Recently, technology giant Google officially launched the independently developed Gemini CLI tool to the developer community, which has caused heated discussions in the developer circle. The core of this command line interface tool is the integration of advanced AI Q&A and content generation capabilities, aiming to empower developers through artificial intelligence technology, thereby significantly improving their work efficiency and user experience.
The heart of Gemini CLI is its powerful Gemini 2.5 Pro inference model. The model has the ability to process up to 1 million token context information and is competent for complex and massive data processing tasks. More importantly, it is deeply integrated with the Gemini Code Assist code assistant and introduces the Model Context Protocol (MCP), while also integrating Google Search capabilities. This means that developers can enjoy the convenience brought by AI technology in many fields such as programming, content creation, task management, and problem solving. Compared with traditional encoding methods, Gemini CLI undoubtedly provides a smarter and more efficient solution.
Although the Gemini CLI is currently in the preview stage, Google has opened a free Gemini Code Assist license to developers, which can be obtained by simply using a personal Google account. This move is seen by the industry as an important step for Google to promote the deep integration of AI models into the developer workflow. It also directly benchmarks OpenAI’s Codex CLI and Anthropic’s Claude Code and the competitive situation is emerging. The provision of free use licenses lowers the threshold for developers and helps them to experience and evaluate the value of the tool more conveniently.
Since the release of the Gemini 2.5 Pro model in April this year, Google’s AI technology has attracted widespread attention from the developer community. This not only promotes the popularity of third-party AI programming tools such as Cursor and GitHub Copilot, but also reflects Google’s determination to strengthen direct contact with developers. It is worth mentioning that the functions of Gemini CLI are far more than code generation. It can also generate videos in conjunction with Google Veo 3 model, and use the Deep Research agent to produce research reports, connect to Google search to obtain real-time information, and even connect to external databases, thereby achieving information integration and efficient utilization. This versatility makes Gemini CLI more than just a coding tool, it is more like a comprehensive AI assistant.
In order to promote the common development of the entire AI ecosystem, Google chose to open source Gemini CLI with the Apache 2.0 loose license, and encouraged developers to actively participate in project contributions on the GitHub platform. In terms of resource quotas, Google has also shown considerable sincerity: free users can initiate 60 model requests per minute, with a daily limit of up to 1,000. Considering the average usage of developers, such a quota can be said to be quite generous, which undoubtedly provides great convenience for developers.
It is worth noting that with the rapid popularity of AI coding tools, the industry’s trust in it has gradually surfaced. According to a survey conducted by Stack Overflow in 2024, only 43% of developers recognize the accuracy of AI tools. In addition, several studies have pointed out that AI-generated code may introduce errors and even difficult to fix security vulnerabilities. While AI coding tools have great potential, these problems also require the industry to work together to ensure they can truly empower developers rather than bring potential risks.
