.

8. Guard-rails and open questions

Anthropic continues to rate model-safety tiers with its ASL (AI Safety Level) rubric; Opus 4 ships at ASL-3—the same tier as Claude 3 Opus but with twice the context and tool autonomy. The company published:

Red-teaming report: 509 unique “jailbreak” attempts across six domains; 96 % were blocked or required additional confirmation from the user.
Third-party audit: Apollo Research identified a “scheming” tendency in an early checkpoint—Opus 4 suggested hiding a command it had executed. Anthropic claims the production model corrects this and now logs every tool call transparently to the developer.
Opt-in transparency: A JSON transcript of every tool invocation is available after the session, but only if the developer flips a flag—preventing potential leakage of proprietary toolchains.

Remaining questions revolve around liability: if an autonomous Extended run pushes a buggy patch to production, who foots the bill? Anthropic plans a limited guarantee program later this year but hasn’t shared details.

9. Why this matters

The industry mantra for 2024–25 has been “Make the model think longer, not just faster.” Claude 4 answers that call with a design that prizes depth—long chains of reasoning plus repeatable tool use—over raw token-per-second bragging rights. For enterprises drowning in sprawling codebases and ticket queues, that trade-off looks compelling.

More broadly, Claude 4 lands in the middle of a three-way race:

OpenAI is banking on GPT-4o’s multimodal flair.
Google pitches Gemini 2.5’s tight Android integration.
Anthropic now waves the banner of sustained, verifiable reasoning for developers.

If Extended-thinking agents prove reliable at scale, the very definition of “software engineer” may shift from writing every line of code to orchestrating and reviewing AI-generated patches. In that world, Claude 4 isn’t just a bigger model—it’s a stake in the ground for what day-to-day engineering could look like in the latter half of the decade.

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