LiteLLM Model Prices Viewer
A sortable and filterable web interface for viewing large language model (LLM) pricing, context window sizes, and features, based on data from the LiteLLM project.
Overview
This tool provides a comprehensive and up-to-date view of the LLM landscape by fetching and displaying data directly from LiteLLM’s widely-used model_prices_and_context_window.json
file. It allows users to easily compare models from various providers based on cost, context size, and supported features like function calling, vision, and audio capabilities.
Features
- Live Data: Fetches the latest model data from the BerriAI/litellm GitHub repository on page load.
- Advanced Search: Use a global search bar with
&
(AND) and |
(OR) operators to quickly find models.
- Column-Level Filtering: Filter models by provider, mode, context window size, cost, and specific features.
- Dynamic Sorting: Sort the table by any column, including model name, provider, context sizes, and costs.
- Shareable URLs: All filter and search states are stored in the URL, allowing you to share your exact view with others.
- Feature Badges: Quickly identify model capabilities like Vision, Function Calling, and Audio support through clear visual badges.
- Cost Formatting: Displays costs in a human-readable format (cost per 1 million tokens).
Usage
- Open the LiteLLM’s Model Prices page.
- Use the main search bar to find models using keywords (e.g.,
gpt & 4
or claude | sonnet
).
- Use the filter inputs and dropdowns at the top of each column to narrow down the results.
- Click on any column header to sort the data. Click again to reverse the sort order.
- The table will update in real-time as you apply filters and sorting.
- Click “Clear Filters” to reset the view.
Technical Details
- Built with vanilla JavaScript and styled with TailwindCSS.
- Fetches data from the LiteLLM GitHub repository via the
fetch
API.
- Performs all filtering, sorting, and rendering client-side.
- Uses URL
searchParams
to maintain and share the state of the filters and search queries.
Credits
For issues, feature requests, or contributions, please open an issue on GitHub.