Visualize model performance on function calling tasks
Display benchmark results
Browse and submit LLM evaluations
Push a ML model to Hugging Face Hub
Rank machines based on LLaMA 7B v2 benchmark results
Compare code model performance on benchmarks
Generate leaderboard comparing DNA models
Evaluate AI-generated results for accuracy
Open Persian LLM Leaderboard
Text-To-Speech (TTS) Evaluation using objective metrics.
Browse and filter machine learning models by category and modality
Benchmark AI models by comparison
Compare model weights and visualize differences
The Nexus Function Calling Leaderboard is a tool designed to visualize and benchmark model performance on function calling tasks. It provides a comprehensive platform to compare and analyze the effectiveness of different models in executing specific functions, helping users make informed decisions based on performance metrics.
• Real-time performance metrics: Track model accuracy, execution speed, and success rates in real-time. • Customizable benchmarks: Define specific function calling tasks to test models in scenarios relevant to your use case. • Comparison tools: Easily compare the performance of multiple models on the same task. • Visual analytics: Detailed graphs and charts to help interpret performance data. • Community-driven insights: Access a community-sourced repository of benchmarked models and tasks. • User-friendly interface: Intuitive dashboard design for seamless navigation and analysis.
What models are supported by Nexus Function Calling Leaderboard?
The platform supports a wide range of models, including popular AI frameworks and custom models. Check the documentation for a full list of supported models.
How often are the benchmarks updated?
Benchmarks are updated in real-time as new models are added or existing ones are retested. You can also request specific models to be benchmarked.
Can I use Nexus Function Calling Leaderboard for private benchmarks?
Yes, the platform allows you to run private benchmarks for internal use. Contact support for details on setting up a private instance.