Multi-model experimentation
Explore Google models from one interface, including Gemini for text and multimodal tasks, Nano Banana for image generation and editing, Veo for video, Lyria for music, and text-to-speech models.
Google AI Studio is a browser-based development environment for experimenting with Google’s generative models and moving prompts into applications through the Gemini API. It supports developers building text, image, video, audio, and agent experiences.
Google AI Studio is a development environment for exploring Google’s generative models and building applications with the Gemini API. It brings prompt experimentation, model access, API-key management, and documentation into one workflow, with support for Gemini, Nano Banana, Veo, Lyria, and text-to-speech models.
The platform is intended for developers who need to test model behavior before integrating it into software. It covers multimodal generation and analysis, conversational agents, real-time interactions, structured outputs, function calling, and managed agent workflows.
Explore Google models from one interface, including Gemini for text and multimodal tasks, Nano Banana for image generation and editing, Veo for video, Lyria for music, and text-to-speech models.
Build workflows that generate text, images, video, and speech or analyze images, videos, documents, and other supported inputs. The documentation describes long-context input and PDF processing of up to 1,000 pages.
Start with an API key and use the Gemini API through official SDKs for Python, JavaScript, Go, Java, and C++, as well as REST. API keys and resource usage can be managed from the product.
Use the Interactions API for stateful, multi-turn interactions with managed tool execution and history. Available tools include Google Search, Google Maps, URL Context, Code Execution, Computer Use, and function calling.
Constrain responses to JSON for automated processing, connect models to external APIs with function calling, and create real-time voice applications with the Live API.
Browse an app gallery and remix projects covering examples such as language learning, background removal, garden design, multiplayer games, and interactive visual applications.
Test prompts and model behavior for applications that combine text with images, video, documents, or audio before connecting the workflow to a product through the Gemini API.
Use stateful interactions, managed history, tool execution, and the Live API to develop assistants that handle multi-turn conversations or real-time voice interactions.
Return JSON-formatted model responses and use function calling to connect generated results with external APIs, business logic, or other software systems.
Use managed agents in a hosted sandbox where Gemini can plan tasks, search the web, run code, and create files, or start from the prebuilt Antigravity agent.
Use the app gallery and remixable projects as starting points for experiments such as language learning tools, background removal, games, and location- or weather-based visual apps.
It is used to experiment with Google’s generative models and build applications with the Gemini API. The workflow covers prompt testing, model selection, API access, multimodal capabilities, agents, and example projects.
The site lists Gemini models alongside Nano Banana for image generation and editing, Veo for video, Lyria for music, and text-to-speech and transcription capabilities. Supported workflows can generate or analyze text, images, video, documents, and audio depending on the model and API.
Developers can create an API key and use the Gemini API through Python, JavaScript, Go, Java, or C++ SDKs, or through REST. The platform also documents the Interactions API for stateful interactions and managed tool execution.
Yes. The pricing documentation describes a free tier with free input and output tokens, Google AI Studio access, and limited access to certain models. Paid and enterprise options are available for higher limits and additional production or organizational features.
The documentation lists Google Search, Google Maps, Code Execution, URL Context, Computer Use, and function calling. Managed agents can use tools while planning and completing tasks in a hosted sandbox environment.
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