Whether you are iterating on a quick bug fix or planning a complex migration, different tasks call for different models.
In keeping with Google Cloud’s commitment to an open ecosystem and to give developers the right model for every job, Claude Opus 5.5 and Claude Sonnet 5.5 are now available in Google Antigravity for Google Cloud customers. Claude Opus 5.5 is built for complex work while Claude Sonnet 5.5 is a faster, lower-cost complement.
Once enabled by an administrator, developers can select Claude Opus 5.5 and Sonnet 5.5 directly from the model picker. Administrators can also select Google’s Gemini models, including Gemini 3.8 Flash and Gemini 4 Argon. The models apply across Antigravity 2.0, Antigravity CLI and our recently released Antigravity IDE extensions for VS Code, JetBrains IntelliJ, and Visual Studio. This lets you choose the right model for the job, under a unified enterprise billing and security boundary.
In this post, we’ll share two engineering patterns for building in Antigravity using these models. To view the entire list of models supported in Antigravity across subscriptions, see our documentation here.
Multi-model engineering patterns in Antigravity
Having multiple model families available inside the same agent harness unlocks practical multi-model workflows that improve code quality while controlling latency and cost.
Pattern 1: Cross-model verification (“LLM-as-a-Judge”) in loop and graph workflows
When building agentic loops or multi-step graph workflows, using the same model to both write code and review its own output can reinforce model-specific blind spots. Pairing two distinct model families, one as the implementer and another as the validator (judge), provides independent verification before moving to the next stage of a workflow.
In Antigravity, you can run this pattern either interactively or via automated subagents:
- Plan and implement with Model A: Start in planning mode using Claude Opus 5.5 or Gemini 4 Argon to design and implement a multi-file change.
- Validate with Model B: Before committing or advancing the loop, switch models, or invoke a one-shot /model check in the CLI, to have a different model family critique the implementation against your test suite and requirements.
Pattern 2: Pairing reasoning models with Flash subagents
Complex engineering tasks often combine a few high-reasoning decisions with dozens of high-volume, mechanical lookups (searching files, grepping logs, checking lint output, or classifying test failures). Running every lookup on a frontier model can increase both latency and spend.
Antigravity’s Subagent customization system (.agents/agents/*.md) lets you assign specific model tiers (inherit, flash, or pro) to specialized subagents. When your primary session is running a more powerful model.
Subagents configured with model: inherit use your active session model for deep reasoning subtasks.
Subagents configured with model: flash offload high-speed search, classification, and triage work to Gemini Flash models.
For example, you can define a fast log-triage subagent in .agents/agents/test-triager.md:
