No, Gemini CLI cannot be used offline in its current implementation. The tool requires an active internet connection because the AI processing occurs on Google’s cloud infrastructure rather than locally on your machine. While the CLI interface runs locally and provides the interactive terminal experience, all the actual AI model inference happens on Google’s servers. This cloud-based architecture is what enables Gemini CLI to provide access to powerful models like Gemini 2.5 Pro with its massive 1 million token context window without requiring users to have high-end hardware capable of running such large models locally.
The online requirement extends beyond just the AI processing - many of Gemini CLI’s powerful features depend on internet connectivity. The Google Search integration for grounding prompts with real-time information requires web access, as do most MCP server integrations that connect to external services like GitHub, databases, or APIs. Authentication with your Google account or API keys also requires network connectivity for initial setup and token refresh operations. Additionally, the tool’s ability to access up-to-date information and current best practices relies on its connection to Google’s continuously updated model serving infrastructure.
However, there are hints about potential future offline capabilities. Google engineers have indicated that they hope to support local models in the future, potentially including smaller Gemini-based models like Gemma that could run on consumer hardware. The CLI’s architecture is described as “model-agnostic,” which suggests it could theoretically be adapted to work with local model backends. Such a development would align with industry trends toward hybrid AI deployments where users can choose between cloud-based models for maximum capability and local models for privacy or offline scenarios. Until such capabilities are implemented, users who need offline AI assistance would need to consider alternative tools that support local model execution, though they would lose access to Gemini CLI’s specific features and Google’s advanced model capabilities.