// news · tools · agents2026-05-29source: google cloud / google blog / heygotrade

Google Antigravity 2.0 reaches general availability alongside Gemini Enterprise Agent Platform — enterprise agent-runtime tooling consolidates around Vertex AI

Google's Antigravity 2.0 reached general availability alongside Gemini Enterprise Agent Platform in the I/O 2026 release window. The combined offering positions Vertex AI as the enterprise agent-runtime and tooling consolidation point for Gemini-family deployments. Business users can start using Gemini 3.5 Flash in the Gemini Enterprise app to discover, create, and use AI workflows. Partners including Macquarie Bank, Shopify, and Salesforce are deploying production workflows.

The platform-consolidation substance is the operational piece. Through 2024-2025 Google's enterprise-AI offering was distributed across Vertex AI (model API), Google Cloud's agent tooling, and the consumer-Gemini surface — each with somewhat-different integration patterns. Antigravity 2.0 GA plus Gemini Enterprise Agent Platform consolidates the enterprise-AI surface around a single procurement-integration point: developers use Antigravity for build-and-iterate workflows, business users access Gemini Enterprise for app-level deployment, both run on Vertex AI infrastructure with the same model versions. The procurement simplification matters for enterprise IT departments evaluating Gemini-family deployments against the Anthropic-on-AWS and OpenAI-on-Azure procurement paths.

The competitive context is the enterprise-AI platform race. Gemini 3.5 Flash GA at $1.50/$9 per 1M tokens is the model-tier capability that the platform consolidates around. Microsoft's Agent 365 enterprise SASE rollout is the Microsoft-side enterprise-AI platform consolidation. The combined Q2 2026 evidence is that hyperscaler enterprise-AI platforms are consolidating around per-platform-distinct integration patterns — Vertex AI for Google, Azure AI Foundry for Microsoft, AWS Bedrock for Anthropic-as-default — with the procurement question being which platform integration most closely matches the existing enterprise infrastructure rather than which model is best in absolute terms.

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