Google Cloud just expanded the Vertex AI Model Garden, bringing Anthropic’s latest and greatest into the fold: Claude Opus 4 and Claude Sonnet 4. If you’ve been following the slow-burning AI arms race, you know both names carry weight—Opus is the heavyweight champ, while Sonnet offers a nimble, cost-sensitive alternative. Here’s what makes this launch more than just another “add to cart” moment for developers and enterprises alike.
Anthropic’s Claude models lean into the hybrid-reasoning approach: rapid “snap answers” when you need them, and a more deliberate “extended thinking” mode for deeper dives. That means you can toggle between near-instant responses and multi-step reasoning sessions without swapping tools. For teams juggling everything from live customer chatbots to complex research agents, that flexibility is a game-changer.
Opus 4 isn’t just a speed bump on the development highway—it’s a full-blown coding marathon runner. In internal tests, Anthropic found Opus 4 ran continuously for nearly seven hours on autonomous coding tasks, dwarfing the previous record of 45 minutes from Sonnet 3.7. And according to benchmarks, it handily outperforms Google’s Gemini 2.5 Pro, OpenAI’s o3 reasoning, and GPT-4.1 in coding and tool-use challenges.

Typical use cases for Opus 4 include:
- Advanced coding workflows that require sustained context (think full-stack feature builds or refactors).
- Autonomous AI agents that conduct research, data extraction, or orchestrate multi-step processes without human babysitting.
- Complex problem solving and long-running jobs where continuity and precision matter (e.g., content management pipelines).
If you need serious horsepower but aren’t ready to break the bank, Sonnet 4 is your ticket. This mid-size model bridges the gap between performance and cost, outperforming its own predecessor (Sonnet 3.7) in both coding and reasoning while following prompts with sharper precision. It’s the model you pick for:
- Code reviews and bug triage, where accuracy and turnaround time count.
- AI-powered assistants that handle document summarization, email drafting, or research briefs.
- Large-scale content generation—from marketing copy to data-driven analysis—where volume and quality need to balance.
On Vertex AI, both Claude Opus 4 and Sonnet 4 arrive as a turnkey Model-as-a-Service (MaaS). Google Cloud’s Model Garden already boasts over 200 foundation models, but this new addition signals a deeper partnership with Anthropic and a bet on hybrid reasoning for enterprise use cases.
Key benefits include:
- Agent orchestration: Use Google’s Agent Development Kit (ADK) or your own framework to spin up multi-agent systems, all managed through Vertex’s Agent Engine.
- BigQuery ML hooks: Call out to Claude directly from SQL for on-the-fly generation, summarization, or classification in your data warehouse.
- Provisioned throughput: Lock in dedicated capacity and predictable costs for mission-critical workloads.
- Batch predictions & caching: Handle high-volume inference with batch APIs and smart caching to keep latency low and budgets in check.
- Global endpoints (public preview): Dynamically route requests to the nearest region for ultra-low latency.
- Enterprise security: Google’s compliance guardrails, VPC Service Controls, and audit logging come baked in.
Anthropic’s roadmap hints at even more specialized models down the line, along with features like “thinking summaries” to surface the chain of thought behind complex answers, and a beta “extended thinking” mode that dynamically balances reasoning depth with tool invocation. Meanwhile, Google is busy layering in deeper integrations—expect tighter BigQuery, Vertex Pipelines, and Looker Studio connectors in the coming months.
For teams evaluating LLMs, this dual offering on Vertex AI means you don’t have to choose between raw power and cost efficiency—you get both under one roof, managed by Google Cloud. Whether you’re a hack-and-slash startup or a security-obsessed enterprise, Claude Opus 4 and Sonnet 4 have landed on Vertex AI, ready to turbocharge your workflows.
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