gemini-cli vs Goose
gemini-cli vs Goose: a Gemini-only TypeScript terminal agent against a Rust agent with desktop app, CLI, API and 15+ providers.
Updated
short verdict
Pick gemini-cli if you work in the terminal with Google Gemini models and want Google Search grounding, GEMINI.md context files, a free OAuth tier and GitHub Actions integration. Pick Goose if you want to choose between 15+ model providers, use a desktop app alongside the CLI, or embed the agent through its API.
Both tools are open source AI agents that run on your machine, call models, and extend through Model Context Protocol (MCP). They differ in scope. gemini-cli is a terminal agent built around Google Gemini models. Goose is a general-purpose agent with a desktop app, a CLI and an API, and it connects to many providers.
this page is for
- Developers deciding between a Gemini-focused terminal agent and a multi-provider agent
- Teams weighing CI automation against a desktop app and embeddable API
- Readers who need to know which tool fits their model provider setup
The better pick when you want a terminal-only agent on Google Gemini models, with search grounding and GitHub Actions support.
best for
- Terminal-first developers using Gemini models
- CI workflows such as code review and issue triage via GitHub Actions
strengths
- Google Search grounding and web content fetching are built in for real-time information
- GEMINI.md context files tailor behavior per project; checkpointing saves and resumes sessions
- Non-interactive mode with JSON output suits scripts; OAuth free tier gives 60 requests/min and 1,000/day
- Installs via Homebrew, npm (npm install -g @google/gemini-cli) or npx
weaknesses
- Documented around Google Gemini models, with auth via Google OAuth, Gemini API key or Vertex AI
- Terminal only; no desktop app or embeddable API is documented
The better pick when you want provider choice, a desktop app next to the CLI, or an API to embed the agent in other software.
best for
- Developers who switch between model providers or use existing subscriptions
- Organizations that want preconfigured custom distributions
strengths
- Connects to 15+ providers, including Anthropic, OpenAI, Google, OpenRouter, Azure and AWS Bedrock
- Ships as a desktop app for macOS, Linux and Windows, a CLI, and an API
- 70+ extensions through MCP; custom distributions bundle providers, extensions and branding
- Written in Rust; governed under the Agentic AI Foundation at the Linux Foundation
weaknesses
- Documented install is a curl script piped to bash; no Homebrew or npm route is listed
- Broader general-purpose scope; no Google Search grounding or GitHub Actions integration is documented
Key differences
- Models: gemini-cli targets Google Gemini models; Goose supports 15+ providers
- Interface: gemini-cli is a terminal agent; Goose offers a desktop app, CLI and API
- Language: gemini-cli is TypeScript (Apache-2.0); Goose is written in Rust
- Extensions: both support MCP; Goose cites 70+ extensions, gemini-cli adds GEMINI.md context files
- Automation: gemini-cli has JSON output and GitHub Actions integration; Goose offers an embeddable API
- Install: gemini-cli via Homebrew, npm or npx; Goose via a curl install script
Choose gemini-cli when
- You want Google Search grounding and web fetching inside the agent
- You need scripted runs with JSON output or GitHub Actions reviews and issue triage
- You want a free tier through Google account OAuth, or Vertex AI for enterprise use
- You prefer installing with Homebrew or npm
Choose Goose when
- You want to switch between providers such as Anthropic, OpenAI or AWS Bedrock
- You want a desktop app on macOS, Linux or Windows alongside the CLI
- You need an API to embed the agent in your own application
- Your organization wants custom distributions with preset providers and extensions
When not to use these
- You need a hosted IDE assistant with inline completions; both tools are agents that run on your machine, not editor plugins
- You cannot send code to a remote model provider and have no local model setup in place
FAQ
- Which is faster, gemini-cli or Goose?
- Neither project documents benchmarks. Goose is written in Rust and gemini-cli in TypeScript, but speed in practice depends mostly on the model and provider you use.
- Can I use both?
- Nothing in either project prevents it, since both run locally and extend through MCP. Goose also lists Gemini as a provider, reached through your subscription via the Agent Communication Protocol (ACP) or an API key.
- Which is easier to configure?
- gemini-cli installs through Homebrew, npm or npx, and signs in with Google OAuth, a Gemini API key or Vertex AI. Goose installs by curl script and needs a provider choice, via API key or subscription. Neither project compares setup effort.
- Which has a free tier?
- gemini-cli documents a free tier with Google account OAuth: 60 requests/min and 1,000 requests/day. Goose documents no such tier, and its cost depends on the provider you connect.