> For the complete documentation index, see [llms.txt](https://docs.ccv.brown.edu/ai-tools/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.ccv.brown.edu/ai-tools/costs-and-limits.md). # Costs and Limits Describes user and system budgets At the moment our services are free to the community, however we apply usage limits to manage overall costs and guarantee fair usage for everyone in the Brown community. ## Transcribe ### Per-user limit (daily) Each user can upload and transcribe **20 hours** of audio/video files each day. Once the limit is reached, the users will not be able to submit transcription jobs. **This limit resets at 0:00 UTC each day.** ### System-wide limit Transcribe does not have any system-wide limit at the moment. ## LibreChat ### Individual Limits (Monthly) Individuals have a budget of **twenty dollars ($20) per month**. In practice, this budget is converted into tokens. Models have different costs. We label them in the UI with three different categories, $, $$, $$$ to provide guidance on the cost of the model. Cost for the month align with calendar months **(limits reset on the 1st of each month)**. ### System wide limit (Monthly) We have total budget allocated to the system. Users will not be able to use the system if they have reached their individual limit, or if as an university we have reached the system limit. Cost for the month align with calendar months (limits reset on the 1st of each month). ### Purchasing additional tokens We do not have that capability at this time. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.ccv.brown.edu/ai-tools/costs-and-limits.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.