- Developers & Coders: Debug code, generate features, and manage repos conversationally.
- DevOps Engineers: Automate workflows, CI/CD pipelines, and operational tasks.
- Researchers & Analysts: Perform deep dives with Search grounding and file analysis.
- Content Creators: Generate text, images, or videos via extensions from terminal.
- Teams & Enterprises: Deploy with custom configs, telemetry, and trusted folders.
How to Use Gemini CLI?
- Install the Tool: Run `npm install -g @google/gemini-cli` and authenticate with Google.
- Launch & Chat: Type `gemini` in terminal, use natural prompts or slash commands like /help.
- Handle Tasks: Query codebases, create issues, debug with ReAct loop and tools.
- Customize & Extend: Add GEMINI.md context, custom commands, or MCP servers.
- Terminal AI Agent: Full Gemini 3 power with ReAct for autonomous task completion.
- Multimodal Generation: Builds apps from images/PDFs, extends to Veo/Imagen via MCP.
- Checkpointing & Headless: Save sessions, script automations without UI.
- Sandbox Security: Isolated execution for safe tools and untrusted code.
- Context Awareness: GEMINI.md files and token caching for efficient projects.
- Supercharges terminal for coding, debugging, and automation.
- Open-source with easy npm install and free access.
- ReAct loop handles complex multi-step tasks smartly.
- Extensions unlock video, image gen from command line.
- Learning curve for advanced commands and configs.
- Rate limits on free tier for heavy usage.
- Sandbox may slow some executions.
- Docs still evolving in preview phase.
Free
Free
Great for getting started and exploring Gemini CLI
Authenticate instantly with your Google Account
Google AI Pro
Custom
Everything in the free version, plus:
Higher usage limits for Gemini CLI and other AI tools
Gemini in Gmail, Docs, Vids, and more; plus Cloud Storage
Google AI Ultra
Custom
Everything in Google AI Pro, plus:
Highest usage limits for our most capable models
Access to Deep Think for complex reasoning through Gemini App
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Agent Development Kit (ADK) is a flexible, open-source framework from Google for developing and deploying AI agents, optimized for Gemini and the Google ecosystem but model-agnostic and compatible with other frameworks. It treats agent development like software engineering with modular components for single or multi-agent systems, supporting hierarchical coordination, LLM-driven delegation, and rich tools including pre-built like search and code execution, custom functions, third-party integrations, and agents as tools. Developers benefit from workflow orchestration via Sequential, Parallel, Loop agents or dynamic LlmAgent transfer, built-in evaluation of responses and trajectories, native multimodal streaming for text/audio, CLI and Developer UI for debugging/visualization, containerized deployment to Vertex AI Agent Engine, Cloud Run, or Docker, and security patterns for safe agents. Available in Python, TypeScript, Go, Java with quick starts.
Agent Development Kit (ADK) is a flexible, open-source framework from Google for developing and deploying AI agents, optimized for Gemini and the Google ecosystem but model-agnostic and compatible with other frameworks. It treats agent development like software engineering with modular components for single or multi-agent systems, supporting hierarchical coordination, LLM-driven delegation, and rich tools including pre-built like search and code execution, custom functions, third-party integrations, and agents as tools. Developers benefit from workflow orchestration via Sequential, Parallel, Loop agents or dynamic LlmAgent transfer, built-in evaluation of responses and trajectories, native multimodal streaming for text/audio, CLI and Developer UI for debugging/visualization, containerized deployment to Vertex AI Agent Engine, Cloud Run, or Docker, and security patterns for safe agents. Available in Python, TypeScript, Go, Java with quick starts.
Gemini File Search
Gemini File Search is a fully managed Retrieval Augmented Generation (RAG) tool in the Gemini API that simplifies grounding AI responses in your private data by automatically handling file upload, chunking, embedding with Gemini models, indexing, and semantic retrieval for accurate, context-aware answers. Developers create persistent File Search stores to hold embeddings indefinitely, upload files directly or via Files API supporting formats like PDF, DOCX, TXT, JSON, code files, and more up to 100MB each, with custom chunking configs for optimal retrieval. It provides citations linking responses to source chunks for verification, metadata filtering for targeted searches, structured outputs for JSON schemas, and integrates seamlessly into generate Content calls without other tools. Free storage and query-time embeddings make it cost-effective, charging only initial indexing ($0.15/1M tokens) plus input/output tokens, with limits scaling by tier up to 1TB for enterprises.
Gemini File Search
Gemini File Search is a fully managed Retrieval Augmented Generation (RAG) tool in the Gemini API that simplifies grounding AI responses in your private data by automatically handling file upload, chunking, embedding with Gemini models, indexing, and semantic retrieval for accurate, context-aware answers. Developers create persistent File Search stores to hold embeddings indefinitely, upload files directly or via Files API supporting formats like PDF, DOCX, TXT, JSON, code files, and more up to 100MB each, with custom chunking configs for optimal retrieval. It provides citations linking responses to source chunks for verification, metadata filtering for targeted searches, structured outputs for JSON schemas, and integrates seamlessly into generate Content calls without other tools. Free storage and query-time embeddings make it cost-effective, charging only initial indexing ($0.15/1M tokens) plus input/output tokens, with limits scaling by tier up to 1TB for enterprises.
Gemini File Search
Gemini File Search is a fully managed Retrieval Augmented Generation (RAG) tool in the Gemini API that simplifies grounding AI responses in your private data by automatically handling file upload, chunking, embedding with Gemini models, indexing, and semantic retrieval for accurate, context-aware answers. Developers create persistent File Search stores to hold embeddings indefinitely, upload files directly or via Files API supporting formats like PDF, DOCX, TXT, JSON, code files, and more up to 100MB each, with custom chunking configs for optimal retrieval. It provides citations linking responses to source chunks for verification, metadata filtering for targeted searches, structured outputs for JSON schemas, and integrates seamlessly into generate Content calls without other tools. Free storage and query-time embeddings make it cost-effective, charging only initial indexing ($0.15/1M tokens) plus input/output tokens, with limits scaling by tier up to 1TB for enterprises.
Editorial Note
This page was researched and written by the ATB Editorial Team. Our team researches each AI tool by reviewing its official website, testing features, exploring real use cases, and considering user feedback. Every page is fact-checked and regularly updated to ensure the information stays accurate, neutral, and useful for our readers.
If you have any suggestions or questions, email us at hello@aitoolbook.ai