Gemini CLI offers a generous free tier that covers the use cases for many individual developers. For enterprise / professional usage, or if you need higher limits, there are multiple possible avenues depending on what type of account you use to authenticate.
See [privacy and terms](./tos-privacy.md) for details on Privacy policy and Terms of Service.
Note: published prices are list price; additional negotiated commercial discounting may apply.
For users who authenticate by using their Google account to access Gemini Code Assist for individuals. This includes:
- 1000 model requests / user / day
- 60 model requests / user / minute
- Model requests will be made across the Gemini model family as determined by Gemini CLI.
Learn more at [Gemini Code Assist for Individuals Limits](https://developers.google.com/gemini-code-assist/resources/quotas#quotas-for-agent-mode-gemini-cli).
- [Google AI Pro and AI Ultra](https://cloud.google.com/products/gemini/pricing) by signing up at [Set up Gemini Code Assist](https://goo.gle/set-up-gemini-code-assist). This is recommended for individual developers. Quotas and pricing are based on a fixed price subscription.
For predictable costs, you can log in with Google.
Learn more at [Gemini Code Assist Quotas and Limits](https://developers.google.com/gemini-code-assist/resources/quotas)
- [Purchase a Gemini Code Assist Subscription through Google Cloud ](https://cloud.google.com/gemini/docs/codeassist/overview) by signing up in the Google Cloud console. Learn more at [Set up Gemini Code Assist] (https://cloud.google.com/gemini/docs/discover/set-up-gemini) Quotas and pricing are based on a fixed price subscription with assigned license seats. For predictable costs, you can sign in with Google.
This includes:
- Gemini Code Assist Standard edition:
- 1500 model requests / user / day
- 120 model requests / user / minute
- Gemini Code Assist Enterprise edition:
- 2000 model requests / user / day
- 120 model requests / user / minute
- Model requests will be made across the Gemini model family as determined by Gemini CLI.
[Learn more about Gemini Code Assist Standard and Enterprise license limits](https://developers.google.com/gemini-code-assist/resources/quotas#quotas-for-agent-mode-gemini-cli).
If you hit your daily request limits or exhaust your Gemini Pro quota even after upgrading, the most flexible solution is to switch to a pay-as-you-go model, where you pay for the specific amount of processing you use. This is the recommended path for uninterrupted access.
Learn more at [Vertex AI Dynamic Shared Quota](https://cloud.google.com/vertex-ai/generative-ai/docs/resources/dynamic-shared-quota) and [Vertex AI Pricing](https://cloud.google.com/vertex-ai/pricing).
- Cost: Varies by pricing tier and model/token usage.
Learn more at [Gemini API Rate Limits](https://ai.google.dev/gemini-api/docs/rate-limits), [Gemini API Pricing](https://ai.google.dev/gemini-api/docs/pricing)
It’s important to highlight that when using an API key, you pay per token/call. This can be more expensive for many small calls with few tokens, but it's the only way to ensure your workflow isn't interrupted by quota limits.
These plans currently apply only to the use of Gemini web-based products provided by Google-based experiences (for example, the Gemini web app or the Flow video editor). These plans do not apply to the API usage which powers the Gemini CLI. Supporting these plans is under active consideration for future support.
When using a Pay as you Go API key, be mindful of your usage to avoid unexpected costs.
- Don't blindly accept every suggestion, especially for computationally intensive tasks like refactoring large codebases.
- Be intentional with your prompts and commands. You are paying per call, so think about the most efficient way to get the job done.
## Gemini API vs. Vertex
- Gemini API (gemini developer api): This is the fastest way to use the Gemini models directly.
- Vertex AI: This is the enterprise-grade platform for building, deploying, and managing Gemini models with specific security and control requirements.
## Understanding your usage
A summary of model usage is available through the `/stats` command and presented on exit at the end of a session.