Embed and use ZeroEval for evaluation tasks
Explore and filter model evaluation results
Display a treemap of languages and datasets
Open Agent Leaderboard
More advanced and challenging multi-task evaluation
Calculate VRAM requirements for running large language models
A Leaderboard that demonstrates LMM reasoning capabilities
Explore speech recognition model performance
World warming land sites
Analyze and visualize data with various statistical methods
Generate synthetic dataset files (JSON Lines)
Browse and compare Indic language LLMs on a leaderboard
Explore and submit NER models
ZeroEval Leaderboard is a data visualization tool designed to help users evaluate and compare AI models effectively. It provides a centralized platform to embed and utilize ZeroEval for various evaluation tasks, making it easier to track performance metrics and benchmark AI solutions.
• Real-Time Updates: Track performance metrics as they change with real-time data updates.
• Customizable Dashboards: Tailor the visualization to focus on key performance indicators relevant to your tasks.
• Historical Data Tracking: Analyze trends and improvements in model performance over time.
• Advanced Filtering: Narrow down data to specific models, tasks, or timeframes for precise analysis.
• Multiple Visualization Options: Choose from charts, tables, and other visualizations to present data effectively.
• Integration with AI Tools: Seamlessly embed ZeroEval into your existing AI workflows and tools.
• Responsive Design: Access the leaderboard from various devices with an optimized viewing experience.
What is ZeroEval Leaderboard used for?
ZeroEval Leaderboard is used to evaluate and compare the performance of AI models, providing insights through visualized data.
Can I customize the appearance of the leaderboard?
Yes, users can customize the dashboard layout, choose visualization types, and apply filters to focus on specific metrics.
How often is the leaderboard updated?
The leaderboard updates in real-time, ensuring that users always have the most current performance data. However, delays may occur based on the frequency of model evaluations.