Google unveils Gemini CLI, an open source AI tool for terminals
Google has announced the release of Gemini CLI, a new agentic AI tool that brings its Gemini AI models directly to the terminals where developers work. This tool is designed to be run locally from the terminal, enabling developers to interact with Google's Gemini AI models seamlessly within their coding environments.
Bringing AI Closer to Developers
Gemini CLI allows developers to make natural language requests, such as seeking explanations for complex code segments, generating new features, debugging code, or executing commands. By integrating Google's AI capabilities with local codebases, developers can enhance their coding workflows and streamline their processes.
Competition and Innovation in AI Coding Tools
Google's Gemini CLI joins a suite of AI coding tools offered by the company, including Gemini Code Assist and Jules. This tool competes with other command-line AI tools in the market, such as OpenAI's Codex CLI and Anthropic's Claude Code, known for their ease of integration, speed, and efficiency.
Since the launch of Gemini 2.5 Pro, Google's AI models have gained popularity among developers, driving the usage of third-party AI coding tools like Cursor and GitHub Copilot. In response to this trend, Google aims to build a direct relationship with developers by providing in-house solutions like Gemini CLI.
Extending Functionality Beyond Coding
While Gemini CLI is primarily intended for coding tasks, Google has designed the tool to support a range of functionalities. Developers can leverage Gemini CLI for creating videos using Google's Veo 3 model, generating research reports with the Deep Research agent, accessing real-time information via Google Search, and connecting to external databases through MCP servers.
Open Source and Generous Usage Limits
To encourage adoption, Google has made Gemini CLI open source under the Apache 2.0 license, inviting developers to contribute to the project on GitHub. The company also offers generous usage limits, allowing free users to make 60 model requests per minute and 1,000 requests per day.
Risks and Challenges in AI Coding
While AI coding tools are gaining popularity, concerns about their accuracy and reliability persist. A survey from Stack Overflow revealed that only 43% of developers trust the accuracy of AI tools. Studies have also shown that AI models can introduce errors or fail to address security vulnerabilities, highlighting the importance of vigilance when using such tools.
