In June 2025, Google launched Gemini CLI, a free, open-source AI agent powered by Gemini 2.5 Pro, transforming how developers work in the terminal. This tool integrates advanced AI capabilities directly into command-line interfaces, offering a generous free tier of 60 requests per minute and 1,000 per day. Gemini CLI is designed to streamline coding, automation, and multimedia tasks, making it a versatile tool for developers. As AI-driven tools like GitHub Copilot and Claude Code gain popularity, Gemini CLI stands out with its multimodal features and open-source transparency. This blog explores its latest updates, features, and impact on the developer ecosystem.

Released in public preview on June 25, 2025, Gemini CLI introduces powerful features for developers across Windows, macOS, and Linux. Key updates include:

Gemini 2.5 Pro Integration: Powered by a 1-million-token context window, it handles large codebases and complex specifications effortlessly.
Generous Free Tier: Offers 60 requests per minute and 1,000 per day for individual developers, doubling Google’s internal usage averages. [Source] Open-Source: Licensed under Apache 2.0, the codebase is open for community contributions on GitHub.
Multimodal Capabilities: Supports image and video generation with Google’s Imagen and Veo models, plus PDF and sketch processing. [Source] Model Context Protocol (MCP): Enables integration with external tools and databases for enhanced functionality.
Google Search Grounding: Fetches real-time web data for contextually relevant responses. [Source] Seamless IDE Integration: Shares technology with Gemini Code Assist for a unified workflow. [Source] Google is actively addressing scaling issues based on community feedback to enhance performance.

1. Setup and Authentication
Install Gemini CLI with Node.js (version 18 or higher) using: npm install -g @google/gemini-cli Authenticate with a Google account for the free tier or use a Google AI Studio/Vertex AI key for advanced features. [Source] 2. Key Capabilities
Code Generation and Debugging: Generate code or debug errors, e.g.: gemini > Create a REST API endpoint for user authentication with JWT tokens Task Automation: Automate tasks like linting with commands in a GEMINI.md file: uvx ruff@latest check –fix . uvx ruff@latest format . Multimodal Tasks: Create media or process PDFs, e.g.: gemini > Make a short video of a ginger cat’s adventures in Australia using Veo Real-Time Research: Fetch current data via Google Search integration. [Source] 3. Customization
Use GEMINI.md files to define project-specific prompts and view context with: /memory show [Source] 4. IDE Integration
Powers agent mode in Gemini Code Assist for seamless terminal-to-IDE workflows.

Gemini CLI boosts productivity with:

Accessibility: Free tier supports students and professionals with 60 RPM/1,000 RPD. [Source] Context-Aware Coding: Handles large codebases with a 1-million-token context window. [Source] Versatility: Supports coding, automation, and multimedia tasks like API documentation or video creation.
Community-Driven: Open-source model encourages contributions via GitHub. [Source] Enterprise Features: Offers usage-based billing and security for teams. [Source] Use Cases:

Solo Developers: Generate code, debug, or prototype apps.
Teams: Standardize workflows with GEMINI.md files.
Non-Coding Tasks: Create technical specs or demo videos.

Gemini CLI competes with tools like OpenAI’s Codex CLI and Anthropic’s Claude Code:

Gemini CLI: Free tier, open-source, 1M token context, multimodal features, Google ecosystem integration. Cons: Preview-stage scaling issues. [Source] OpenAI Codex CLI: Mature, strong code generation, but not fully open-source and has smaller context window.
Anthropic Claude Code: Excels in reasoning, but paid, limited multimodal features, and not open-source.
Gemini CLI’s free tier and multimodal versatility make it a strong contender.

Preview Stage: Scaling issues like “slow response” errors are being addressed. [Source] No Local Model: Relies on cloud-based Gemini 2.5 Pro, limiting offline use.
Learning Curve: Customizing GEMINI.md or MCP requires familiarity with Google’s AI ecosystem.
Enterprise Limits: Higher throughput requires paid plans with unclear pricing. [Source]

Gemini CLI positions Google as a leader in AI-driven development with its free, open-source model and multimodal capabilities. Its integration with Google Cloud, Imagen, and Veo encourages developers to adopt Google’s AI ecosystem. Future enhancements, like local model support or expanded MCP compatibility, could redefine terminal-based AI workflows. [Source]

Gemini CLI empowers developers with a free, open-source AI tool for coding, automation, and multimedia tasks. Despite its preview status, its potential is vast, driven by community contributions. Explore it on GitHub, share feedback, or subscribe to our newsletter for AI tooling updates.