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Google Antigravity v0.1.11

Released · Google

Models:Makes Gemini 3.7 Flash the default

What the release notes say

0.1.11 August 11, 2026 Default Gemini 3.7 Flash upgrade, session budget limits, Vertex AI Express Mode, and autonomous behavior modes The 0.1.11 release updates the default model to gemini-3.7-flash , introduces session-level budget enforcement and turn termination stop reasons, Vertex AI Express Mode authentication, and an autonomous agent behavior setting. It also expands tool hook metadata, resolves string annotation coercion for postponed evaluation, and improves MCP server and subagent stability. Improvements (6) Default Model Upgrade to Gemini 3.7 Flash : Upgraded the default inference model to gemini-3.7-flash . Session Budget Enforcement & Stop Reasons : Added BudgetConfig to define session-level usage limits (total tokens, turns, and cost) and StopReason enum ( BUDGET_EXCEEDED , TURN_LIMIT , USER_CANCELLED , etc.) to inspect turn termination causes. Vertex AI Express Mode Support : Added native support for Express Mode authentication via VertexEndpoint(api_key=...) and LocalAgentConfig(vertex=true, api_key=...) , simplifying headless and non-GCP deployments. Autonomous Agent Behavior Mode : Control the agent's behavior with AgentBehavior . By default the SDK now has an AgentBehavior.AUTONOMOUS mode (previously AgentBehavior.INTERACTIVE ) to streamline scripting, background, and headless interaction modes. Override by setting CapabilitiesConfig(agent_behavior=AgentBehavior.INTERACTIVE) . Multi-Interface Hook Registration : Enabled single-instance registration across multiple hook interfaces ( PreToolHook , PostToolHook , PreTurnHook ), allowing for cross-functional instrumentation without duplicate invocations. PreToolArgs Metadata : Exposed trajectory_id and step_index on tool hook payloads for chat thread context tracing. Fixes (4) ToolRunner String Annotation Coercion : When using from future import annotations , tool argument coercion failed on stringified types; resolved by resolving type annotations via typing.get_type_hints before type adaptation.