| | --- |
| | title: Agentic LLM Price Comparisons |
| | emoji: 🤖 |
| | colorFrom: blue |
| | colorTo: green |
| | sdk: static |
| | pinned: false |
| | short_description: 218 tool-calling LLMs analyzed by cost and context |
| | --- |
| | |
| | # Agentic LLM Price Comparison Dashboard |
| |
|
| | Interactive visualization dashboard analyzing 218 LLM models with tool-calling capabilities from OpenRouter's API. |
| |
|
| | ## Overview |
| |
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| | This dashboard provides a comprehensive cost-effectiveness analysis of language models supporting tool calling - essential for: |
| | - Agentic AI systems |
| | - MCP (Model Context Protocol) implementations |
| | - Multi-tool orchestration workflows |
| | - Function calling and API integration |
| |
|
| | ## Features |
| |
|
| | - **Quadrant Analysis**: Interactive scatter plot comparing cost vs context window size |
| | - **Top Value Models**: Best models by value score in each category |
| | - **Distribution Charts**: Context window and vendor analysis |
| | - **Searchable Table**: Complete dataset with filtering capabilities |
| | - **Key Insights**: Automated analysis of pricing trends and standout models |
| |
|
| | ## Data Source |
| |
|
| | - **Source**: [OpenRouter API](https://openrouter.ai/) |
| | - **Snapshot Date**: November 8, 2025 |
| | - **Models Analyzed**: 218 with tool calling support |
| | - **Analysis Repo**: [GitHub](https://github.com/danielrosehill/OR-Models-With-Tools-0811) |
| |
|
| | ## Quadrant Framework |
| |
|
| | Models are categorized by: |
| | - **Cost per token**: Economic efficiency for production deployment |
| | - **Context window**: Capability for complex, long-form tasks |
| |
|
| | This creates four strategic quadrants for model selection based on use case requirements. |
| |
|
| | ## Note on Pricing |
| |
|
| | All prices are point-in-time snapshots. For current pricing, always refer to OpenRouter's live API at [openrouter.ai](https://openrouter.ai/). |
| |
|
| | --- |
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|
| | Built with Chart.js, PapaParse, and vanilla JavaScript. Hosted as a static Hugging Face Space. |
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