Multilingual metrics for the LMSys Arena Leaderboard
Cluster data points using KMeans
Form for reporting the energy consumption of AI models.
Mapping Nieman Lab's 2025 Journalism Predictions
Display a Bokeh plot
VLMEvalKit Evaluation Results Collection
Transfer GitHub repositories to Hugging Face Spaces
Visualize dataset distributions with facets
Try the Hugging Face API through the playground
Finance chatbot using vectara-agentic
Filter and view AI model leaderboard data
Submit evaluations for speaker tagging and view leaderboard
Calculate VRAM requirements for running large language models
The Multilingual LMSys Chatbot Arena Leaderboard is a comprehensive platform designed to evaluate and compare chatbots across multiple languages. It provides multilingual metrics to assess chatbot performance, making it a valuable tool for developers, researchers, and enthusiasts. The leaderboard allows users to benchmark chatbots, track progress, and identify top-performing models in various languages.
What metrics are used to evaluate chatbots on the leaderboard?
The leaderboard uses a variety of metrics, including accuracy, fluency, contextual understanding, and response time, to provide a holistic evaluation of chatbot performance.
How often is the leaderboard updated?
The leaderboard is updated regularly to reflect new models, improvements in existing models, and advancements in evaluation metrics.
Can I submit my own chatbot for evaluation?
Yes, the platform allows developers to submit their chatbots for evaluation, provided they meet the submission guidelines and requirements.