Recently, tech giant Google officially launched an independently developed Gemini CLI tool to the developer community, which has caused heated discussions in the developer circle. At the heart of this command line interface tool is the integration of advanced AI Q&A and content generation capabilities, designed to enhance developers’ capabilities through artificial intelligence technologies, thereby significantly improving their productivity 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 has the ability to complete complex and large-scale data processing tasks. More importantly, it has in-depth integration with Gemini Code Assiss Code Assistan and introduces the Model Context Protocol (MCP), while also integrating Google Search capabilities. This means developers can enjoy the convenience of AI in many areas such as programming, content creation, task management, and problem solving. Compared with traditional coding methods, Gemini CLI undoubtedly provides a smarter and more effective solution.
Although the Gemini CLI is currently in the preview stage, Google has released a free Gemini Code Assist license to developers, which can be obtained by simply using a personal Google account. The industry sees this move as an important step for Google to mine its AI models into its developer workflow. It also directly benchmarks OpenAI’s Codex CLI and Anthropic’s Claude code, and competition is emerging. Provide a free license, use lower bars for developers and help them experience and evaluate the value of the tool more easily.
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 cursors 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 much more than code generation. It can also generate videos with Google WEO 3 models and use in-depth research agents to generate research reports, connect to Google search real-time information, and even connect to external databases, enabling information integration and effective utilization. This versatility makes Gemini CLI more than just a coding tool, it is more like a comprehensive AI assistant.
To promote the co-development of the entire AI ecosystem, Google chose to open source Gemini CLI with the Apache 2.0 loose license and encourage developers to actively participate in project contributions on the Github platform. Google also shows a considerable quota of sincerity resources: Free users can start 60 model requests per minute, limiting up to 1,000 per day. Given the average usage of developers, it can be said that such quotas are very 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. Additionally, some studies point out that AI-generated code may introduce errors and may even be difficult to resolve security vulnerabilities. Despite the huge potential of AI coding tools, these issues also require the industry to work together to ensure they can truly empower developers, rather than bring potential risks.
