Gemini 3で開発を始める：開発者向け新ツール群を発表 Start building with Gemini 3

Google DeepMind has announced Gemini 3, its newest flagship model, and made it broadly available to developers across its cloud and AI tooling stack. The release emphasizes stronger reasoning, multimodal understanding, and—perhaps most notably—a clear orientation toward agentic application development.

Developers can access Gemini 3 through Google AI Studio, Vertex AI, and the Gemini API, plugging directly into existing Google Cloud workflows. Alongside these familiar surfaces, Google introduced a new platform called Antigravity, positioned as an environment for building, testing, and deploying AI agents. While details are still emerging, Antigravity appears intended to help developers design multi-step autonomous workflows that may involve browser actions, tool calls, and code execution—areas where simply having a strong base model is no longer sufficient.

On the technical side, Google highlights gains in long-context handling, code generation, and visual reasoning, with particular emphasis on tasks that require planning and tool use. These are exactly the capabilities that matter for agents, which must decompose goals, choose tools, and recover from errors over extended interactions. Although third-party benchmark verification will take time, the messaging signals that Google sees agentic performance, rather than raw chat quality, as the differentiator going forward.

The launch lands in an increasingly crowded field. OpenAI has been pushing its Operator and Agent Builder offerings, Anthropic has rolled out Computer Use and the Model Context Protocol, and Meta continues to release open-weight Llama models that anchor a parallel developer ecosystem. Against that backdrop, Antigravity can be read as Google's serious entry into the agent-tooling layer, complementing its model lineup with infrastructure that competitors have been steadily building out.

For enterprises evaluating which stack to adopt, the decision is shifting beyond model accuracy alone. Tool integrations, evaluation frameworks, observability, latency, pricing, and safety guardrails all increasingly shape procurement. Google's advantage lies in tight coupling with Workspace, Search, and Cloud, while challengers compete on openness, specialized agent primitives, or aggressive pricing. It remains to be seen how Gemini 3 and Antigravity perform in real production deployments, but the announcement suggests Google intends to compete aggressively in the agent era rather than cede that frontier.

Developers interested in evaluating the model can begin in AI Studio for quick prototyping or move to Vertex AI for managed enterprise deployment. Those building autonomous agents are the clearest target audience, and early experimentation will likely reveal where Gemini 3's reasoning and tool-use improvements translate into practical reliability gains.