Google AI Studio
AIPopularWeb-based platform from Google to build, fine-tune, prototype and deploy applications using Gemini and related multimodal models.
-(0 Reviews)
Free Available
Starting from Free
Premium plans available
Google AI Studio
AIPopular
Web-based platform from Google to build, fine-tune, prototype and deploy applications using Gemini and related multimodal models.
-(0 Reviews)
Free Available
Starting from Free
Premium plans available
About Google AI Studio
Google AI Studio is a web-based development and experimentation environment that connects creators to Google's Gemini family of large multimodal models and related services. It provides an interface for prompt engineering, model fine-tuning, prototyping applets, and integrating model capabilities (text, image, audio, video, tool/function calling) into apps. Studio supports starter applets and local development workflows (using a Gemini API key), and can be used together with Google Cloud Vertex AI for enterprise-scale deployment. Its value is in shortening the path from prompt to production by combining model access, multimodal features and developer-oriented tooling in one platform.
Screenshots
+
Key Features
Prompt-to-Production Workflow: Integrated UI and tooling to iterate on prompts, build prototype applets and move prototypes toward production-ready deployments with Gemini models.
Multimodal Model Access: Native access to Gemini model capabilities including text, image, audio and video modalities and the Live API (audio/video streaming) for interactive multimodal experiences.
Fine-Tuning and Custom Models: Ability to fine-tune base models for custom tasks and datasets (community reports indicate free fine-tuning options within Studio), enabling tailored performance for domain-specific use cases.
Starter Applets and Local Development: Official starter applets (React-based) that run inside AI Studio and can be run locally by inserting a Gemini API key, accelerating building of map, video, and interactive demos.
Function Calling and Tooling Integration: Support for function calling, code execution, and integrated Google search grounding to let models call external APIs (e.g., Maps Embed) and execute external actions.
Media Generation & Plugins: Access to media generation (Imagen, Veo) and model features that produce or manipulate images, video, and other media formats for richer applications.
Vertex AI Compatibility: Compatibility with Google Cloud Vertex AI for enterprise developers who need managed infrastructure, scaling, and enterprise-grade deployment options.
Examples, Cookbook & SDKs: Official example repositories and SDK guides (Gemini cookbook) to demonstrate quickstarts, LiveAPI usage, and multi-feature integrations for developers.
Interactive web IDE for prompting and testing Gemini models
Fine-tuning and customization of base models (free fine-tuning options mentioned)
Starter applets and templates (React-based) that run inside AI Studio
Integration with Gemini API and Vertex AI APIs for training and deployment
Support for function calling / invoking external APIs (e.g., Maps Embed API)
Demonstrations of 2D and 3D spatial understanding and reasoning
Local development workflow using environment (.env) files with Gemini API key
Tooling for building AI agents and multi-component applications
Works with regional Vertex AI deployments (EU / UK compatibility noted)
Use Cases
Prompt engineering and rapid prototyping: Iteratively design and test prompts and conversational flows for Gemini, then package prototypes into small applets or demos.
Custom fine-tuned models for domain tasks: Fine-tune Gemini models on proprietary datasets (text, images) to improve performance on customer support, legal summarization, or specialized classification.
Multimodal interactive apps: Build applications that combine video/audio/image understanding with text reasoning (e.g., video event exploration, spatial mapping with embedded maps) using starter applets and LiveAPI.
Tool-enabled assistants: Create assistants that execute functions, call external APIs (like Maps Embed), run code, and ground answers with Google search or other tools for accurate, actionable outputs.
Media generation and content creation: Generate and edit images or short video snippets using integrated media models (Imagen, Veo) for marketing, creative workflows, or automated asset creation.
Enterprise deployment via Vertex AI: Move prototypes from Studio into managed, scalable production deployments on Google Cloud Vertex AI for enterprise-grade reliability and compliance.
Rapid prototyping of LLM-powered apps and agents
Fine-tuning base models for domain-specific tasks
Building spatially-aware applications (2D/3D reasoning, video event exploration)
Integrating LLMs with external services (maps, embeds, other APIs) via function calling
Educational tutorials and starter projects for developer onboarding
Local development and testing of Gemini-powered frontend apps
